Novel systems and methods for effective infrastructure management

Abstract

Novel systems and methods for infrastructure management are described herein. Exemplar novel systems and methods include using a network of sensors for measuring fluid condition attribute at constraint locations inside infrastructure, a fluid flow controller for calculating stress at the constraint locations and a flow-redistributing component for redistributing fluid flow through one or more routes inside infrastructure to relieve stress at the constraint locations. Novel systems and methods for implementing infrastructure management strategies are also described herein. They include structural components to carry out features like obtaining data and / or estimated values, calculating and / or estimating stress values, developing flow redistributing strategies for relieving stress in infrastructure, and implementing these strategies to relieve stress. Novel systems and methods to adapt flow control to the changing storm conditions are also described herein. These systems and methods adjust flow redistributing strategies, in real time, in response to the changing storm severity.

Description

NOVEL SYSTEMS AND METHODS FOR EFFECTIVE INFRASTRUCTURE MANAGEMENTRELATED CASE

[0001] This patent application claims priority to U.S. provisional patent application number 63 / 592,923 filed on October 25, 2023, which is incorporated herein by reference for all purposes.FIELD

[0002] The present teachings generally relate to novel present systems and methods for effective fluid flow control during urban development, shifts in water use patterns, and / or variable weather conditions, with particular emphasis on climate events. More particularly, the present teachings relate to novel present systems and methods for effective fluid flow control during urban development, shifts in water use patterns, and / or variable weather conditions, with particular emphasis on climate events (e.g., storm events), by redistributing fluid flow to relieve undesirable stresses caused by overflow or flooding in and / or failure of fluid infrastructure.BACKGROUND

[0003] Fluid infrastructure includes such items as catchments, subcatchments, pumps, diversions, storage tanks, wells, treatment units, and conveyances used during transportation or processing of fluid or water. Examples of fluid infrastructure network include sewage system, groundwater well system, aquafer, aqueduct network and rain harvesting system. These types of infrastructure network are designed to collect and deliver fluid streams and sometimes treat the delivered fluid streams. By way of example, infrastructure networks dedicated to collecting and delivering treated water for drinking and agricultural and industrial use must be properly managed as they are integral to human life. Unfortunately, regardless of whether fluid treatment is necessary or not, current infrastructure management suffers from several drawbacks as it is time consuming, arduous and financially burdensome. Moreover, these drawbacks pale in comparison to the inability of the current infrastructure management to appropriately respond during climate events.

[0004] What is, therefore, required are novel systems and methods that effectively manage infrastructure, during climate events, without suffering from the drawbacks of the current infrastructure management.SUMMARY

[0005] The present teachings offer novel systems and methods (hereinafter “present systems” or “present arrangements,” and “present methods,” respectively) that are designed to effectively manage fluid infrastructure, without suffering from the drawbacks of current infrastructure management technologies. The present arrangements and methods effectively manage infrastructure such as wastewater or sewage systems, particularly during shifts in water use patterns, and / or variable and sometimes unpredictable weather conditions like storm events. The present teachings recognize that in urban environments, for example, sudden influxes of water resulting from storms tend to increase fluid flow, beyond their predetermined capacities, in wastewater streams. An excessive increase in fluid flow ultimately leads to wastewater or sewage overflow inside infrastructure and / or infrastructure failure, undesirably contaminating clean water streams and sources serving infrastructure.

[0006] Based on these recognitions, the present teachings implement novel approaches of monitoring and when necessary, such as during certain climate events (e.g., storm events), reducing or minimizing the resulting inordinate amount of stress placed on infrastructure due to excessive wastewater overflow. Under certain approaches, the present teachings provide systems and methods that balance fluid flow across multiple routes to reduce or minimize stress at one or more portions, e.g., constraint locations, of the infrastructure that are unduly stressed during climate events.

[0007] In sharp contrast to current infrastructure management systems and methods that are not be able to respond quickly enough to rapidly changing conditions during a climate event, the present systems and methods according to the present teachings, are capable of real-time infrastructure management using novel dynamic response techniques described herein. As a result, even if an intensity of a climate event is predicted incorrectly, the present systems and methods dynamically change from one response strategy to another, more effective response strategy that appropriatelyreduces or minimizes the stresses placed on infrastructure. The dynamic response features implemented by the present systems and methods handle both small and big storm events, replacing response strategies as conditions change.

[0008] The present systems and methods are also capable of learning from past events to improve future performance of the wastewater infrastructure management. Certain aspects of the present systems and methods, which are described in the claims herein, effectively solve these problems through various features and components, such as a network of sensors, flow control and / or flow distribution / redistribution components, and processors. Other aspects of the present systems and methods perform real-time data processing, perform predictive modeling using remote telemetry units (hereinafter “RTUs”), and / or implement adaptive flow control strategies.

[0009] In some aspects, the present teachings offer real-time infrastructure management systems. One such exemplar system includes: (1 ) an initial sensor disposed at or near an initial location and measuring fluid condition attribute at the initial location to produce initial values; (2) a subsequent sensor disposed at or near a subsequent location and measuring fluid condition attribute at the subsequent location to produce subsequent values, and wherein the subsequent sensor is located downstream from the initial sensor; (3) multiple intermediate sensors, at least one of which is disposed at or near and measures fluid condition attribute at one location of a first route to produce intermediate values, and at least another of the multiple intermediate sensors is disposed at or near and measures fluid condition attribute at one location of a second route to produce additional intermediate values, wherein each of the first route and the second route facilitate fluid communication between the initial location and the subsequent location, and the second route is different from the first route, and wherein each of the initial location, the one location of the first route, the one location of the second route, and the subsequent location is a constraint location in infrastructure as measurement of fluid condition attribute at each of the initial location, the one location of the first route, the one location of the second route, and the subsequent location, during a climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of the initial location,the one location of the first route, the one location of the second route, and the subsequent location, respectively; (4) one or more flow controllers communicatively coupled to receive, in real time, the initial values from the initial sensor, the subsequent values from the subsequent sensor, and the intermediate values and the additional intermediate values from the multiple intermediate sensors, and based upon the initial values, the subsequent values, the intermediate values and the additional intermediate values, determine, during the climate event and in real time, a stress value for each of the constraint locations, and implement one or more flow redistributing strategies that are based upon at least one of the stress values of at least one of the constraint locations; and (5) one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components, wherein each of the fluid flow intersections represents an intersection of the initial route, the first route and the second route, and at least one of the flowdistributing components, based upon one or more of flow distributing strategies received from one or more of the flow controllers during the climate event and in real time, redistribute fluid flow through at least one of the fluid flow intersections and among the initial route, the first route and the second route to effectively modify at least one of the stress values obtained from at least one of the constraint locations to be equal to or below the predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0010] In some aspects, the present teachings offer other real-time infrastructure management systems. One such exemplar system includes: (1 ) an initial sensor disposed at or near an initial location and measuring fluid condition attribute at the initial location to produce initial values; (2) a subsequent sensor disposed at or near a subsequent location and measuring fluid condition attribute at the subsequent location to produce subsequent values, and wherein the subsequent sensor is located downstream from the initial sensor; (3) one or more intermediate sensors disposed at or near and measuring fluid condition attribute at one location of the first route to produce intermediate values, wherein the first route facilitates fluid communication between theinitial location and the subsequent location, and wherein each of the initial location, the one location of the first route and the subsequent location is a constraint location in infrastructure as measurement of fluid condition attribute at each of the initial location, the one location of the first route and the subsequent location, during a climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of the initial location, the one location of the first route and the subsequent location, respectively; (4) one or more flow controllers communicatively coupled to receive, in real time, the initial values from the initial sensor, the subsequent values from the subsequent sensor and the intermediate values from one or more of the intermediate sensors, and based upon the initial values, the subsequent values and the intermediate values, determine, during the climate event and in real time, a stress value at each of the constraint locations, and implement one or more flow redistributing strategies that are based upon at least one of the stress values of at least one of the constraint locations; and (5) one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components, wherein each of the fluid flow intersections represents an intersection of the initial route and the first route, and at least one of the flow-distributing components, based upon one or more of flow distributing strategies received from one or more of the flow controllers, during the climate event and in real time, redistribute fluid flow through at least one of the fluid flow intersections and between the initial route and the first route to effectively modify at least one of the stress values obtained from at least one of the constraint locations to be equal to or below the predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0011] In some aspects, the present teachings offer other real-time infrastructure management systems. One such exemplar systems include: (1 ) a subsequent sensor disposed at or near a subsequent location and measuring fluid condition attribute at the subsequent location to produce subsequent values, and wherein the subsequent sensor is located downstream from an initial location; (2) multiple intermediate sensors, at leastone of which is disposed at or near and measures fluid condition attribute at the one location of a first route to produce intermediate values, and at least another of the multiple intermediate sensors is disposed at or near one location of a second route and measures fluid condition attribute at the one location of a second route to produce additional intermediate values, wherein each of the first route and the second route facilitate fluid communication between the initial location and the subsequent location, and the second route is different from the first route, and wherein each of the one location of the first route, the one location of the second route, and the subsequent location is a constraint location in infrastructure as measurement of fluid condition attribute at each of the one location of the first route, the one location of the second route, and the subsequent location, during the climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of the one location of the first route, the one location of the second route, and the subsequent location, respectively; (3) one or more flow controllers communicatively coupled to receive, in real time, the subsequent values from the subsequent sensor, and the intermediate values and the additional intermediate values from the multiple intermediate sensors, and based thereupon upon the subsequent values, the intermediate values and the additional intermediate values, determine, during the climate event and in real time, a stress value at each of the constraint locations, and implement one or more flow redistributing strategies that are based upon at least one of the stress values of at least one of the constraint locations; and (4) one or more flowdistributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components, wherein each of the fluid flow intersections represents an intersection of the first route and the second route, and at least one of the flow-distributing components, based upon one or more of the flow distributing strategies received from one or more of the flow controllers during the climate event and in real time, redistribute fluid flow through at least one of the fluid flow intersections and between the first route and the second route to effectively modify atleast one of the stress values obtained from at least one of the constraint locations to be equal to or below the predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0012] In some aspects, the present teachings offer other real-time infrastructure management systems. One such exemplar system includes: (1 ) a subsequent sensor designed to be disposed at or near and measuring fluid condition attribute at a subsequent location to produce subsequent values, and wherein the subsequent sensor is downstream from an initial location; (2) multiple intermediate sensors, at least one of which is designed to be disposed at or near and measuring a fluid condition attribute at one location of the first route to produce one or more intermediate values, and at least another of the multiple intermediate sensors is designed to be disposed at or near and measuring fluid condition attribute at one location of the second route to produce one or more additional intermediate values, and wherein the first route and the second route facilitate fluid communication between the initial location and the subsequent location, wherein the fluid condition attribute at the one location of the first route and the one location of the second route is affected by one or more intermediate streams flowing into the first route and the second route prior to the one location of the first route and prior to the one location of the second route, respectively; (3) multiple intermediate remote telemetry units ("RTUs"), at least two of which are communicatively coupled to the multiple intermediate sensors and at least one of the multiple intermediate RTUs has stored therein one flow model, which is a synchronized machine-learning model designed to estimate and generate an RTU estimated range of intermediate values for the one location of the first route, as a function of time and based upon a climate event forecast and one or more of the intermediate values at the one location of the first route, and at least another of the multiple intermediate RTUs has stored therein another flow model, which is a synchronized machine-learning model designed to estimate and generate an additional RTU estimated range of intermediate values for the one location of the second route, as a function of time and based upon the climate event forecast and one or more of the additional intermediate values at the one location of the second route, and wherein the multiple intermediate RTUs are designed to convey one or more of the intermediate values, if one or more of the intermediate values are not within theRTU estimated range of intermediate values for the one location of the first route and also designed to convey one or more of the additional intermediate values, if one or more of the additional intermediate values are not within the additional RTU estimated range of intermediate values for the one location of the second route; (4) a server designed for communicatively coupling with the multiple intermediate RTUs, and the server having stored therein a digital twin model of the one flow model, wherein the digital twin of the one flow model is substantially similar to the one flow model stored on one of the intermediate RTUs, wherein the server is designed to estimate, based upon the climate event forecast and one or more of the intermediate values, fluid condition attribute at or near the one location of the first route and provide a server estimated range of intermediate values for the one location of the first route, and the server has also stored therein a digital twin of the another flow model, wherein the digital twin of the another flow model is substantially similar to the another flow model stored on another of the multiple intermediate RTUs monitoring the one location of the second route, wherein the server produces at least one additional server estimated range of intermediate values based upon the climate storm event forecast and one or more of the additional intermediate values, and the server is designed to receive, from one or more of the multiple intermediate RTUs, one or more of the intermediate values that are not within the RTU estimated range of intermediate values for the one location of the first route and also designed to receive one or more of the additional intermediate values that are not within the additional RTU estimated range of intermediate values for the one location of the second route, and the server is designed to convey one or more of the intermediate values that are not within the server estimated range of intermediate values for the one location of the first route and also designed to convey one or more of the additional intermediate values that are not within the additional server estimated range of intermediate values for the one location of the second route; (5) one or more flow controllers designed to be communicatively coupled for receiving, in real-time, initial values from the initial sensor, subsequent values from the subsequent sensor, one or more of the intermediate values or at least one of the server estimated range of intermediate values, or one or more of the additional intermediate value or at least one the server estimated additional intermediate values from the server, and one of the flowcontrollers is programmed to determine, in real-time, a stress value for each of the initial location and the subsequent location, a stress value or an estimated stress value for each of the one location of the first route and the one location of second first route based upon the initial value, the subsequent value, one or more of the intermediate values or at least one of the server estimated range of intermediate values, or one or more of the additional intermediate value or at least one the additional server estimated range of intermediate values, respectively; and (6) one or more flow-distributing components designed to be disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route and into one or more of the flow-distributing components, wherein the fluid flow intersection represents an intersection of the initial route, the first route and the second route, and wherein each of the flow-distributing components receive, from one or more of the flow controllers, one or more flow redistributing strategies that are based upon the stress value at each of the initial location and the subsequent condition, the stress value or the estimated stress value for each of the one location of the first route and the one location of the second route, and during the climate event and in real time, at least one of the flow-distributing components is designed to redistribute fluid flow through the fluid flow intersection location and among the initial route, the first route and the second route, based upon one of the flow redistributing strategies that effectively modifies the stress value and / or the estimated stress value of at least one of constraint locations in infrastructure such that the fluid condition attribute of at least one of the constraint locations is equal to or below a predetermined tolerable threshold attribute value that is assigned to at least one of the constraint locations; and (7) wherein the constraint location is one location chosen from a group comprising the initial location, the one location of the first route, the one location of the second route and the subsequent location, and measurement of fluid condition attribute at the location, during the climate event, are capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to the location.

[0013] In some aspects, the present teachings offer other real-time infrastructure management systems. One such exemplar system includes: (1 ) an initial sensor designed to be disposed at or near and measuring fluid condition attribute at an initial location, located on an initial route, to produce initial values, wherein the fluid condition attribute at the initial location is affected by one or more intermediate streams flowing into the initial route prior to the initial location; (2) an initial remote telemetry unit ("RTU") communicatively coupled to the initial sensor and has stored therein an initial flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at the initial location, as a function of time, and to produce, for a climate event, an RTU estimated range of initial values based upon the climate event forecast and the initial values, and wherein the initial RTU is designed to convey the initial values if the initial values are not within the RTU estimated range of initial values; (3) a subsequent sensor designed to be disposed at or near and measuring fluid condition attribute at the subsequent location to produce subsequent values, and wherein the subsequent sensor is downstream from the initial sensor, wherein the fluid condition attribute at the subsequent location is affected by one or more intermediate streams flowing into the subsequent location; (4) a subsequent RTU communicatively coupled to the subsequent sensor and has stored therein a subsequent flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at the subsequent location, as a function of time, wherein the subsequent RTU is designed to produce, based upon the climate event forecast and subsequent values, an RTU estimated range of subsequent values, and wherein the subsequent RTU is designed to convey the subsequent values, if the subsequent values are not within the RTU estimated range of subsequent values; (5) one or more intermediate sensors, at least one of which is designed to be disposed at or near and measuring a fluid condition attribute at one location of the first route to produce one or more intermediate values, and the first route facilitates fluid communication between the initial location and the subsequent location, wherein the fluid condition attribute at the one location of the first route is affected by one or more intermediate streams flowing into the first route prior to the one location of the first route; (6) one or more intermediate RTUs, each of which is communicatively coupled to at least one of the intermediate sensors and has storedtherein one flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at the one location of the first route, as a function of time, wherein one or more of the intermediate RTUs are designed to produce, for the climate event and based upon the climate event forecast and one or more of the intermediate values, an RTU estimated range of intermediate values, and wherein the intermediate RTU is designed to convey one or more of the intermediate values if one or more of the intermediate values are not within the RTU estimated range of intermediate values; (7) a server designed for communicatively coupling with the initial RTU, the subsequent RTU and one or more of the intermediate RTUs and having stored therein a digital twin of the initial flow model, the subsequent flow model and the one flow model, wherein the digital twin of each of the initial flow model, the subsequent flow model and the one flow model is substantially similar to the initial flow model, the subsequent flow model and the one flow model stored on the initial RTU, the subsequent RTU and one of the intermediate RTUs, respectively, wherein the server is designed to estimate, for the climate event and based upon the climate event forecast and one or more of the initial values, the subsequent values, and the intermediate values, fluid condition attribute at the initial location, the subsequent location and the one location of the first route, respectively, to provide a server estimated range of initial values, a server estimated range of subsequent values and a server estimated range of intermediate values, and the server is designed to receive from the initial RTU the initial values if the initial values are not within the RTU estimated range of initial values, receive from the subsequent RTU the subsequent values, if the subsequent values are not within the RTU estimated range of subsequent values, and receive from the intermediate RTU one or more of the intermediate values, if the intermediate values are not within the RTU estimated range of intermediate values, and the server is designed to convey those of the initial values, the subsequent values and the intermediate values that are not within the server estimates range of initial values, the server estimates range of subsequent values and the server estimates range of intermediate values, respectively; (8) one or more flow controllers designed to be communicatively coupled to receive from the server, in real-time, the initial values or the server estimated range of initial values, the subsequent values or the server estimated range of subsequentvalues, the intermediate values or the server estimates range of intermediate values; and (9) one of the flow controllers is programmed to determine, in real-time, a stress value or an estimated stress value for each of the initial location, the subsequent location and the one location of the first route, respectively, based upon the initial values or the server estimated range of initial values, the subsequent values or the server estimated range of subsequent values, the intermediate values of the server estimates range of intermediate values; and (10) one or more flow-distributing components designed to be disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through the initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route and into one or more of the flow-distributing components, wherein the fluid flow intersection represents an intersection of the initial route and the first route, and each of the flowdistributing components implement one of the flow redistributing strategies, received from one or more of the flow controllers, that redistribute during the climate event and in real time, based upon the stress value or the estimated stress value at each of the initial location, the subsequent condition, and the one location of the first route, fluid flow through the fluid flow intersection location and between the initial route and the first route to effectively modify the stress value or the estimated stress value obtained at the one location of the first route to be below a predetermined tolerable threshold attribute value that is assigned to the one location of the first route and / or to effectively modify the estimated stress value obtained at the initial location to be below a predetermined tolerable threshold attribute value that is assigned to the initial location; (11 ) wherein each of the initial location, the one location of the first route and the subsequent location is a constraint location in infrastructure as measurement or estimate of fluid condition attribute at the constraint location, during the climate event, are capable of reaching or exceeding, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to the constraint location.

[0014] In some aspects, the present teachings offer other real-time infrastructure management systems. One such exemplar system includes: (1 ) a subsequent sensor disposed at or near and measuring fluid condition attribute at a subsequent location toproduce subsequent values, and wherein the subsequent sensor is located downstream from an initial location, wherein the fluid condition attribute at the subsequent location is affected by one or more intermediate streams flowing into the subsequent location; (2) a subsequent RTU communicatively coupled to the subsequent sensor and has stored therein a subsequent flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at the subsequent location, as a function of time, wherein the subsequent RTU is designed to produce, for a climate event, an RTU estimated range of subsequent values based upon the climate event forecast and the subsequent values, and wherein the subsequent RTU is designed to convey the subsequent values if the subsequent values are not within at least one of the RTU estimated range of subsequent values; (3) multiple intermediate sensors, at least one of which is disposed at or near and measures fluid condition attribute at the one location of a first route to produce intermediate values of the first intermediate sensor, and at least another of the multiple intermediate sensors is disposed at or near one location of a second route and measures fluid condition attribute at the one location of a second route to produce intermediate values of the second intermediate sensor, wherein each of the first route and the second route facilitate fluid communication between the initial location and the subsequent location, and the second route is different from the first route, and wherein each of the one location of the first route, the one location of the second route, and the subsequent location is a constraint location in infrastructure as measurement of fluid condition attribute at each of the one location of the first route, the one location of the second route, and the subsequent location, during the climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of the one location of the first route, the one location of the second route, and the subsequent location, respectively; (4) multiple intermediate RTUs, at least two of which are communicatively coupled to two or more of the intermediate sensors and at least one of which has stored therein one flow model, which is a synchronized machine-learning model designed to generate an RTU estimated range of intermediate value for the one location of the first route, as a function of time, and at least another of the multiple intermediate RTUs has stored therein another flow model,which is a synchronized machine-learning model designed to generate, as a function of time, an additional RTU estimated range of intermediate values for the one location of the second route, and wherein at least one the RTUs is designed to convey one or more of the intermediate values, if one or more of the intermediate values is not within the RTU estimated range of intermediate value for the one location of the first route, and at least another of the multiple intermediate RTUs is designed to convey one or more of the additional intermediate values, if one or more of the additional intermediate values are not within the additional RTU estimated range of intermediate values for the one location of the second route; (5) a server designed for communicatively coupling with the subsequent RTU and one or more of the intermediate RTUs and having stored therein a digital twin of each of the subsequent flow model, the one flow model, and another flow model wherein the digital twin of each of the subsequent flow model, the one flow model and another flow model is substantially similar to the subsequent flow model, the one flow model and the another flow model stored on the subsequent RTU, one of the intermediate RTUs, and another of the RTUs, respectively, wherein the server is designed to estimate, for the climate event and based upon the climate event forecast and the subsequent values, the intermediate values, and the additional intermediate values, fluid condition attribute at the subsequent location, the one location of the first route, and the one location of the second route, respectively, to provide a server estimated range of subsequent values, a server estimated range of intermediate values, and an additional server estimated range of intermediate values, and the server is designed to receive from receive from the subsequent RTU the subsequent values, if the subsequent values are not within the RTU estimated range of subsequent values, and receive from the intermediate RTU one or more of the intermediate values, if the intermediate values are not within the RTU estimated range of intermediate values, and receive from the another intermediate RTU the additional intermediate values, if the additional intermediate values are not within the additional RTU estimated range of intermediate values and the server is designed to convey those of the subsequent values, the intermediate values and the additional intermediate values that are not within the server estimates range of subsequent values, the server estimates range of intermediate values, and the additional server estimates range of intermediate values,respectively; (6) one or more flow controllers communicatively coupled to receive from the server, in real-time, the subsequent values or the server estimated range of subsequent values, the intermediate values or the server estimates range of intermediate values, and the additional intermediate values or the additional server estimates range of intermediate values, and one of the flow controllers is programmed to determine, in real-time, a stress value or an estimated stress value for each of the subsequent location, the one location of the first route, and the one location of the second route, respectively, based upon the subsequent values or the server estimated range of subsequent values, the intermediate values of the server estimates range of intermediate values, and the additional intermediate values or the additional server estimates range of intermediate values; and (7) one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components, wherein each of the fluid flow intersections represents an intersection of the first route and the second route, and at least one of the flow-distributing components, based upon one or more of the flow distributing strategies received from one or more of the flow controllers during the climate event and in real time, redistributes fluid flow through at least one of the fluid flow intersections and between the first route and the second route to effectively modify the stress value or the estimated stress value obtained for at least one of the constraint locations to be equal to or below the predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0015] In some aspects, the present teachings offer real-time methods of infrastructure management. One such exemplar method includes: (1 ) obtaining, at one or more fluid flow controllers, initial values using an initial sensor disposed at or near and measuring a fluid condition attribute at an initial location; (2) obtaining, at one or more of the fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring the fluid condition attribute at the subsequent location, and wherein the subsequent sensor is located downstream from the initial sensor; (3) obtaining, at one or more of the fluid flow controllers, one or more intermediate values using one or moreintermediate sensors, at least one of which is disposed at or near and measuring fluid flowing in or stored at one location of a first route providing fluid communication between the initial location and the subsequent location; (4) determining, in real time and using one or more of the fluid flow controllers, a stress value at each of the initial location, the one location on the first route and the subsequent location based upon the initial values, one or more of the intermediate values and the subsequent values, respectively, to produce an initial route stress value and a first route stress value; (5) identifying which one of the initial route stress value and the first route stress value is of highest magnitude and arriving at a highest stress route value, wherein the initial route stress value represents the stress value of at least the initial location, and the first route stress value represents a sum of the stress values at each of at least the one location on the first route and the subsequent location; and (6) redistributing fluid flow, during a climate event, in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, in the initial route and the first route to effectively reduce magnitude of the highest stress route value, wherein one or more of the flow-distributing components being disposed at one or more fluid flow intersections, each of which is located downstream from the initial location such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components and each of the fluid flow intersections intersects the initial route and the first route, and wherein one or more of the flow-distributing components are communicatively coupled to one or more of the fluid flow controllers.

[0016] In some aspects, the present teachings offer other real-time methods of infrastructure management. One such exemplar method includes: (1 ) obtaining, at one or more of the fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring a fluid condition attribute at the subsequent location, and wherein the subsequent sensor is located downstream from an initial location; (2) obtaining, at one or more of the fluid flow controllers, multiple intermediate values using multiple intermediate sensors, at least one of which is disposed at or near and measuring the fluid condition attribute at one location of a first route to produce one or more intermediate values and at least another of multiple intermediate sensors is disposed on and measuring the fluid condition attribute at one location of a secondroute to produce one or more additional intermediate values, wherein each of the first route and the second route providing fluid communication between the initial location and the subsequent location; (3) determining, in real time and using one or more of the fluid flow controllers, a stress value at each of the one location on the first route, the one location of the second route and the subsequent location based upon one or more of the intermediate values, one or more of the additional intermediate values and the subsequent values, respectively, to produce a first route stress value and a second route stress value; (4) identifying which one of the first route stress value and the second route stress value is of highest magnitude and generating a highest stress route value, wherein the first route stress value represents a summation of the stress value at each of the one location on the first route and the subsequent location and the second route stress value represents a summation of the stress values at each of the one location on the second route and the subsequent location; and (5) redistributing fluid flow, during a climate event and in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, between the first route and the second route to effectively reduce magnitude of the highest stress route value, wherein one or more of the flow-distributing components being disposed at one or more fluid flow intersections, each of which is located downstream from the initial location such that fluid flow exiting the initial location flows through an initial route into one or more of the flow-distributing components and each of the fluid flow intersections intersects the first route and the second route, and wherein one or more of the flowdistributing components are communicatively coupled to one or more of the fluid flow controllers.

[0017] In some aspects, the present teachings offer other methods of implementing infrastructure management strategies. One such exemplar method includes: (1 ) obtaining, at one or more fluid flow controllers, initial values using an initial sensor disposed at or near and measuring a fluid condition attribute at an initial location; (2) obtaining, at one or more of the fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring the fluid condition attribute at a subsequent location, and wherein the subsequent sensor is downstream from the initial sensor; (3) obtaining one or more intermediate values using one or more intermediatesensors disposed at or near and measuring the fluid condition attribute at a one location of a first route providing fluid communication between the first location and the subsequent location; (4) obtaining, based upon a climate event forecast and one or more of the intermediate values, one or more server estimated range of intermediate values using a server operating in conjunction with one or more of the intermediate sensors, and wherein the server is designed to receive the one or more of the intermediate values, and the server is communicatively coupled to one or more of the fluid flow controllers to convey the one or more server estimated intermediate values or one or more intermediate values, and the server conveys the intermediate values, if one or more of the intermediate values are not within the server estimated range of intermediate values; (5) determining, in real time and using one or more of the fluid flow controllers, a stress value for each of the initial location and the subsequent location based upon the initial value and the subsequent value, and a stress value or an estimated stress value for the one location of the first route based upon or one or more of the intermediate values and one or more of the server estimated intermediate values, respectively, to produce an initial route stress value and a first route stress value or an estimated first route stress value; (6) identifying which one of the initial route stress value, first route stress value and the estimated first route stress value is of highest magnitude and arriving at a highest stress route value, wherein the initial route stress value represents the stress value of at least the initial location, the first route stress value represents a summation of stress value for each of the one location of the first route and the subsequent location and the estimated first route stress value represents a summation of at least the estimated stress value of the one location of the first route and the stress value of the subsequent location; and (7) formulating, based upon the highest flow stress value, multiple infrastructure management strategies that reduce the highest stress route value; (8) comparing, using one or more key point indicators of success in reducing the highest flow stress value, each of the infrastructure management strategies to an outcome of the climate event; (9) determining, based on the comparing using one or more of the key point indicators of success in reducing the highest flow stress value, one or more successful infrastructure management strategies that effectively reduce the highest flow stress value; and (10) storing, in one or more ofthe fluid flow controllers, one or more of the successful infrastructure management strategies.

[0018] In some aspects, the present teachings offer other real-time methods of infrastructure management. One such exemplar method includes: (1 ) obtaining, at one or more of the fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring the fluid condition attribute at a subsequent location, and wherein the subsequent sensor is located downstream from an initial location; (2) obtaining multiple intermediate values using multiple intermediate sensors, at least one of which is disposed at or near and measuring the fluid condition attribute at a one location of a first route to produce one or more intermediate value, and another of the multiple intermediate sensors is disposed at or near and measuring the fluid condition attribute at a one location of a second route to produce one or more additional intermediate values, wherein each of the first route and the second route provide fluid communication between the first location and the subsequent location; (3) obtaining, based upon a climate event forecast and one or more of the intermediate values, one or more server estimated range of intermediate values using a server operating in conjunction with at least one of the intermediate sensors, obtaining, at one or more of the fluid flow controllers and based upon the climate event forecast and one or more of the additional intermediate values, one or more additional server estimated range of intermediate values using the server operating in conjunction with at least another of the intermediate sensors, and wherein the server is designed to receive one or more of the intermediate values and one or more of the additional intermediate values, and the server is communicatively coupled to convey to one or more of the fluid flow controllers one or more of the intermediate values or one or more the server estimated range of intermediate values and one or more of the additional intermediate values or one or more the additional server estimated intermediate values, and the server conveys one or more of the intermediate values, if one or more of the intermediate values are not within the server estimated range of intermediate values and conveys one or more of the additional intermediate values, if one or more of the additional intermediate values are not within the additional server estimated range of intermediate values; (4) determining, in real time and using one or more of the fluid flow controllers, a stressvalue of the subsequent location, and a stress value or an estimated stress value for each of the one location of the first route and the one location of the second route based upon one or more of the subsequent values, one or more of the intermediate values or one or more of the server estimated range of intermediate values, one or more of the additional intermediate values or one or more of the additional server estimated range of intermediate values, respectively, and based upon the stress value or the estimated stress value for each of the one location of the first route and the one location of the second route, producing a stress value or an estimated stress value for each of the first route and the second route; (5) identifying which one of the stress value or the estimated stress value for the first route and the stress value or the estimated stress value for the second route is of highest magnitude and arriving at a highest stress route value, wherein the stress value or the estimated stress value for the first route represents a summation of at least the stress value or the estimated stress value for the one location of the first route and the stress value of the subsequent location, respectively, and the stress value or the estimated stress value for the second route represents a summation of at least the stress value or the estimated stress value for the one location of the second route and the stress value of the subsequent location, respectively; and (6) redistributing fluid flow, during the climate event and in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, between the first route and the second route to effectively reduce magnitude of the highest stress route value, wherein one or more of the flowdistributing components being disposed at one or more fluid flow intersections, each of which is located downstream from the initial location such that fluid flow exiting the initial location flows through an initial route into one or more of the flow-distributing components and each of the fluid flow intersections intersects the first route and the second route, and wherein one or more of the flow-distributing components are communicatively coupled to one or more of the fluid flow controllers.

[0019] In some aspects, the present teachings offer other methods of implementing infrastructure strategies. One such exemplar method includes: (1 ) obtaining, based upon initial values and a climate event forecast, a server estimated range of initial values using a server operating in conjunction with one or more initial sensors, at leastone of which is disposed at or near and measures a fluid condition attribute at an initial location to produce the initial values, and wherein the server is communicatively coupled to convey to one or more of the fluid flow controllers the initial values or the server estimated range of initial values, and server conveys the initial values, if the initial values are not within the server estimated range of initial values; (2) obtaining, at one or more of the fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measures the fluid condition attribute at the subsequent location, and wherein the subsequent sensor is downstream from the initial sensor; (3) obtaining, based upon a climate event forecast and intermediate values, a server estimated range of intermediate values using a server operating in conjunction with one or more intermediate sensors, at least one of which is disposed at or near and measures a fluid condition attribute at a location on a first route to produce the intermediate values, and wherein the server is communicatively coupled to convey to one or more of the fluid flow controllers the intermediate values or the server estimated range of intermediate values, and server conveys the intermediate values, if the intermediate values are not within the server estimated range of intermediate values, and wherein the first route provides fluid communication between the initial location and the subsequent location; (4) determining, at one or more of the fluid flow controllers, a stress value for the subsequent location based upon the subsequent values and a stress value or an estimated stress value for each of the initial location and the one location of the first route based upon the initial values or the server estimated range of initial values, and one or more of the intermediate values or the server estimated range of intermediate values, respectively; (5) formulating, based upon the stress value for the subsequent location and the stress value or the estimated stress value for each of the initial location and the one location of the first route, one or more infrastructure management strategies that reduce the stress value or the estimated stress value at the initial location and / or the stress value or estimated stress value at the one location of the first route; (6) comparing each of the infrastructure management strategies to an outcome of the climate event using one or more key point indicators of success in reducing the stress value or the estimated stress value at the initial location and / or the stress value or the estimated stress value at the one location of the first route; (7)determining, based upon the comparing using one or more of the key point indicators of success in reducing the stress value or the estimated stress value at the initial location and / or the stress value or the estimated stress value at the one location of the first route, one or more successful infrastructure management strategies that effectively reduce the stress value or the estimated stress value at the initial location and / or stress value or the estimated stress value at the one location of the first route; (8) storing, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies; (9) retrieving, during a subsequent climate event and from one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies; and (10) redistributing fluid flow between the initial route and the first route, using one or more of the successful infrastructure management strategies, to effectively reduce stress at the initial location and / or at the one location of the first route during the subsequent climate event, wherein the redistributing is carried out using one or more flow-distributing components disposed at one or more flow intersections, each being downstream from the initial location such that fluid flow exiting the initial location flows through an initial route into one or more of the flow-distributing components and each of the fluid flow intersection location intersects the initial route and the first route.

[0020] In some aspects, the present teachings offer methods of implementing infrastructure strategies. One such exemplar method includes: (1 ) obtaining, at one or more of fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring the fluid condition attribute at a subsequent location, and wherein the subsequent sensor is downstream from an initial location; (2) obtaining multiple intermediate values using multiple intermediate sensors, at least one of which is disposed at or near and measuring the fluid condition attribute at a one location of a first route to produce one or more intermediate value, and another of the multiple intermediate sensors is disposed at or near and measuring the fluid condition attribute at a one location of a second route to produce one or more additional intermediate values, wherein each of the first route and the second route provide fluid communication between the first location and the subsequent location; (3) obtaining, based upon a climate event forecast and one or more of the intermediate values, one or more serverestimated range of intermediate values using a server operating in conjunction with at least one of the intermediate sensors, obtaining, at one or more of the fluid flow controllers and based upon the climate event forecast and one or more of the additional intermediate values, one or more additional server estimated range of intermediate values using the server operating in conjunction with at least another of the intermediate sensors, and wherein the server is designed to receive one or more of the intermediate values and one or more of the additional intermediate values, and the server is communicatively coupled to convey to one or more of the fluid flow controllers one or more of the intermediate values or one or more the server estimated range of intermediate values and one or more of the additional intermediate values or one or more the additional server estimated intermediate values, and the server conveys one or more of the intermediate values, if one or more of the intermediate values are not within the server estimated range of intermediate values and conveys one or more of the additional intermediate values, if one or more of the additional intermediate values are not within the additional server estimated range of intermediate values; (4) determining, in real time and using one or more of the fluid flow controllers, a stress value of the subsequent location, and a stress value or an estimated stress value for each of the one location of the first route and the one location of the second route based upon one or more of the subsequent values, one or more of the intermediate values or one or more of the server estimated range of intermediate values, one or more of the additional intermediate values or one or more of the additional server estimated range of intermediate values, respectively, and based upon the stress value or the estimated stress value for each of the one location of the first route and the one location of the second route, producing a stress value or an estimated stress value for each of the first route and the second route; (5) identifying which one of the stress value or the estimated stress value for the first route and the stress value or the estimated stress value for the second route is of highest magnitude and arriving at a highest stress route value, wherein the stress value or the estimated stress value for the first route represents a summation of at least the stress value or the estimated stress value for the one location of the first route and the stress value of the subsequent location, respectively, and the stress value or the estimated stress value for the second routerepresents a summation of at least the stress value or the estimated stress value for the one location of the second route and the stress value of the subsequent location, respectively; (6) redistributing fluid flow, during the climate event and in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, between the first route and the second route to effectively reduce magnitude of the highest stress route value, wherein one or more of the flowdistributing components being disposed at one or more fluid flow intersections, each of which is located downstream from the initial location such that fluid flow exiting the initial location flows through an initial route into one or more of the flow-distributing components and each of the fluid flow intersections intersects the first route and the second route, and wherein one or more of the flow-distributing components are communicatively coupled to one or more of the fluid flow controllers; (7) determining, based upon the comparing using one or more of the key point indicators of success in reducing the stress value or the estimated stress value of each of the first route and the second route or in reducing the stress value or the estimated stress value at each of the one location of the first route and / or one location of the second route, one or more successful infrastructure management strategies; and (8) storing, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies.

[0021] In some aspects, the present teachings offer other methods of implementing infrastructure strategies. One such exemplar method includes: (1 ) obtaining, based upon initial values and a climate event forecast, a server estimated range of initial values using a server operating in conjunction with one or more initial sensors, at least one of which is disposed at or near and measuring a fluid condition attribute at an initial location to produce the initial values, and wherein the server is communicatively coupled to and conveys to one or more of the fluid flow controllers the initial values or the server estimated range of initial values, and the server conveys the initial values, if the initial values are not within the server estimated range of initial values; (2) obtaining, based upon subsequent values and the climate event forecast, a server estimated range of subsequent values using the server operating in conjunction with one or more subsequent sensors, at least one of which is disposed at or near and measuring a fluidcondition attribute at a subsequent location to produce the subsequent values, and wherein the server conveys the subsequent values or the server estimated range of subsequent values, and the server conveys the subsequent values, if the subsequent values are not within server estimated range of subsequent values; (3) obtaining, based upon the climate event forecast and one or more intermediate values, one or more server estimated intermediate range of values using the server operating in conjunction with one or more intermediate sensors, at least one of which is disposed at one location on a first route providing fluid communication between the initial location and the subsequent location, wherein at least one of the intermediate sensors measures the fluid condition attribute at the one location of the first route to produce one or more of the intermediate values, and wherein the server conveys the intermediate values or one or more of the server estimated intermediate range of values to one or more of the fluid flow controllers, and the server conveys the intermediate values, if the intermediate values are not within one or more of the server estimated intermediate range of values; (4) determining a stress value or an estimated stress value for each of the initial location, the one location of the first route and the subsequent location based upon the initial values or the server estimated range of initial values, one or more of the intermediate values or one or more of the server estimated range of intermediate values, and the subsequent values or one or more of the server estimated range of subsequent values, respectively, wherein the determining includes using one or more of the fluid flow controllers, and wherein each of the initial location, the one location of the first route and the subsequent location is a constraint location in infrastructure as a measurement or an estimate of fluid condition attribute at or near the constraint location, during the climate event, is capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to the constraint location; (5) establishing a stress value or an estimated route stress value for each of the initial route and the first route by adding the stress values or the estimated stress values for constraint locations present along each of the initial route and the first route to produce an initial route stress value or an estimated initial route stress value and a first route stress value or an estimated first route stress value; (6) identifying which one of the initial route stress value or theestimated initial route stress value and the first route stress value or the estimated first route stress value has highest magnitude to arrive at least one highest stress route value; and (7) redistributing, during the climate event, in real time and based upon one of the flow redistributing strategies, fluid flow in the initial route and / or the first route, that effectively reduces magnitude of at least one of the highest stress route value.

[0022] In some aspects, the present teachings offer other methods of implementing infrastructure strategies. One such exemplar method includes: (1 ) obtaining, based upon subsequent values and a climate event forecast, one or more server estimated range of subsequent values using the server operating in conjunction with one or more subsequent sensors, at least one of which is disposed at or near and measuring a fluid condition attribute at a subsequent location to produce the subsequent values, and wherein the server conveys the subsequent values or the server estimated range of, and the server conveys the subsequent values, if the subsequent values are not within the server estimated range of subsequent values; (2) obtaining, based upon the climate event forecast and multiple intermediate values, a server estimated range of intermediate values and an additional server estimated range of intermediate values using the server operating in conjunction with multiple intermediate sensors, at least one of which is disposed at or near and measures the fluid condition attribute at one location on a first route to produce one or more intermediate values, wherein at least another of the multiple intermediate sensors is disposed at or near and measures the fluid condition attribute at the one location of the second route to produce one or more of the additional intermediate values, wherein the first route and the second route provide fluid communication between the initial location and the subsequent location and wherein the server estimated range of intermediate values are based upon the intermediate values and the additional server estimated range of intermediate values are based upon the additional intermediate values, and the server conveys to one or more of the fluid flow controllers one or more of the intermediate values or the server estimated range of intermediate values and the additional intermediate values or the additional server estimated range of intermediate values, and the server conveys one or more of the intermediate values, if one or more of the intermediate values are not within the server estimated range of intermediate values and the server conveys one or moreof the additional intermediate values, if one or more of the additional intermediate values are not within the additional server estimated range of intermediate values; (3) determining, at one or more of the fluid flow controllers, a stress value or an estimated stress value for each of the subsequent location, the one location of the first route and the one location on the second route based upon the subsequent values or the server estimated range of subsequent values, one or more of the intermediate values or the server estimated range of intermediate values, and one or more of the additional intermediate values or the additional server estimated range of intermediate values, respectively; (4) formulating, based upon the stress value or the estimated stress value for each of the subsequent location, the one location of the first route and the one location of the second route, multiple infrastructure management strategies that reduce stress along the first route and / or the second route; (5) comparing each of the infrastructure management strategies to an outcome of the climate event using one or more key point indicators of success in reducing the stress value or the estimated stress value for the first route and / or the second route; (6) determining, based upon the comparing using one or more of the key point indicators of success in reducing the stress value or the estimated stress value for the first route and / or the second route; and (7) storing, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies.

[0023] The construction and operation of the present systems and teachings together with the additional objects and advantages thereof, are better understood from the following detailed descriptions of specific embodiments when read in conjunction with the accompanying figures that are described below.BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 shows a schematic of a conventional approach to wastewater treatment that provides both low-quality and high-quality sewage treatment.

[0025] Figure 2 shows a simplified schematic of an underlying infrastructure served by the present infrastructure management systems and that highlights excessive fluid flow from intermediate streams (e.g., storm water drainage systems and smaller sewer lines) entering a fluid flow route (e.g., a trunk line and an interceptor line providing fluidcommunication between an initial location, e.g., fluid reservoir, catchment and subcatchment, and a subsequent location, e.g., wastewater treatment facility, and that, during a climate event, undesirably stresses infrastructure.

[0026] Figure 3 shows a present infrastructure management system, according to one embodiment of the present arrangements, that three fluid flow route options, e.g., an initial fluid flow route (hereinafter “initial route”), a first fluid flow route (hereinafter “first route”), and a second fluid flow route (hereinafter “second route”), for relieving stress on infrastructure.

[0027] Figure 4 shows another present infrastructure management system, according to another embodiment of the present arrangements, that provides two fluid flow route options, e.g., the first route and the second route, for relieving stress on infrastructure.

[0028] Figure 5 shows yet another present infrastructure management system, according to yet another embodiment of the present arrangements, that provides two fluid flow route options, e.g., the initial route and the first route, for relieving stress on infrastructure.

[0029] Figure 6 shows a perspective view of a flow-distributing component, according to one embodiment of the present systems, incorporated, in a novel manner, into a dynamic underflow control and that redistributes flow among or between various fluid flow route options, as shown in Figures 3-5, to reduce the undesirable stress on infrastructure.

[0030] Figure 7 shows a perspective view of another flow-distributing component, according to another embodiment of the present arrangements, incorporated into an outfall storage provision and that redistributes flow among or between various fluid flow route options, as shown in Figures 3-5, to reduce the undesirable stress on infrastructure.

[0031] Figure 8 shows a perspective view of yet another flow-distributing component, according to yet another embodiment of the present arrangements, incorporated into an offline storage provision and that redistributes flow among or between various fluid flow route options, as shown in Figures 3-5, to reduce the undesirable stress on infrastructure.

[0032] Figure 9 shows a perspective view of yet another flow-distributing component, according to another embodiment of the present arrangements, incorporated into a storage provision (e.g., storm tank) and that redistributes flow among or between various fluid flow route options, as shown in Figures 3-5, to reduce undesirable stress on infrastructure.

[0033] Figure 10 shows a control scheme, according to one embodiment of the present teachings, that control operation of the flow-distributing component shown in Figure 9 and implemented under different climate conditions to reduce undesirable stress on infrastructure.

[0034] Figure 11 A shows a setting, for a small storm, of a relatively high predetermined tolerable threshold attribute value in a graphical representation of numerical stress values versus a fluid condition attribute of fluid stored in storage provision shown in Figure 9.

[0035] Figure 11 B shows a setting, for a small storm, of a relatively high predetermined tolerable threshold attribute value in a graphical representation of numerical stress values versus a fluid condition attribute of fluid flowing through storage provision shown in Figure 9.

[0036] Figure 12A shows a setting, for a big storm, of a relatively low predetermined tolerable threshold attribute value in a graphical representation of numerical stress values versus a fluid condition attribute of fluid stored in storage provision shown in Figure 9.

[0037] Figure 12B shows a setting, for a big storm, of a relatively low predetermined tolerable threshold attribute value in a graphical representation of numerical stress values versus a fluid condition attribute of fluid flowing through storage provision shown in Figure 9.

[0038] Figure 13 shows a schematic of a decision support system, according to one embodiment of the present arrangements, and that, preferably, operates in real time and independently of obtaining sensor measurement values and / or estimated sensor values, generates one or more flow redistribution strategies to relieve stress and assist an operator, who implements one or more of the flow redistribution strategies.

[0039] Figure 14 shows a control system architecture, according to one embodiment of the present arrangements, that includes high-level strategy, low-level control and local control.

[0040] Figure 15 shows a schematic of a portion of an infrastructure network management system, according to one embodiment of the present arrangements, including a server that is communicatively coupled to the decision support system shown in Figure 13 and a remote telemetry unit (hereinafter “RTU”) that is, in turn, communicatively coupled to a sensor and a server.

[0041] Figure 16 shows a schematic of the portion of an infrastructure network management system of Figure 15 including a server that is communicatively coupled to multiple RTUs and to simplify illustration shows a configuration of the server that has stored therein a digital twin model, which estimates sensor values of a fluid condition attribute, as a function of time, inside an infrastructure item that is being monitored by one of the RTUs.

[0042] Figure 17 shows a schematic of a portion of an infrastructure network management system, according to another embodiment of the present arrangements, including one copy of a digital twin model stored on the server and another copy of the digital twin model stored on the RTU.

[0043] Figure 18 shows a schematic of a portion of an infrastructure network management system, according to yet another embodiment of the present arrangements and that uses a server’s digital twin model to generate one or more estimated sensor values of a fluid condition attribute inside the remotely located infrastructure item and facilitate management of that item.

[0044] Figure 19 shows a schematic of a portion of an infrastructure network management system, according to yet another embodiment of the present arrangements and that uses the digital twin models, one copy present at the server and another copy present at the RTU, to determine whether a forecast of environmental or climate conditions used by the digital twin models in generating estimated sensor values of a fluid condition attribute was an outlier and should be maintained, or whether the digital twin models no longer provide a reliable estimate and should be updated, recalibrated or reconstructed.

[0045] Figure 20 is a flowchart describing a method of infrastructure management, according to one embodiment of the present teachings, including redistributing fluid flow between multiple options of fluid flow routes that are available to reduce undesirable stress on infrastructure.

[0046] Figure 21 is a flowchart describing another method of infrastructure management, according to another embodiment and that uses estimated intermediate values obtained by a server operating in conjunction with one or more intermediate sensors that measures fluid condition attributes of fluid flowing in or stored at one location of a fluid flow route that facilitates fluid communication between an initial location and subsequent location.

[0047] Figure 22 is a method of implementing infrastructure management strategies, according to one embodiment of the present invention, including redistributing fluid flow, according to one or more successful infrastructure management strategies, among or between multiple options of fluid flow routes that are available to reduce undesirable stress on infrastructure.

[0048] Figure 23 is a flowchart describing another method of infrastructure management, according to another embodiment of the present teachings, and that uses estimated sensor values for constraint locations, e.g., initial location, locations on one or more fluid flow routes, and subsequent location, to reduce undesirable stress on infrastructure.DETAILED DESCRIPTION

[0049] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present systems, methods, teachings and arrangements. It will be apparent, however, to one skilled in the art that the present systems, methods, teachings and arrangements may be practiced without limitation to some or all these specific details. In other instances, well-known process steps have not been described in detail in order to not unnecessarily obscure the present systems, methods, teachings and arrangements.

[0050] The present teachings provide effective fluid flow control during urban development, shifts in water use patterns, and / or variable weather conditions, withparticular emphasis on climate events (e.g., storm events), by monitoring and adjusting fluid flow to relieve undesirable stress in infrastructure.

[0051] The present teachings offer present arrangements and methods for infrastructure management and for implementing infrastructure management strategies. These present arrangements comprise certain salient components, such as sensors, one or more fluid flow controllers, and one or more flow distributing components. A network of sensors may include an initial sensor disposed at an initial location (e.g., location of a large water reservoir), a subsequent sensor at a subsequent location (e.g., location of a wastewater treatment facility) and one or more intermediate sensors along one or more fluid flow routes that provide fluid communication between the initial location and the subsequent location. Each of these sensors at different locations measure one or more fluid condition attributes chosen from a group comprising fluid flow rate, fluid height, volume, hydraulic capacity, retention time, storage capacity, contaminant concentration, and fluid quality.

[0052] One or more flow controllers of the present systems may receive, in real-time, data from the sensor network and perform several critical functions, such as calculate stress values for different locations (e.g., constraint locations on a route) based on the sensor data, and, preferably, also determine route stress values, for example, by adding stress values for the different locations of interest present along each route, and develop and implement flow redistribution strategies, based on these type of stress values, to relieve undesirable stress on infrastructure. One or more flow controllers may incorporate proportional-integral-derivative control mechanisms for data processing and strategy implementation.

[0053] A “stress value,” as this term is used in the specification, refers to a value obtained by computing a ratio of a fluid condition attribute measurement value at a particular location to a predetermined tolerable threshold attribute value attribute assigned to that location. A fluid condition attribute value maybe a fluid flowrate value through or a fluid storage value at that location and is typically obtained using a sensor disposed at or near that location. The predetermined tolerable threshold attribute value may be set by an engineer using historical sensor data. By way of example, an engineer may examine historical sensor data and evaluate the stresses experienced, duringcertain climate events, at one or more problematic locations present in infrastructure and set an appropriate value for the predetermined tolerable threshold attribute value. According to the present teachings, the measurement of a fluid condition attribute at a particular location inside infrastructure should not exceed the assigned predetermined tolerable threshold attribute value, resulting in a stress value greater than 1. According to the present teachings, a location registering at a stress value of greater than 1 is deemed to be operating in an undesirable mode, i.e., operating in over-capacity mode. Operating infrastructure locations in over-capacity mode is undesirable as it not only leads to infrastructure failure, but also causes sewage or wastewater contamination of clean water bodies, such as rivers, lakes, and reservoirs.

[0054] The present teachings recognize a need to solve this, among other problems encountered during climate events, and propose effectively reducing stresses at one or more constraint locations present in infrastructure by redistributing fluid flow as explained below. According to the present teachings, a location in infrastructure is deemed to be a constraint location, if a measurement or an estimated value of a fluid condition attribute at that location, during a climate event, is capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to the location.

[0055] The present teachings recognize that inside infrastructure, there are different routes extending from an initial location (e.g., location of a large water reservoir) to a subsequent location (e.g., location of a wastewater treatment facility) and that each of these routes may have disposed thereon one or more constraint locations. To this end, the present teachings propose computing a route stress value or an estimated route stress value, which represent a summation of a stress value or an estimated stress value, respectively, of each constraint location present along a route. Redistributing fluid flow, according to the present teachings, using different sets of routes available as options for relieving stress in infrastructure also effectively reduces undesirable stress in routes experiencing high stress values or estimated stress values during a climate event.

[0056] The present teachings recognize that the predetermined tolerable threshold attribute value may vary based on the intensity of the climate event, e.g., storm. For a small storm, the present teachings recommend using a relatively high predeterminedtolerable threshold attribute value, and for a big storm, the present teachings recommend using a relatively low predetermined tolerable threshold attribute value to effectively manage stress inside infrastructure.

[0057] Regardless of the intensity of the climate event, redistributing fluid flow, according to the present teachings, among or between different routes present in infrastructure allows fluid condition attribute values at constraint locations to be maintained at or below their assigned predetermined tolerable threshold values and / or allows stress reduction in highly stressed routes. To this end, the present teachings recognize the importance of identifying the presence of different routes available as options for relieving stress in infrastructure. One or more flow-distributing components of the present systems are, preferably, used to carry out the redistributing fluid flow function and are disposed at the intersections of multiple routes. A flow-distributing component redistributes fluid flow based upon instructions from the flow controllers and include such facilities or components as fluid facilities, pump stations, gates, inflatable dams, weirs, or valves.

[0058] The present systems and teachings offer components or features for infrastructure management and for implementing infrastructure management strategies. The present methods include features like obtaining data and / or estimated values, calculating and / or estimating stress values, developing flow redistributing strategies for relieving stress in infrastructure, and implementing these strategies to relieve stress. To conform to the present teachings, the present methods do not rely upon any particular system or structure. However, implementing the present methods using the present systems represents a preferred embodiment of the present teachings.

[0059] By way of example, an obtaining data functionality of the present methods uses sensors that, preferably, continuously measure fluid condition attributes and transmit sensor measurement data to flow controllers in real-time. Along the lines of using a network of sensors, the estimating values functionality of the present methods, preferably, use a server. The server is communicatively coupled with one or more RTUs that operate in conjunction with these sensors disposed at or near the constraint location. For performing certain local control functions, the RTU maintains a synchronized machine-learning flow model, a digital twin of which is maintained on theserver. Based on certain RTU criteria and during a climate event, the RTU conveys actual sensor measurements that it receives from the sensor, at or near the constraint location, to the server. The server, during the climate event, may estimate values of fluid condition attributes, i.e., sensor measurement, at or near the constraint location. The server, preferably, transmits, in real time, the sensor measurements or these estimated values, depending on what the server deems to be more reliable, to one or more fluidflow controllers.

[0060] As another example, the calculating stress feature of the present teachings uses one or more flow controllers that, based upon sensor measurement data and above-mentioned estimated values, compute stress values and / or estimated stress values for each monitored location in infrastructure and may even compute route stress values and / or estimated route stress values as indicated above.

[0061] As yet another example, based upon the stress values and / or estimated stress values for constraint locations, route stress values and and / or estimated route stress values, predetermined tolerable threshold attribute values used in different types of storms, fluid flow controllers of the present teachings formulate flow redistributing strategies to relieve stress in infrastructure.

[0062] As yet another example, one or more flow-distributing components redistribute fluid flow at an intersection between or among fluid flow routes available as options to receive excessive flow and thereby reduce undesirable stress on the highly stressed routes and / or the highly stressed constraint locations inside infrastructure. By way of example, this feature maintains stress values at acceptable levels inside infrastructure by redistributing fluid flow through the different routes, such that stress levels at the constraint locations are at or below an assigned predetermined tolerable threshold attribute value. In preferred embodiments of the present teachings, fluid condition attribute value at the constraint location with the maximum stress value is modified to be equal to or below the assigned predetermined tolerable threshold attribute value for effective infrastructure management.

[0063] Using these features, the present teachings also offer advanced functionalities and features for effective infrastructure management. By way of example, one such advanced feature is storm event adaption, which is also referred herein to as “adaptiveflow control,” as it allows the present infrastructure management systems to adapt flow control to the changing storm conditions, i.e., in real-time adjust flow redistributing strategies based on the changing storm severity. Specifically, the present system, if required in real time, preferably, changes the predetermined threshold settings as conditions unpredictably evolve.

[0064] By way of example, if an expected small storm unpredictably evolves into a big storm, then the present methods dynamically change the stress threshold setting from a relatively high predetermined tolerable threshold attribute value to a relatively low predetermined tolerable threshold attribute value. Furthermore, if instead of an expected big storm event a small storm is realized, then the present methods dynamically change the stress threshold setting from a relatively low predetermined tolerable threshold attribute value to a relatively high predetermined tolerable threshold attribute value.

[0065] The present systems and methods, using climate event forecasts and digital twin models, offer proactive flow redistributing strategies by estimating future fluid condition attribute values and stress values, allowing for effective proactive measures of infrastructure management.

[0066] The present systems and methods are capable of evaluating the effectiveness of multiple flow redistributing strategies after a climate event, storing successful flow redistributing strategies for future use. This allows for continuous improvement in infrastructure management over time.

[0067] In connection with wastewater treatment facilities that include therewithin high- quality and low-quality treatment schemes, the present systems and methods effectively manage fluid flow, as they do inside infrastructure. But certain embodiments of the present teachings do not redistribute fluid flow inside a wastewater treatment facility directly between high-quality and low-quality treatment schemes.

[0068] The present systems and methods offer a comprehensive approach to realtime, effective infrastructure management, integrating advanced monitoring, predictive modeling, and adaptive control strategies to maintain integrity of the existing infrastructure during variable climate events. In certain embodiments of the present systems and methods, the present teachings prioritize infrastructure stressmanagement and performance over cost optimization, with a focus on maintaining stress levels below critical thresholds across one or more of the constraint locations.

[0069] Figure 1 shows a sewer management facility 10 that includes a sewer system 15 that is coupled to a wastewater treatment facility 25. Sewer system 15 has certain components, i.e., catchment area 12, a storage chamber 14, an outlet 16, a high-quality treatment line 18, and a low-quality treatment line 20. Treatment scheme 25 provides high-quality treatment and low-quality treatment.

[0070] In low-quality treatment, the fluid is partially treated to produce water. Low- quality treatment does not rely upon biological treatment, which may be time consuming. Rather, low-quality treatment implements mechanical and chemical treatment, which allow for high throughput of fluid treatment. In contrast, high-quality treatment provides “full” treatment of water where all contaminants, including bacteria, are reduced below limits established by the Environmental Protection Agency. As such, high-quality treatment incorporates mechanical, chemical and biological treatment of sewage to produce water.

[0071] According to the configuration of Figure 1 , contents inside storage chamber 14 are conveyed through a high-quality treatment line 18 for high-quality treatment that is carried out using a primary chamber 22 and a secondary chamber 24. Typically, primary chamber 22 has a higher flow rate capacity of treatment than secondary chamber 24. In high-quality treatment, contents of storage chamber 14 initially undergo solids removal and are subsequently treated for bacteria and nutrient compositions. Once the flow rate capacity of high-quality treatment reaches its maximum capacity, then through low- quality treatment line 20, contents of storage chamber 14 are conveyed to low-quality treatment chamber 26. Primary chamber 22 in this conventional approach to wastewater treatment is configured to implement mechanical and chemical treatment and secondary chamber is preferably configured to implement contaminant removal.

[0072] Although a low-quality treatment chamber (e.g., chamber 26 of Figure 1 ) produces relatively low quality of treated sewer, it does so at high flow rates. As a result, in the event of a storm, a treatment scheme, that relies on high flow rates of sewer treatment such as those realized when low-quality treatment is enabled, reduces the chances of overflow from an outlet of storage chamber (e.g., outlet 16 of storagechamber 14 of Figure 1 ). Particularly if the storm event is deemed a “big storm event,” then the conventional approach enables low-quality treatment well in advance of the storm’s arrival. For a big storm event, if the low-quality treatment is not enabled, then the conventional approach recognizes that the undesired outcome of “overflow” is realized. Further, if the storm event is deemed a “small storm event,” then the conventional approach deems it unnecessary to expend the energy to enable and keep active low-quality treatment and, from one perspective considers, even more undesirable than that - discharge low-quality fluid into the environment. According to this approach, for a “small storm event,” not enabling low-quality treatment not only avoids expending unnecessary energy, but also prevents the undesired outcome of “overflow.” A big storm event may be more than or equal to 1 inch of rainfall in an hour, and a small storm event may be less than or equal to 0.01 inches of rainfall in an hour.

[0073] Overflow of untreated sewage is the most undesirable outcome and relative to the outcome of sewage overflow, low quality-treatment of sewage is a desirable outcome. Against this backdrop, this conventional approach analyzes the desirability of these outcomes of “overflow of untreated sewage” or “no overflow of untreated sewage” in light of the amount of energy expended to avoid overflow. In certain circumstances in the conventional approach, “overflow of untreated sewage” is an acceptable outcome when the energy enable low quality treatment is not being wasted. As a result, prior to arrival of a storm, a decision whether to enable low-quality treatment is warranted under the conventional approach and this decision may be predicated on the size of the storm.

[0074] Building on these types of outcomes and taking into account their underlying energy requirements, this conventional approach of wastewater treatment enables low quality treatment, or high flow rate treatment, well in advance of a storm’s arrival.Furthermore, in this approach, based on the number of times one or more outcomes are realized, a cost of realizing an outcome for the sewer system is established. By way of example, the following cost function is used:

[0075] Cstorage = Y / (X+Y) (Equation 1 )In Equation 1 , “Y” equals number of times one of the potential outcomes (in initial route 210) is realized and “X” equals number of times another of the potential outcomes initial route 210 step 210) is realized. In this example, one of the potential outcomes (e.g., “nooverflow of untreated sewage”) is different from another of the potential outcomes (e.g., “overflow of untreated sewage”).

[0076] This conventional wastewater treatment approach also calculates, based on the number of the fluid condition attributes in the sewer system, another competing cost function:

[0077] Cst (Equation 2)In Equation 2, “Cst” is the cost of flow inside the sewer system, “Qst(t)” represents a current fluid condition attribute value associated with the treatment scheme located outside the sewer system, “Qmax” represents a maximum fluid condition attribute value associated with the treatment scheme and “e” is a minimum cost value associated with the treatment scheme.

[0078] The present teachings, therefore, recognize that the operation of the fluid flow controller, in the conventional approach, is limited to controlling fluid or sewage flow through sewer system 10 to minimize a difference between the cost of realizing an outcome, Cstorage, for the sewer system and the cost of flow through the sewer system, Cst. In other words, the fluid flow controller of the conventional approach operates in a limited capacity to minimize both the risk of overflow (represented by Cstorage) and the operational costs (represented by Cst) while adapting to changing climate conditions and treatment schemes.

[0079] One or more fluid flow controllers of the present systems and methods, in sharp contrast, accomplish a completely different goal of effectively relieving stress in infrastructure, which is of no concern to conventional approaches to wastewater treatment. In this context, the preferred embodiments of the present systems and methods need not include or be based upon: (1 ) determining a cost function of flow inside the infrastructure; (2) determining a cost function of realizing one or more potential outcomes of the infrastructure during a climate event; (3) minimizing a difference between a cost function of realizing one or more potential outcomes of the infrastructure and a cost function of flow inside the infrastructure; and (4) redistributing fluid flow at an intersection location of a high-quality treatment scheme and a low-quality treatment scheme.

[0080] The present teachings recognize, among other things, that excessive fluid flow, during a climate event, from intermediate streams entering a fluid flow route, which provides fluid communication between an initial location and a subsequent location, undesirably stresses infrastructure. In connection with this realization, Figure 2 shows an infrastructure layout 50 that includes a route 55 (e.g., a relief line, a trunk line and / or an interceptor line), which starts from an initial location 52 (e.g., fluid reservoir, catchment and subcatchment), passes through an intermediate location 54 and extends to a subsequent location 56 (e.g., wastewater treatment facility). Fluid flow from intermediate streams 58 (e.g., storm water drainage systems and smaller sewer lines) is introduced into route 55 prior to and after intermediate location 54.

[0081] According to the present teachings, by way of example, excessive fluid flow from intermediate streams 58, prior to intermediate location 54, may produce an undesirable stress at intermediate location 54 if, during a climate event, for example, the fluid condition attribute value at intermediate location 54 is capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to intermediate location 54. According to the present teachings, similarly, as another example, excessive fluid flow from intermediate streams 58, prior to subsequent location 56, may produce an undesirable stress at subsequent location 56 if, during a climate event, for example, the fluid condition attribute value at subsequent location 56 is capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to subsequent location 56. As yet another example, fluid flow from other intermediate streams entering or entering prior to initial location 52 may produce an undesirable stress at initial location 52 if, during a climate event, for example, the fluid condition attribute value at initial location 52 is capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to initial location 52.

[0082] Under these circumstances, the present teachings deem each of initial location 52, intermediate location 54 and subsequent location 56 as “constraint locations” because fluid condition attribute values at each of these locations in infrastructure, during a climate event, are capable of undesirably reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of these locations. Thus, according to the present teachings, when a location inside infrastructure, registershigh fluid condition attribute values due to excessive flow for any reason and satisfies the condition of - being capable of undesirably reaching or exceeding a predetermined tolerable threshold attribute value assigned to the location - it is deemed a “constraint location.”

[0083] Figures 3-5 show different exemplar configurations of the underlying infrastructure that are effectively managed by the present methods and systems. Not shown in Figures 3-5, to simplify illustration, are the intermediate streams, similar to intermediate streams 58 of Figure 2, that produce excessive flow in various routes inside infrastructure, during a climate event, resulting in undesirable stresses at the constraint locations. The present systems and methods operate on the underlying infrastructure to reduce or eliminate this undesirable stress. Moreover, the present teachings realize that the different sets of routes, presented in each of Figures 3-5, are available as options to receive this excessive fluid flow, using a flow-distributing component or a redistributing feature of the present systems and methods, and redistribute the excessive flow and thereby reduce or eliminate the undesirable stress in infrastructure.

[0084] Figure 3 shows one exemplar configuration of an underlying infrastructure 104, in which the present teachings recognize the presence of three different route options for infrastructure stress relief. In Figure 3, fluid flow starts from an initial location 106, at a fluid reservoir 108, passes through an initial route 110 to an intersection location, upon which a flow-distributing component 116 is disposed. At the intersection location, flowdistributing component 116 is capable of redistributing fluid flow among three route options, i.e., initial route 110, a first route 112 and a second route 114. In this configuration, both first route 112 and second route 114 facilitate fluid communication between initial location 106 and a subsequent location 128. An intermediate location 118, represents a location on first route 112 and another intermediate location 120 represents a location on second route 114. A Combined Sewer Overflow (hereinafter “CSO”) 122 is disposed, after intermediate location 118, on first route 112 and a surge tank 126 is disposed between CSO 122 and subsequent location 128.

[0085] The present teachings recognize that the presence of flow-distributing component 116, at the appropriate intersection location, redistributes fluid flow amonginitial route 110, first route 112 and second route 114 to relieve stress in infrastructure. Moreover, the present teachings also recognize that such redistributing of fluid flow also reduces or eliminates the undesired overflow that may result from CSO 122 and / or surge tank 126 under extreme climate conditions.

[0086] By way of background, CSO 122, is commonly used in traditional infrastructure, as a single pipe that carries both sewage and stormwater runoff. During normal climate conditions, e.g., dry weather and light rain, fluid in first and second routes 112 and 114 are normally transported, i.e., without placing first and second routes 112 and 114 under stress, to a subsequent location 128, e.g., wastewater treatment plant. However, during a climate event, such as heavy rainfall or snowmelt, the fluid volume at intermediate location 118 on first route 112 may exceed the capacity allowed at intermediate location 118. The present teachings recognize that in the absence of flow-distributing component 116 and under these unexpected excessive flow conditions, CSO 122 runs the risk of: (1 ) overflowing directly into nearby water bodies 124 (e.g., rivers, lakes, or coastal waters); (2) discharging untreated or partially treated sewage, contaminating water sources, and (3) posing water pollution concern and health risks. Furthermore, the present teachings also recognize that reducing the undesirable overflow from CSO 122, to achieve compliance with environmental regulations, through infrastructure improvements, green infrastructure, and separate storm water systems may be cost prohibitive.

[0087] Surge tank 126 is commonly incorporated in traditional infrastructure, as a storage provision. It is used when managing rapid changes in flow rates, especially during big storm events, and for providing an additional buffer to prevent sewage overflows. The present teachings recognize that the use of surge tank 126, in the absence of flow-distributing component 116 and when an unexpected big storm is encountered, runs similar risks associated with sewage overflow due to improper sizing and placement within infrastructure.

[0088] According to the present teachings, the presence of flow-distributing component 116, at the appropriate intersection location, redistributes fluid flow among initial route 110, first route 112 and second route 114, and thereby prevents the undesired sewageoverflows that may otherwise, in the absence of flow-distributing component 116, result from CSO 122 and surge tank 126.

[0089] Figure 4 shows one exemplar configuration of an underlying infrastructure 204, in which the present teachings recognize the presence of two different routes available as options for infrastructure stress relief. In Figure 4, fluid flow starts from a fluid reservoir 208, passes through an initial route to an intersection location, upon which a flow-distributing component 216 is disposed. At the intersection location, flowdistributing component 216 is capable of redistributing fluid flow between two route options, i.e., a first route 212 and a second route 214. In this configuration, both first route 212 and second route 214 facilitate fluid communication between fluid reservoir 208 and a subsequent location 128. An intermediate location 218, represents a location on first route 212 and another intermediate location 220 represents a location on second route 214. A Combined Sewer Overflow (hereinafter “CSO”) 222 is disposed, after intermediate location 218, on first route 212 and a surge tank 226 is disposed between CSO 222 and subsequent location 228. In the absence of flow-distributing component 216 and during a climate event, CSO 222 runs the risk of overflowing directly into nearby water bodies 224.

[0090] The present teachings recognize that the presence of flow-distributing component 216, at the appropriate intersection location, redistributes fluid flow between first route 112 and second route 114 to relieve stress in infrastructure. Moreover, the present teachings also recognize that such redistributing of fluid flow also reduces or eliminates the undesired overflow that may result from CSO 222 and / or surge tank 226 under extreme climate conditions.

[0091] Figure 5 shows one exemplar configuration of an underlying infrastructure 204, in which the present teachings recognize the presence of two different routes available as options for infrastructure stress relief. These two route options are different from those discussed in connection with Figure 4. In Figure 5, fluid flow starts from an initial location 306 at a fluid reservoir 308, passes through an initial route 310 to an intersection location, upon which a flow-distributing component 316 is disposed. At the intersection location, flow-distributing component 316 is capable of redistributing fluid flow between an initial route 310 and a first route 312. In this configuration, both initialroute 310 and first route 312 facilitate fluid communication between initial location 306 and a subsequent location 328. An intermediate location 318, represents a location on first route 312. A CSO 322 is disposed, after intermediate location 318, on first route 312 and a surge tank 326 is disposed between CSO 322 and subsequent location 328. In the absence of flow-distributing component 316 and during a climate event, CSO 322 runs the risk of overflowing directly into nearby water bodies 324.

[0092] The present teachings recognize that the presence of flow-distributing component 316, at the appropriate intersection location, redistributes fluid flow between initial route 306 and first route 312 to relieve stress in infrastructure. Moreover, the present teachings also recognize that such redistributing of fluid flow also reduces or eliminates the undesired overflow that may result from CSO 222 and / or surge tank 226 under extreme climate conditions.

[0093] Figures 6-9 show different embodiments of a flow-distributing component, according to one embodiment of the present arrangements, that redistributes flow among or between different route options, as shown in Figures 3-5, to reduce the undesirable stress on infrastructure. By way of example, flow-distributing components of Figures 6-9 may be used in connection with the underlying infrastructure configuration of Figure 3, and redistribute flow among initial route 110, first route 112 and second route 114 shown in Figure 3. As another example, flow-distributing components of Figures 6-9 may be used in connection with the underlying infrastructure configuration of Figure 4, and redistribute flow between first route 212 and second route 214 shown in Figure 4. As yet another example, flow-distributing components of Figures 6-9 may be used in connection with the underlying infrastructure configuration of Figure 5 and redistribute flow between initial route 310 and first route 312 shown in Figure 5.

[0094] Figure 6 shows a flow-distributing component, according to one embodiment of the present arrangements, incorporated, into a dynamic underflow control. By way of example, the dynamic underflow control in Figure 6 is depicted as being used in connection with the underlying infrastructure shown in Figure 5. In the dynamic underflow controller of Figure 6, an intermediate stream 340 (e.g., a trunk line) is fitted with a diverting weir 348 that restricts fluid flow along a fluid path 324 towards receiving water bodies. Intermediate stream 340, through an underflow line 342, is in fluidcommunication with first route 312 (e.g., an interceptor line which may also receive fluid flow from other intermediate streams as shown in Figure 2). An arrow represents direction of fluid flow inside first route 312 towards subsequent location 328. A parallel underflow line 344, providing fluid communication between intermediate stream 340 and first route 312 is fitted with a gate 346. In these embodiments, gate 346 serves as flow distributing component 316 shown in Figure 5.

[0095] During a climate event that produces excessive fluid flow, gate 346 of Figure 6, similar to fluid-distributing component 316 of Figure 5, has routes available as options for redistributing such fluid flow and reducing stress in infrastructure. Using one option route includes adjusting fluid flow through first route 312 and using another option includes adjusting fluid flow such that the fluid flows back inside intermediate stream 340, preferably, towards its location of origination, e.g., a fluid reservoir such as a catchment or a subcatchment.

[0096] The magnitude of flow rate is modified through each route option by adjusting the status of gate 346, i.e., completely opening, partially opening, and closing, and infrastructure stress is relieved accordingly. By way of example, in connection with Figure 5, if gate 346 is disposed at intersection where flow-distributing component 316 is present, then by opening gate 346, during a climate event, to a larger extent allows more water from an overwhelmed fluid reservoir 308 (e.g., overwhelmed subcatchment) to enter first route 312 and thereby provide stress relief to the overwhelmed fluid reservoir 308, and particularly to an undesirably stressed initial location 306, if initial location 306 is deemed a constraint location. As another example, by closing gate 346, during a climate event, to a larger extent allows more water from an overwhelmed first route 312 to flow back through initial route 310 towards fluid reservoir 308, and thereby provide stress relief to the overwhelmed first route 312, and particularly to an undesirably stressed intermediate location 318 on first route 312, if intermediate location 318 is deemed a constraint location.

[0097] As a result, the present systems and methods use dynamic underflow control in the present arrangements to allow management of a Hydraulic Grade Line (“HGL”) in various routes in infrastructure during a climate event that produces undesirable excessive flow.

[0098] Figure 7 shows another flow-distributing component, according to another embodiment of the present arrangements, incorporated, into outfall storage. By way of example, outfall storage of Figure 7 is depicted as being used in connection with the underlying infrastructure shown in Figure 5. In outfall shortage embodiment of the present arrangements, an intermediate stream 340' (e.g., a trunk line) is fitted with one or more diverting weirs 348 that restrict fluid flow along a fluid path 324 towards receiving water bodies. In this figure, an intermediate stream 340' through a throttle line 354 is in fluid communication with a first route 312' that conveys fluid flow towards subsequent location 328. A fluid line 350 fitted with a dewatering pump 350 conveys fluid flow from intermediate stream 340' to first route 312'. In these embodiments, dewatering pump 352 serves as flow distributing component 316 shown in Figure 5.

[0099] During a climate event that produces excessive fluid flow, dewatering pump 352 of Figure 7, similar to fluid-distributing component 316 of Figure 5, has two option routes for redistributing such fluid flow and reducing stress in infrastructure. Using one option route includes adjusting fluid flow through first route 312' and using another option includes adjusting fluid flow through intermediate stream 340', such that the fluid flows back inside intermediate stream 340', preferably, towards its location of origination, a fluid reservoir such as a catchment or a subcatchment.

[0100] The magnitude of flow rate is modified through each option route by adjusting the pumping rate of dewatering pump 352. By way of example, in connection with Figure 5, if dewatering pump 352 is disposed at intersection where flow-distributing component 316 is present, then by either decreasing the pumping rate of or by completely shutting off dewatering pump 352, fluid flow is stored inside intermediate stream 340', which may be thought as being similar to initial route 310 of Figure 5, and thereby avoiding spilling sewage or contaminated fluid into water bodies 324, and providing stress relief to an undesirably stressed upstream intermediate location 318 shown in Figure 5, if intermediate location 318 is deemed a constraint location. As another example, when stress inside first route 312' subsides, then by opening dewatering pump 352 allows the fluid stored inside intermediate stream 340' to flow out through first route 312' to a subsequent location 324, and thereby providing stress relief to intermediate stream 340', if it is filled up to capacity with the stored fluid, andparticularly to an undesirably stressed initial location 310 of Figure 5 on first route 310, if initial location 310 is deemed a constraint location.

[0101] Figure 8 shows yet another flow-distributing component, according to yet another embodiment of the present arrangements, incorporated, into offline storage. By way of example, offline storage of Figure 8 is depicted as being used in connection with the underlying infrastructure shown in Figure 5. In the offline storage embodiment of the present arrangements, an intermediate stream 340" (e.g., a trunk line) conveys fluid through a filling line 358, fitted with a filling gate 360, to a wet weather storage tank 356, which in turn, connects back through a fluid line 350' to intermediate stream 340". Fluid line 350' is fitted with a dewatering pump 352' that pumps fluid from wet weather storage tank 356 to intermediate stream 340" that flows towards subsequent location 328. In these embodiments, dewatering pump 352' serves as flow distributing component 316 shown in Figure 5.

[0102] Wet weather storage tank 356 may be tunnel. Dewatering using dewatering pump 352’ and filling using a tunnel or wet weather storage tank 356 are based on downstream constraints. For example, if offline storage of Figure 8 is depicted as being used in connection with the underlying infrastructure shown in Figure 3, then the above- mentioned filling operation may be carried out when the downstream first route 112 and / or second route 114 shown in Figure 3 are undesirably stressed and / or when the downstream intermediate location 118 on first route 112 and / or an intermediate location 120 on second route 114, shown in Figure 3, are undesirably stressed and are deemed to be constraint locations in infrastructure. When such undesirably stresses subside, then the above-mentioned dewatering operation may be carried out.

[0103] Figure 9 shows yet another flow-distributing component, according to yet another embodiment of the present arrangements, incorporated, into a storm tank. By way of example, storm tank of Figure 9 may be used in connection with the underlying infrastructure shown in Figure 5. In the storm tank embodiment of the present arrangements, an intermediate stream (e.g., a trunk line) conveys fluid through a filling line 358' to a storm tank 356', which in turn, connects to a gate 352" and moves forward through a fluid line 350', preferably, back to the intermediate stream, an interceptor lineor a subsequent location 328 shown in Figure 5. In these embodiments, gate 352" serves as flow distributing component 316 shown in Figure 5.

[0104] Storm tank 356' stores fluid in varying volumes, which fill storm tank 356' to different fluid levels, i.e., a non-usable fluid level 362, flood prevention volume 364 and overflow prevention volume 366. In this embodiment of the present teachings, flood prevention volume 364 stores enough fluid to prevent flood and overflow prevention volume 366 stores enough fluid to prevent overflow within storm tank 356'.

[0105] Figure 10 shows a control scheme 370, according to one embodiment of the present teachings, controlling the filling and emptying operation of storm tank 356' shown in Figure 9. Control scheme 370, in preferred embodiments of the present teachings, operates at a local control level implemented entire in a SCADA system and allows storm tank 356’ to properly operate even if there is a failure in the SCADA system.

[0106] Control scheme 370 of Figure 10 in a dry weather condition, which is denoted by reference numeral 372, keeps gate 352" of Figure 9 in an “open” position. In an overflow prevention condition, which is denoted by reference numeral 374 in Figure 10, Level > Lwet, where “Level” refers to a fluid level present in storm tank 356' shown in Figure 9 and “Lwet” refers to the length of a pipe experiencing increased flow during wet weather conditions, e.g., intermediate stream pipe (e.g., a trunk line), that conveys excess fluid or sewage through a filling line 358' to a storm tank 356'. When Level > Lwet, then control scheme 370 of Figure 10 modulates operation of (e.g., controls an appropriate opening of) gate 352" of Figure 9 to maintain overflow prevention volume 366 in storm tank 356' shown in Figure 9. This operation of control scheme 370 of Figure 10 avoids contamination of water bodies by preventing overflow or spilling of fluid (e.g., sewage) into them. When Level < Lwet, then control scheme 370 of Figure 10 reverts back to and operates according to dry weather conditions and keeps gate 352" of Figure 9 in an “open” position.

[0107] In a flood prevention condition, which is denoted by reference numeral 376 in Figure 10, Level > Lsp, “Lsp” refers to the length of a pipe that is flowing full or operating to full capacity, e.g., intermediate stream pipe (e.g., a trunk line) that conveys excess fluid or sewage through a filling line 358' to a storm tank 356' is operating to fullcapacity. When Level > Lsp, then control scheme 370 of Figure 10 modulates operation of (e.g., controls an appropriate opening of) gate 352" of Figure 9 to maintain flood prevention volume 364 in storm tank 356’ shown in Figure 9. This operation of control scheme 370 of Figure 10 avoids contamination of water bodies by preventing flooding of fluid (e.g., sewage) into them. When Level < Lsp, then control scheme 370 of Figure 10 reverts to and operates according to overflow prevention condition 374 of Figure 10 and keeps gate 352" of Figure 9 appropriately open to maintain flood prevention volume 364 of Figure 9.

[0108] Figure 11 A shows, for a small storm, a graphical representation 386 of stress values in infrastructure (e.g., stress values computed for a constraint location) versus storage levels (e.g., storage levels in CSO 122 of Figure 3). According to this figure, to maintain a desired stress value of 1 (which is a dimensionless quantity), during a small storm, the storage level in CSO 122 of Figure 3 is preferably set to a value of “2,” which is preferably reported in the units of distance (e.g., feet or meters), as a fluid level inside CSO 122 of Figure 3. Furthermore, for the fluid condition attribute of fluid level, the value of “2” is a setting for a relatively high predetermined tolerable threshold attribute value (shown as vertically extending dashed line in Figure 11 A). As a result, when the fluid level inside CSO 122 of Figure 3 exceeds a value of “2,” during a small storm, then the stress value at CSO 122 of Figure 3 is higher than 1 and CSO 122 of Figure 3 requires stress relief through fluid flow redistribution according to the present teachings.

[0109] Figure 11 B shows, for a small storm, a graphical representation 388 of stress values in infrastructure versus fluid flow rate (e.g., bottleneck flow in throttle line 354 of Figure 7 may be restricted due to an undesirably stressed constraint location).According to this figure, to maintain a desired stress value of 1 , during a small storm, the fluid flow rate is preferably set to a value of “4000” reported in the units of flowrate, i.e., in volume per unit time flowing through throttle line 354 of Figure 7. Moreover, for the fluid condition attribute of fluid flow, the value of “4000” is a setting for a relatively high predetermined tolerable threshold attribute value (shown as vertically extending dashed line in Figure 11 B). As a result, when the fluid flow inside throttle line 354 of Figure 7 exceeds a value of “4000,” during a small storm, then the stress value atthrottle line 354 of Figure 7 is higher than 1 and throttle line 354 of Figure 7 requires stress relief through fluid flow redistribution according to the present teachings.

[0110] Figure 12A shows, for a big storm, a graphical representation 390 of stress values in infrastructure versus storage levels (e.g., storage levels in CSO 122 of Figure 3). According to this figure, to maintain a desired stress value of 1 , during a big storm, the storage level in CSO 122 of Figure 3 is preferably set to a value of “1 ,” which is preferably reported in the units of distance (e.g., feet or meters), as a fluid level inside CSO 122 of Figure 3. Furthermore, for the fluid condition attribute of fluid level, the value of “1” is a setting for a relatively low predetermined tolerable threshold attribute value (shown as vertically extending dashed line in Figure 12A). As a result, when the fluid level inside CSO 122 of Figure 3 exceeds a value of “1 ,” during a big storm, then the stress value at CSO 122 of Figure 3 is higher than 1 and CSO 122 of Figure 3 requires stress relief through fluid flow redistribution according to the present teachings.

[0111] Figure 11 B shows, for a big storm, a graphical representation 392 of stress values in infrastructure versus fluid flow rate (e.g., bottleneck flow in throttle line 354 of Figure 7). According to this figure, to maintain a desired stress value of 1 , during a big storm, the fluid flow rate is preferably set to a value of “3000” reported in the units of flowrate, i.e., in volume per unit time flowing through throttle line 354 of Figure 7.Moreover, for the fluid condition attribute of fluid flow, the value of “3000” is a setting for a relatively low predetermined tolerable threshold attribute value (shown as vertically extending dashed line in Figure 12B). As a result, when the fluid flow inside throttle line 354 of Figure 7 exceeds a value of “3000,” during a big storm, then the stress value at throttle line 354 of Figure 7 is higher than 1 and throttle line 354 of Figure 7 requires stress relief through fluid flow redistribution according to the present teachings.

[0112] To simplify illustration and facilitate discussion, in each of Figures 11A, 11 B, 12A, and 12B, a stress value function is shown to have a linear relationship with the values of a fluid condition attribute being monitored. The present teachings, however, that the stress value function may also be linear, so long as the stress value function, f(x), where x refers to the fluid condition attribute value, satisfies these two conditions: (1 ) f(pptav)=1 , where “pptav” refers to a predetermined tolerable threshold attribute value, and f'(x)>0, where f'(x) refers to a first derivative function of f(x). Furthermore, fora small storm, the present teachings recommend setting “pptav,” for constraint locations, to be a relatively high predetermined tolerable threshold attribute value, and for big storm events, the present teachings recommend setting “pptav,” for constraint locations, to be a relatively low predetermined tolerable threshold attribute value.

[0113] Against this backdrop, the present teachings offer adaptive flow control for effective infrastructure management. The present teachings, if required in real time, preferably, dynamically change the predetermined threshold settings as conditions unpredictably evolve. If an expected small storm unpredictably results into a big storm, then the present teachings dynamically change the stress threshold setting from a relatively high predetermined tolerable threshold attribute value to a relatively low predetermined tolerable threshold attribute value. Furthermore, if an expected big storm unpredictably produces a small storm, then the present teachings dynamically change the stress threshold setting from the relatively low predetermined tolerable threshold attribute value to relatively high predetermined tolerable threshold attribute value.

[0114] Figure 13 shows a decision support system 400, according to one embodiment of the present arrangements, for setting predetermined tolerable threshold attribute values for different constraint locations to effectively manage the undesirable stress resulting from storms of different intensities. In certain embodiments, decision support system of the present teachings, obtains a climate event or rainfall forecast 416 through a network 410, e.g., The Internet, and runs multiple scenarios of probable rainfall patterns that are conveyed to a decision support engine 406. Preferably, every time new rainfall or a climate event forecast is available, sensors, such as rain gauges 440 and fluid flowrate and / or fluid level meters, collect sensor measurements. These measurements are sent to a sensor historian database 420, which in turn conveys them through a firewall / data diode to decision support engine 406. In this manner, decision support engine 406 is continuously updated, preferably, every time new a climate event or a new rainfall forecast is available. Furthermore, in those instances when the sensor measurements are not available or for obtaining estimations of sensor values for future instance in time, a digital twin model server 408 (described in detail with respect to Figures 15-19) is, preferably used. Digital twin model server 408 provides server estimated sensor values to decision support engine 406. Based on this data, amongother types of data, an operator 436 sets the various predetermined threshold values described herein (e.g., a predetermined tolerable threshold attribute value, a relatively low predetermined tolerable threshold attribute value, a relatively high predetermined tolerable threshold attribute value) and sends them back to decision support engine 406.

[0115] Based on the settings of these predetermined threshold values, decision support engine 406 formulates flow redistributing strategies that relieve stress in infrastructure. These flow redistributing strategies are conveyed through an information path 432 to digital twin model server 408. After implementing one or more of these flow redistributing strategies during one or more climate events, digital twin model server 408 generates an outcome, e.g., an evaluation, based upon certain key point indicators (e.g., reducing overflow volume, reducing flooding volume, reducing energy consumption and increasing river water quality), of the effectiveness of a particular flow redistributing strategy in relieving stress during a particular climate event. Digital twin model server 408 through another information path 434 sends the outcome back to decision support engine 406. As a result, flow redistributing strategies are constantly refined at decision support engine 406, which has stored therein one or more successful flow redistributing strategies in light of the most recent climate events. In certain embodiments, decision support engine 406 recommends, based on the above- mentioned key point indicators, to operator 436, during a climate event and / or for a future climate event, one or more successful flow redistributing strategies. Preferably, operator 436 implements these strategies using a flow-distributing component 438, which is the same as flow-distributing components 116, 216, 316 shown in Figures 3-5, respectively, gates 346 and 352' shown in Figures 6 and 9, respectively, and dewatering pumps 352 and 352' shown in Figures 7 and 8, respectively.

[0116] Figure 14 shows a control system architecture, according to certain embodiments of the present arrangements, that includes high-level strategy 550, low- level control and local control (collectively denoted by reference numeral 552). High- level strategy 550 implements a network-wide strategy and is described in Figure 13. High-level strategy 550 relies upon a digital twin model server 508, which functions substantially similar to digital twin model 408 shown in Figure 13. Digital twin modelserver 508 communicates with decision support engine 506 through information pathways 532 and 534, which are accordingly substantially similar in function to their counterparts, i.e., decision support engine 406, information pathways 432 and 434, shown in Figure 13. In Figure 14, a sensor historian database 520 and an operator 540 are also substantially similar in function to their counterparts, i.e., sensor historian database 420, operator 436, shown in Figure 13. As shown in Figure 14, sensor historian database 520 provides updated and historic sensor information to enable local control and low-level control 412, and operator 540, reacting to current and future climate events, exercises low-level control using a Programmable Logic Controller (“PLC”) 556 and SCADA historian 554.

[0117] At a local control level, operator 540 using PLC 556 receives measurements of a storage sensor 512 and controls operation of a flow-distributing component 516. Flowdistributing component 516 of Figure 14 is substantially similar in function to its counterpart, i.e., flow-distributing component 438 shown in Figure 13. In low-level control 412, network of sensor 412 (also shown in Figure 13) convey their measurements for storage in SCADA historian 554.

[0118] Present systems and methods for implementing its real time decision support system, may rely upon a synchronized machine-learning model, which is referred to as a digital twin model. In one configuration, one of the digital twin models operates on an RTU and another of the digital twin models operates on a server (e.g., digital twin model 408 of Figure 13 or 508 of Figure 14), which is communicatively coupled to and aggregates data from multiple RTUs distributed within a fluid infrastructure network. In this configuration, at least one RTU is connected to a sensor and the RTUs and the sensors are disposed at monitoring locations (e.g., constraint locations) of fluid infrastructure network that are remote to the server (e.g., digital twin model 408 of Figure 13 or 508 of Figure 14). As a result, the server may be thought of as a central processor that aggregates remotely collected data and digital twin models for management of the fluid network. Representative fluid infrastructure item, according to the present arrangements and present teachings, includes conduit, reservoir, orifice, weir, pump and wastewater treatment plant.

[0119] According to the present teachings, the digital twin model is used to produce estimates of the sensor measurements at an RTU and the server. In one embodiment of the present teachings, the RTU compares an actual sensor measurement with an RTU estimated range of values obtained from the digital twin model (operating at the RTU). If the actual sensor measurement and the estimate from the digital twin model are within a tolerable range, then the actual sensor measurement is not conveyed from the RTU (where it resides) to the server. In this circumstance, the server (e.g., digital twin model 408 of Figure 13 or 508 of Figure 14) relies upon the digital twin model stored thereon and assumes that at least one of server estimated range of value obtained from the digital twin model (at the server) to be the actual sensor measurement.

[0120] If, however, the actual sensor measurement and the RTU estimated range of values from the RTU’s digital twin model are not within a tolerable range, then the actual sensor measurement is conveyed from the RTU to the server (e.g., digital twin model 408 of Figure 13 or 508 of Figure 14). At the server, information regarding a realized environmental condition (e.g., amount of precipitation) is received and, used in conjunction with the actual sensor measurements received from the RTU, to obtain a server estimated range of values for the sensor measurement from the server’s digital twin model. If the difference between the actual sensor measurement and the server estimate range of value from the server’s digital twin model, is outside a tolerable range, then the realized environmental condition is deemed an outlier. In this situation, the present teachings consider the digital twin models, at the RTU and at the server, to be synchronized and therefore, retains the digital twin model at the server and reports the actual sensor measurement, received from the RTU to one or more of fluid flow controllers of the present systems.

[0121] If, however, the difference between the actual sensor measurement and the server estimate range of values for the sensor measurement, obtained from the digital twin model at the server, is within the tolerable range, then the digital twin models, at the RTU and at the server, are considered by the present teachings not to be synchronized. Accordingly, the digital twin model at the server is updated or reconstructed so that it is synchronized with the digital twin model present at the RTU.

[0122] Figure 15 shows a fluid infrastructure network management system 1100, according to one embodiment of the present arrangements and that is designed to monitor a fluid infrastructure. Fluid infrastructure monitoring system 1100 includes an RTU 1102 and a server 1104 that are communicatively coupled through a communication network 1110 (e.g., the Internet or a satellite). Further, RTU 1102 is powered by a battery 1132 to carry out a wide variety of functions.

[0123] RTU 1102 includes an RTU microprocessor 1128 that is communicatively coupled to an RTU communication module 1134, which is in turn communicatively coupled to network 1110. Inside RTU 1102, an RTU memory module is bi-directionally coupled to RTU microprocessor 1128. A sensor module 1136 receives data from a sensor 1112 that is configured to measure a fluid condition attribute of a remote fluid infrastructure item, which is located remotely with respect to server 1104.

[0124] According to Figure 15, a sensor measurement taken by sensor 1112 is conveyed from sensor module 1136, through a communicative coupling, to RTU microprocessor 1128. Either after processing or without processing, a computed value relying on the sensor measurement or the sensor measurement itself is conveyed from RTU microprocessor 1128 to RTU communication module 1134.

[0125] In an alternate embodiment of the present fluid infrastructure monitoring system, sensor module 1136 is directly coupled to RTU communication module 1134 and a sensor measurement, taken at sensor 1112, does not have to go through RTU microprocessor 1128 to arrive at RTU communication module 1134. In this alternate arrangement, the sensor measurement, taken at sensor 1112, is conveyed from sensor module 1136 directly to RTU communication module 1134. Regardless of whether RTU microprocessor 1128 is involved in communicating a sensor measurement, taken at sensor 1112, the sensor measurement is conveyed from RTU communication module 1134 through a network to server 1104.

[0126] Server 1104, which is substantially similar to digital twin model server 408 of Figure 13 or 508 of Figure 14, includes a server communications module 1138 that is bidirectionally coupled to a server processor 1140, which is in turn bi-directionally coupled to a database 1142. Server communications module 1138, like RTU communication module 1134, is communicatively coupled to network 1110. In connection with a sensormeasurement, taken at sensor 1112, server communications module 1138 receives the sensor measurement from network 1110 and forwards it to server processor 1140 that uses it in a comparison, for example, explained below.

[0127] Although Figure 15 shows that server 1104 is communicatively coupled, through network 1110, to a single RTU 1102, the present arrangements are not so limited. To this end, Figure 16 shows a fluid infrastructure network management system 1200, according to another embodiment of the present arrangements and that includes a server 1204 communicatively coupled, through a network 1210, to multiple RTUs, e.g., an RTU 1202 and other RTUs 1214A, 1214B and 1214C. In this embodiment, RTU 1202, network 1210 and server 1204, are substantially similar to their counterparts, i.e., RTU 1102, network 1110 and server 1104, respectively, shown in Figure 15.

[0128] Figure 16 shows that server 1204 of fluid infrastructure network management system 1200 has operating therein a machine learning engine 1206 and an RTU digital twin model 1208. One or more sensor measurements taken from sensor 1212 are conveyed from RTU 1202, through network 1210, to server 1204. A sensor measurement is not the only information that is so conveyed. Sensor parameter information related to sensor 1212 of Figure 16, which is substantially similar to sensor 1112 of Figure 15, is conveyed from RTU 1202, through network 1210 (e.g., the Internet or a satellite), to server 1204. Similarly, other sensor measurements, taken using one or more different sensors (i.e., different from sensor 1212) are conveyed from one or more RTUs (e.g., RTU 1214A, RTU 1214B and RTU 1214C, if the fluid infrastructure items associated with each of these RTUs provide an input or input stream into the RTU 1202) associated with one or more of these different sensors, through network 1210, to server 1204.

[0129] In one embodiment of the present arrangements, inside server 1204, machine learning engine 1206 uses sensor parameter information of the fluid infrastructure network, sensor measurements of inputs into and outputs from the fluid infrastructure item of interest, i.e., fluid infrastructure item or a constraint location for which the digital twin model is being constructed, and a probability distribution function of environmental information surrounding the sensor (e.g., sensor 1212 of Figure 16) to construct a digital twin model of RTU 1202. A digital twin model, according to preferred embodiments ofthe present teachings, is a stochastic predictive model that forecasts the measurements of one or more of the sensors in the fluid infrastructure network.

[0130] Representative sensor measurements of fluid condition attributes, in connection with a fluid inside a fluid infrastructure item or at a constraint location, include flowrate data, flow level data, hydrostatic pressure data, flow velocity data, concentration data for one or more chemical species of interest, pH, turbidity, total suspended solids, residual chlorine, total chlorine, total organic carbon, dissolved oxygen, ammonia, nitrates, and phosphorous. Fluid condition attribute values obtained using a sensor are conveyed using an associated RTU therewith (e.g., RTU 1214A, RTU 1214B and RTU 1214C if the fluid infrastructure items associated with each of these RTUs provide an input or input stream into, or an output or an output stream exiting RTU 1202), through network 1210, to server 1204.

[0131] In connection with inputs into a fluid infrastructure item of interest (e.g., infrastructure item which has fluid condition attributes measured by sensor 1212), the input information used to construct digital twin model 1208 includes at least one information chosen from a group comprising precipitation information surrounding the sensor (e.g., sensor 1212 measurements which are estimated by digital twin model 1208) or a constraint location, fluid level of one or more different inputs into a fluid infrastructure item or a constraint location and flow rate of one or more different the inputs into a fluid infrastructure item or a constraint location. By way of example, if RTU 1214A is associated with a conduit, which serves as a fluid infrastructure item and conveys fluid from a storage tank, another fluid infrastructure item monitored by RTU 1214B, to RTU 1202, then a fluid flowrate sensor measurement of the conduit is conveyed from RTU 1214A, through network 1210, to server 1204 and / or a fluid level sensor measurement of the storage tank is conveyed from RTU 1214B, through network 1210, to server 1204. Further, these sensor measurements of the inputs into RTU 1202 are conveyed through a network to a server for construction of digital twin model 1208, one of which also ultimately resides in RTU 1202.

[0132] As another example, server 1204 receives precipitation data 1216 from National Weather Service that forecasts the amount and time of precipitation at an area surrounding the location of a remote sensor (e.g., sensor 1212) for the construction,using machine learning engine 1206, of a digital twin model (e.g., digital twin model 1208) of an RTU (e.g., RTU 1202). In this manner, digital twin models of each RTU (e.g., RTU 1202, RTUs 1214A, 1214B, or 1214C) are constructed and preferably stored inside a server (e.g., server processor 1140 of Figure 15).

[0133] Similarly, with respect to outputs exiting fluid infrastructure item of interest (e.g., infrastructure item which has fluid condition attributes measured by sensor 1212), the output information used to construct digital twin model 1208 includes at least one information chosen from a group comprising evaporation information surrounding the sensor (e.g., sensor 1212 measurements of which are estimated by digital twin model 1208), fluid level of one or more different outputs exiting a fluid infrastructure item and flow rate of one or more different outputs exiting a fluid infrastructure item. Fluid flowrate and / or fluid level measurements of outputs or output streams exiting fluid infrastructure item of interest (being monitored by RTU 1202) are conveyed from their respective RTUs, through network, to the server. Such sensor measurements of the outputs exiting RTU 1202 are used in the construction of digital twin model 1208.

[0134] Examples of sensor parameters include location of the sensor, (e.g., sensor 1212 that may be located at a constraint location), type of sensor, critical high / low transmission rates of sensor and / or of RTU (e.g., RTU 1202, RTUs 1214A, 1214B, or 1214C), battery level of sensor. Some or all these parameters are obtained from a sensor, an RTU or are input at a server.

[0135] In one embodiment of the present teachings, the digital twin model (e.g., digital twin model 1208 of Figure 16) is initially created using a microprocessor (e.g., microprocessor 128 of Figure 15) at an RTU (e.g., RTU 1102 of Figure 15) using the information discussed above and then a copy of that digital twin model is conveyed to the server (e.g., server 1204 of Figure 16). However, a server may enjoy superior data processing capabilities over an RTU, and therefore in preferred embodiments of the present teachings, digital twin model 1208 is initially constructed inside server 1204 and is then a copy of the digital twin model is conveyed through network 1210 to RTU 1202 so that a copy of digital twin model 1208 resides at server 1204 and at RTU 1202. Server 1204 of Figure 16 is, preferably, substantially similar to digital twin model server 408 of Figure 13 or 508 of Figure 14.

[0136] In this context, Figure 17 shows a fluid infrastructure network management system 1300, according to preferred embodiments of the present arrangements and teachings, in which an RTU 1302 communicatively coupled, through network 1310, to a server 1304, which is also communicatively coupled to multiple RTUs, i.e., RTU 1314A, RTU 1314B and RTU 1314C. Further, server 1304 has residing therein a machine learning engine 1306 and digital twin model 1308 that is used for predicting or forecasting the measurements of a sensor (e.g., sensor 1212 of Figure 16) that is monitored by RTU 1302. In this configuration, RTU 1302, network 1310, server 1304, RTU 1314A, RTU 1314B and RTU 1314C, machine learning engine 1306 and digital twin model 1308 are substantially similar to their counterparts, i.e., RTU 1202, network 1210, server 1204, RTU 1214A, RTU 1214B and RTU 1214C, machine learning engine 1206 and digital twin model 1208, shown in Figure 16. Further, in this configuration, a copy of the digital twin model is, preferably, conveyed from server 1304, through network 1310, to RTU 1302. As a result, there are two copies of a digital twin model, one at server 1304 and that is denoted by reference numeral “1308,” and another at RTU 1302 and that is denoted by reference numeral “1318.”

[0137] The present teachings recognize that in this manner, digital twin models for other infrastructure items at other constraint locations, in the fluid infrastructure network, that are monitored by other RTUs, e.g., RTU 1314A, RTU 1314B and RTU 1314C, are created either, preferably, in server 1304 or in RTU 1302 and then a copy of the digital twin model is conveyed to the other, i.e., either, preferably, to RTU 1302 or server 1304. Regardless of the approach of where an initial digital twin model is created, a server, e.g., server 1304, has stored thereon a copy of a digital twin model of a digital twin model stored inside each of the RTUs that monitor different fluid infrastructure items disposed at or near different constraint locations inside infrastructure. More importantly, the present teachings recognize that a server, preferably, incorporates an infrastructure connection between RTUs (e.g., RTU 1314B monitors a tank, which is located downstream from RTU 1314Athat monitors a conduit that is connected to a fluid infrastructure item that is monitored by RTU 1302), to automatically determine - “a system-wide digital twin model.” To this end, the present teachings recognize also that such a “system wide digital twin model” may allow a few scheduled transmissions ofactual sensor measurements from one or more RTUs to the server and gain a more precise estimate of the sensor measurements being monitored by one or more of the RTUs, without dramatically increasing the energy requirements associated with transmissions of sensor measurements from the RTU to the server. It is not necessary to create a “system wide digital twin model,” and the present teachings recognize that by simply constructing, in the server, different digital twin models, a copy of each also being stored on the RTU, the present arrangements offer the advantages of RTUs, without relying on the monitoring activities of the RTUs.

[0138] Figure 18 shows a fluid infrastructure network management system 1400, according to a preferred embodiment of the present arrangements. As explained below, management system 1400 relies on one or more estimated range of values of fluid condition attribute inside a fluid infrastructure item by a server as being or being an estimate of the sensor measurements of a fluid condition attribute inside a fluid infrastructure item. In this embodiment of the present teachings, management system 1400, preferably, does not receive a sensor measurement from an RTU that is monitoring and periodically receiving the sensor measurements of a fluid condition attribute inside the fluid infrastructure item.

[0139] In the embodiment shown in Figure 18, an RTU 1402, preferably, occasionally receives, through network 1410, a forecast of precipitation data 1416 (e.g., time and amount of precipitation, which may be in the form a probability distribution function). Using the forecast of precipitation data, an RTU digital twin model 1418 instructs, preferably, a machine learning engine 1420 (located at the RTU) to generate a probability distribution function estimating a fluid condition attribute that may be measured, at a future instance in time or at a future period, by a sensor. As another input, RTU 1402 also receives, at a sensor module 1422, a sensor measurement from a sensor 1412, measuring a fluid condition attribute inside a fluid infrastructure item. RTU 1402, therefore, is in good position to compare the sensor measurement with one or more of the RTU’s estimated fluid condition attributed values. In preferred embodiments of the present teachings, RTU 1402 electronically compares, a graphical representation of which comparison is denoted by reference numeral “1424,” the sensor measurement with a probability distribution function of the estimated fluid condition attribute values.

[0140] If the sensor measurement falls within a confidence interval of one or more RTU estimated range of values (e.g., that ranges in value from about ± 10% of the mean of the probability distribution function to about ± 15% of the mean of the probability distribution function), then the present teachings recognize that, as an energy savings measure, an RTU need not convey the actual sensor measurement to the server.

[0141] Server 1404 also receives, through network 1410, a forecast of precipitation data 1416 (e.g., time and amount of precipitation which may be in the form a probability distribution function). Server 1404 uses a server’s digital twin model 1408 to use precipitation data 1416 and generate a probability distribution function, estimating fluid condition attribute values for an infrastructure item. In preferred embodiments of the present arrangements, digital twin model 1408 instructs a machine learning engine 1406 to use precipitation data 1416 and generate the probability distribution function that estimates fluid condition attribute values. Regardless of the way in which the fluid condition attribute sensor measurement is estimated, server 1404 assumes the sensor measurement to be a mean value of the probability distribution function estimating fluid condition attribute values and reports, at a server’s user interface, the mean value of the server’s probability distribution function as being the sensor measurement or being an estimate of the sensor measurement.

[0142] Such reporting may be periodic, e.g., every 5 minutes, and need not be carried out after the lapse of future instance in time, which forms the basis of the estimate, e.g., the probability distribution function, of the sensor measurement. In one preferred embodiment of the present teachings, after a lapse of future instance in time or after a lapse of future period of time and if server 1404 does not receive from RTU 1402 a sensor measurement, then server reports to a user the mean value of the server’s probability distribution function as being the sensor measurement or being a reliable estimate of the sensor measurement.

[0143] Further, even if the actual sensor measurement falls within a confidence interval, RTU 1402 may convey, through network 1410, the actual sensor measurement to server 1404. Under such conditions and for conserving energy, RTU 1402 may so convey relatively infrequently, e.g., once a day or once a week, the actual sensor measurements. In certain embodiments of the present teachings, when server 1408does not receive, at a predefined time, a sensor measurement from RTU 1402, then at or after the predefined time, server 1408 relies upon precipitation data to calculate server estimated range of values, e.g., relies upon a probability distribution function, and reports a mean value of these estimated fluid condition attribute values as being the sensor measurement or being a reliable estimate of the sensor measurement.

[0144] The present teachings also recognize the importance of a possibility that the sensor measurement falls outside the confidence interval of the RTU’s one or more estimated fluid condition attribute values (e.g., outside of the ranges in value from about ± 10% of the mean of the probability distribution function to about ± 15% of the mean of the probability distribution function), then the present teachings recognize that an additional condition must be tested, i.e., whether the actual amount of precipitation realized is an outlier or within the expected amount of precipitation (as discerned from precipitation data 516).

[0145] In the embodiment shown in Figure 19, a fluid network management system 1500 includes an RTU 1502 that is communicatively coupled, through a network 1510, to a server 1504. Further, in Figure 19, RTU 1502, server 1504, server machine learning engine 1506, server digital twin model 1508, network 1510, sensor 1512, RTU digital twin model 1518, RTU machine learning engine 1520, sensor module 1522, a graphical representation 1524 of sensor data relative to RTU’s estimated sensor data and a graphical representation 1526 of sensor data relative to the server’s estimated sensor data are substantially similar to their counterparts shown in Figure 18, i.e., RTU 1402, server 1404, server machine learning engine 1406, server digital twin model 1408, network 1410, sensor 1412, RTU digital twin model 1418, RTU machine learning engine 1420, sensor module 1422 and a graphical representation 424 of sensor data relative to RTU’s estimated sensor data and a graphical representation 426 of sensor data relative to the server’s estimated sensor data.

[0146] Precipitation data 1516, e.g., forecasts of environmental conditions in areas surrounding one or more sensors such as sensor 1512, is conveyed, preferably through network 1510, to both RTU 1502 and server 1504. In this configuration, RTU 1502, using machine learning engine 1520 and forecasts of environmental conditions obtainedfrom precipitation data 1516, determines RTU’s new estimated fluid condition attribute values inside a fluid infrastructure item for an instance in time or for a period of time.

[0147] If the absolute value of a difference between the sensor measurement obtained from sensor 1512 and sensor module 1522 and the RTU 1502’s new estimated fluid condition attribute values is greater than a predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside the predefined confidence interval of the RTU 1502’s multiple estimated fluid condition attribute values, then the underlying sensor measurement used for computing the estimate is conveyed from RTU 1502, through network 1510, to server 1504. At server 1502, precipitation data 1516, e.g., the actual amount of precipitation realized around areas surrounding one or more sensors, such as sensor 1512, is used to compute one or more server 1504’s new estimated fluid condition attribute values (e.g., see curve in graphical representation 1526). This estimate is of a fluid condition attribute, for an instance in time or for a period of time, inside a fluid infrastructure item being monitored by sensor 1512. Server 1504 compares, as shown in graphical representation 1526, the sensor measurement taken from sensor 1512 with one or more server 1504’s new estimated fluid condition attribute values (e.g., a probability distribution function that includes multiple estimated values).

[0148] If the absolute value of a difference between the sensor measurement and one of the server’s new estimated fluid condition attribute values is equal to or greater than a check predefined threshold tolerance value, or if the sensor measurement, for an instance in time or for a period of time, falls outside the check predefined confidence interval of multiple server’s new estimated fluid condition attribute values, then the digital twin model 1508 is maintained at server 1504. In this scenario, the present teachings recognize that the actual precipitation realized in the area surrounding sensor 1512 is an outlier relative to the forecasted amount of precipitation in that area. As a result, the present teachings do not deem digital twin model to be an inaccurate at estimating the fluid condition attribute inside a remotely located fluid infrastructure item, rather understand that the forecast did not accurately predict the amount of precipitation. Furthermore, the server conveys the actual sensor measurement to one or more of the flow controllers of the present systems.

[0149] If, however, the absolute value of the difference between the sensor measurement and one of the server’s new estimated fluid condition attribute values is equal to or less than the check predefined threshold tolerance value, or if the sensor measurement, for an instance in time or for a period of time, falls within the check predefined confidence interval of multiple server’s new estimated fluid condition attribute values, then digital twin model 1508 is updated, recalibrated or reconstructed at server 1504. A copy of this updated, recalibrated or reconstructed digital model is conveyed to RTU 1502 so that the “twin” nature of the digital model is reestablished. The digit twin model is updated, recalibrated or reconstructed because the present teachings recognize that the previous digital twin model’s estimated fluid condition attribute values are unreliable, or otherwise unacceptable. As a result, the present teachings propose updating, recalibrating, or reconstructing, as may be needed, so that the new digital twin model’s estimated fluid condition attribute values are reliable and acceptable.

[0150] The present teachings recognize that for predictive modelling, e.g., infrastructure management for future instances in time, and / or current instances in time where sensor measurement values are not available, estimated values of sensor measurements may be relied upon to generate estimated stress values or highest stress route values discussed above. Accordingly, the present teachings offer real-time infrastructure management systems that rely upon estimated sensor values for reducing stress inside infrastructure. One such exemplar infrastructure management system includes: (1 ) an initial sensor designed to be disposed at or near an initial location for measuring fluid condition attribute at the initial location and producing initial values (e.g., sensors 412 shown in Figures 13 and 14 or sensor shown in Figure 14 disposed at initial location 306 shown in Figure 5); (2) a subsequent sensor designed to be disposed at or near a subsequent location for measuring fluid condition attribute at the subsequent location and producing subsequent values (e.g., sensors 412 shown in Figures 13 and 14 or sensor shown in Figure 14 disposed at subsequent location 328 shown in Figure 5); and (3) one or more intermediate sensors, at least one of which is designed to be disposed on one location of a first route for measuring a fluid condition attribute at one location of the first route and producing intermediate values (e.g.,sensors 412 shown in Figures 13 and 14 or sensor shown in Figure 14 disposed at intermediate location 318 of first route 312 shown in Figure 5).

[0151] The subsequent sensor is disposed downstream from the initial sensor because the subsequent location is downstream from the initial location inside the underlying infrastructure. Furthermore, first route 312 facilitates fluid communication between initial location 306 and subsequent location 328. Moreover, the present teachings recognize that the fluid condition attribute at the one location of the first route may exceed a predetermined tolerable threshold attribute value assigned to that location due to excessive fluid flow from one or more intermediate streams entering the first route prior to that location. In sharp contrast, conventional infrastructure management systems simply do not recognize the need for and / or offer solutions for relieving stress inside infrastructure caused by excessive flow from such intermediate streams.

[0152] Certain preferred embodiments of the present infrastructure management systems include one or more intermediate RTUs (e.g., RTU 1302 and multiple RTUs 1314A, 1314B, and 1314C shown in Figure 17). Each of the RTUs is communicatively coupled to at least one of the intermediate sensors and has stored therein one flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at one location of the first route, as a function of time (e.g., RTUs 1402 is communicatively coupled to one or more sensors 1412 that substantially similar to sensors 412 shown in Figures 13 and 14 or sensor shown in Figure 14 disposed at intermediate location 318 of first route 312 shown in Figure 5). One or more of the intermediate RTUs are designed to produce, for a future climate event such as a storm, at least one RTU estimated intermediate value based upon a climate event forecast and the intermediate values, (e.g., graphical representations 1424 at RTU 1402 or 1524 at RTU 1502 shown in Figures 18 and 19, respectively, convey, under certain conditions discussed above, a probability distribution function estimating fluid condition attribute values inside a fluid infrastructure item that in one arrangement is disposed at intermediate location 318 of first route 312 shown in Figure 5).

[0153] A server of the present arrangements is designed to be communicatively coupled to one or more of the intermediate RTUs and has stored therein a digital twin of the one flow model (e g., server 1404 has RTU1 digital twin model 1408 or server 1504has RTU1 digital twin model 1408 as shown in Figures 18 and 19, respectively). The digital twin of the one flow model is substantially similar to the one flow model stored on one of the intermediate RTUs. The server is designed to estimate, based upon the climate event forecast and the intermediate values, the fluid condition attribute values at the one location of the first route and provide at least one server estimated range of intermediate values for the climate event, (e.g., graphical representations 1426 at server 1404 or graphical representation 1526 at server 1504 show a probability distribution function estimating fluid condition attribute values inside the fluid infrastructure item).

[0154] One or more flow controllers of the present arrangements are designed to be communicatively coupled for receiving, in real-time, initial values from the initial sensor, subsequent values from the subsequent sensor, and at least one of the server estimated range of intermediate values or one or more intermediate values from the server (e.g., decision support engine 406 receives sensor values of sensors 412 disposed on intermediate location 318 shown in Figure 5 and estimated values from digital twin model server 408 shown in Figure 13). Based upon the initial value, the subsequent value, at least one of the server estimated intermediate range of values or one or more intermediate values, one of the flow controllers is programmed to determine, in real-time, a stress value for each of the initial location and the subsequent location, and a stress value or an estimated stress value for one location of the first route, respectively.

[0155] One or more flow-distributing components of the present arrangements are, preferably, designed to be disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with the initial location (e.g., flow-distributing component 438 shown in Figure 13 or flowdistributing component 516 shown in Figure 14 are substantially similar to flowdistributing component 316 shown in Figure 5). As a result, fluid flow exiting the initial location flows through the initial route and into one or more of the flow-distributing components. In certain configurations of the underlying infrastructure, a fluid flow intersection represents an intersection of the initial route and the first route, (e.g., flowdistributing component 316 shown in Figure 5 is disposed on an intersection location that intersects initial route 310 and first route 312). In preferred embodiments of thepresent systems that manage these infrastructure configurations, each of the flowdistributing components receive from one or more of the flow controllers, during the storm event and in real time, one or more flow redistributing strategies that are based upon the stress value at each of the initial location and the subsequent location, and the stress value or the estimated stress value at the one location of the first route (e.g., flow distributing component 438 receives strategies from decision support engine 406 shown in Figure 13 or flow distributing component 516 receives strategies from decision support engine 506 shown in Figure 14, and each of flow distributing components 438 or 516 are substantially similar to flow distributing component 316 shown in Figure 5).

[0156] Certain of these flow redistributing strategies effectively modify the stress value and / or the estimated stress value of at least one of the constraint locations in infrastructure and / or modify a route stress value and / or an estimated route stress value in infrastructure. For example, the stress value or an estimated stress value of a constraint location is reduced such that the fluid condition attribute value of at least one of the constraint locations is equal to or below a predetermined tolerable threshold attribute value assigned to that constraint location. Accordingly, at least one of the flowdistributing components, in one of the underlying infrastructure configurations, is designed to redistribute fluid flow at the fluid flow intersection location between the initial route and the first route and according to one of the flow redistributing strategies to reduce the stress value and / or the estimated stress value of at least one of the constraint locations, (e.g., flow distributing component 316 shown in Figure 5 redistributes fluid flow between initial route 310 and first route 312 to reduce stress in at least one of constraint locations, which include initial location 306, intermediate location 318 of first route 312 and subsequent location 328 shown in Figure 5). According to other flow redistributing strategies, at least one of the flow-distributing components redistribute fluid flow at the fluid flow intersection location between the initial route and the first route to reduce the stress value or estimates stress value of the initial route, if the initial route is experiencing undesirable levels of stress or reduce the stress value or estimates stress value of the first route, if the first route is experiencing undesirable levels of stress.

[0157] By way of example, in the underlying infrastructure configuration where a fluid flow intersection represents an intersection of the initial route and the first route as shown in Figure 5, the constraint location may be one location inside infrastructure chosen from a group comprising the initial location, one location of the first route, and the subsequent location. In this underlying infrastructure configuration, each of the initial location, one location of the first route and the subsequent location are deemed to be constraint locations because measurement of fluid condition attribute at any of these locations, during the climate event, is capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of these locations.

[0158] In this exemplar infrastructure configuration of the initial route and the first route as shown in Figure 5, one or more of the flow controllers of the present systems are, preferably, programmed to implement the following instructions: (1 ) determining a stress value for the initial route and an estimated stress value for the first route by (i) adding a stress value for each of the constraint locations present along the initial route to produce an initial route stress value, and (ii) adding a stress value or an estimated stress value for each of the constraint locations present along the first route to produce an estimated first route stress value; and (2) identifying which one of the initial route stress value and the estimated first route stress value has highest magnitude to generate a highest stress route value; and (3) redistributing, using one or more of the flow redistributing strategies, fluid flow in at least one of the fluid flow intersections, between the first route and the initial route to effectively reduce magnitude of the highest stress route value.

[0159] The estimated first route stress value, preferably, represents a sum of at least the stress value for the subsequent location and the estimated stress value at the one location of the first route and the initial route stress value is represented by the stress value of the initial location, if no other constraint locations are present on the initial route.

[0160] In certain configurations of the underlying infrastructure, as shown in Figure 3, three routes, e.g., an initial route, a first route and a second route, are available as options for relieving stress inside infrastructure (hereinafter referred to as “the infrastructure’s three-routes options”). In certain embodiments of the present systems that are designed to manage such infrastructure configurations, at least one of theintermediate sensors is designed to be disposed on one location on a second route for measuring fluid condition attribute at the one location of the second route and produce one or more additional intermediate values, (e.g., sensors 412 shown in Figures 13 or sensor 412 or 512 shown in Figure 14 disposed at intermediate location 320 of second route 314 shown in Figure 3). The second route is different from the first route, but nevertheless facilitates fluid communication between the initial location and the subsequent location.

[0161] The present infrastructure management systems allow using multiple estimated intermediate sensor measurement values for multiple intermediate sensors to generate estimated stress values or highest stress route values. In one exemplar implementation of the present teachings, multiple estimated sensor measurement values, for multiple intermediate sensors disposed on the same and / or different routes, are used. To this end, certain preferred embodiments of the present infrastructure management systems also include using multiple intermediate RTUs in connection with multiple intermediate sensors disposed on different routes. By way of example, at least two of the intermediate RTUs are communicatively coupled to two or more of the intermediate sensors, at least one of which is disposed on one location of a second route that is different from the first route. As explained above, an intermediate sensor, disposed on one location on a second route, measures fluid condition attribute at the one location of the second route to produce one or more additional intermediate values, i.e., in addition to the intermediate values produced by the intermediate sensor disposed on one location of the first route.

[0162] In one embodiment, at least one of the multiple intermediate RTUs of the present systems has stored therein another flow model, which is a synchronized machine-learning model designed to estimate the fluid condition attribute, as a function of time, at the one location of the second route. In connection with one or more of the intermediate sensors disposed on the second route, one or more of the intermediate RTUs produce at least one additional RTU estimated range of intermediate values based upon the climate event forecast and one or more of the additional intermediate values.

[0163] The server, in these preferred embodiments, is designed to communicatively couple with multiple of the intermediate RTUs and has stored therein a digital twin of another flow model. The server’s digital twin of another flow model is substantially similar to another flow model stored on one of the intermediate RTUs monitoring the one location of the second route. In these present arrangements, the server produces at least one additional server estimated range of intermediate values based upon a climate event forecast and one or more of the additional intermediate values. As a result, in these preferred embodiments, one or more of the flow controllers are communicatively coupled to receive, in real-time, at least one of the additional server estimated intermediate fluid condition attribute value. If, however, the (actual) additional intermediate values, that did not fall within the additional RTU estimated range of intermediate values, are present on the server, then those additional intermediate values are conveyed to one or more of fluid flow controllers of the present system.

[0164] Furthermore, based upon the initial value, the subsequent value, at least one of the server estimated intermediate value or the intermediate values, and at least one of the additional server estimated intermediate value or the additional intermediate values, one of the flow controllers is, preferably, programmed to determine the stress value for each of the initial location and the subsequent location, and the estimated stress value at the one location of the first route and an additional estimated stress value at the one location of the second route, respectively. Problems arising from the undesirable stress values or estimated stress values may be relieved by one or more of the flowdistributing components, which, in these preferred embodiments, are disposed on the fluid flow intersection of the initial location, the first route and the second route.

[0165] Based upon the stress value for each of the initial location and the subsequent location, and the estimated stress value at the one location of the first route and the additional estimated stress value at the one location of the second route, at least one of the flow-distributing components of the present systems, during the climate event and in real time, preferably redistribute fluid flow at the fluid flow intersection location among the initial route, the first route and the second route. As such, one of the flow-distributing components of the present systems effectively modify the stress value and / or the estimated stress values based upon one of the flow redistributing strategies that reducethe fluid condition attribute value of at least one of the constraint locations in infrastructure to be equal to or below the assigned predetermined tolerable threshold attribute value. The constraint location, in one preferred embodiment of the present teachings and in connection with the infrastructure’s three-routes options, are chosen from a group comprising the initial location, the one location of the first route, the one location of the second route and the subsequent location. Each of the initial location, the one location of the first route, the one location of the second route and the subsequent location are deemed as “constraint locations” because the measurement of fluid condition attribute at any of those locations, during the climate event, is capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, their respective predetermined tolerable threshold attribute values.

[0166] Alternately, one of the flow-distributing components of the present systems effectively modify the route stress values and / or the estimated route stress values based upon one of the flow redistributing strategies that reduce one or more of the undesirable route stress values. In connection with the constraint locations present on these routes, one or more of the flow controllers of the present infrastructure management systems may be programmed to implement the following instructions: (i) determining a route stress value for each of the initial route, the first route, and the second route by: (a) adding stress value for constraint locations present along the initial route to produce an initial route stress value, (b) adding the stress value and the estimated stress value for constraint locations present along the first route to produce an estimated first route stress value and (c) adding the stress value and the estimated stress value for constraint locations present along the second route to produce an estimated second route stress value; (iii) identifying which one of the initial route stress value, the estimated first route stress value and the estimated second route stress value has highest magnitude to provide a highest stress route value; and (iv) redistributing, using one or more of the flow redistributing strategies, fluid flow in at least one of the fluid flow intersections, among the first route, the second route and the initial route to effectively reduce magnitude of one or more of the undesirable route stress values.

[0167] In other preferred embodiments of the present systems, one or more of the flow controllers redistribute between the first route and the second route, as they are the two options available in infrastructure for reducing undesirable stress present in one or more of the routes. In this scenario, one or more of the flow controllers are programmed to implement the following instructions: (1 ) determining an estimated route stress value for each of the first route and the second route by: (a) adding the stress value and the estimated stress value for constraint locations present along the first route to produce an estimated first route stress value, and (b) adding the stress value and the estimated stress value for constraint locations present along the second route to produce an estimated second route stress value; (2) identifying which one of the estimated first route stress value and the estimated second route stress value has highest magnitude to provide a highest stress route value; and (3) redistributing, using one or more of the flow redistributing strategies, fluid flow in at least one of the fluid flow intersections, between the first route and the second route to effectively reduce magnitude of the highest stress route value. In these embodiments, the estimated second route stress value represents a sum of the stress value for the subsequent location and the estimated stress value at one location of the second route.

[0168] In the present systems, RTUs may similarly operate in connection with one or more initial sensors and / or one or more subsequent sensors to provide estimated sensor measurement values at other locations, than the intermediate ones, to effectively relieve undesirable stress in infrastructure. To this end, certain preferred embodiments of the present systems include: (1 ) an initial sensor designed to be disposed at or near an initial location for measuring fluid condition attribute at the initial location and producing initial values; (2) an initial remote telemetry unit ("RTU") communicatively coupled to the initial sensor and has stored therein an initial flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at the initial location, as a function of time, and the initial RTU is designed to produce, for a climate event, at least one RTU estimated range of initial value based upon a climate event forecast and the initial values (e.g., RTUs 1402 is communicatively coupled to one or more sensors 1412 that is substantially similar to sensors 412 shown in Figures 13 or sensors 412 or 512 shown in Figure 14 and is disposed at or near initial location306 shown in Figure 5); (3) a subsequent sensor designed to be disposed at or near a subsequent location for measuring fluid condition attribute at the subsequent location and producing subsequent values, and the subsequent sensor is downstream from the initial sensor; (4) a subsequent RTU communicatively coupled to the subsequent sensor and has stored therein a subsequent flow model, which is a synchronized machinelearning model designed to estimate fluid condition attribute at the subsequent location, as a function of time, and the subsequent RTU is designed to produce, for the climate event, at least one RTU estimated range of subsequent value based upon the storm event forecast and the subsequent values (e.g., RTUs 1402 is communicatively coupled to one or more sensors 412 shown in Figures 13 or sensors 412 or 512 shown in Figure 14 and is disposed at or near subsequent location 328 shown in Figure 5); (5) one or more intermediate sensors, at least one of which is designed to be disposed on one location of a first route for measuring a fluid condition attribute at one location of the first route and producing one or more intermediate values.

[0169] In the context of an underlying infrastructure configuration, as shown in Figure 5, that has two routes, e.g., initial route and the first route, available as options for relieving undesirable stress, the first route facilitates fluid communication between the initial location and the subsequent location. Furthermore, in this infrastructure configuration, the fluid condition attribute at one location of the first route is affected by one or more intermediate streams flowing into the first route prior to one location of the first route that is deemed to be a “constraint location.” One or more intermediate RTUs, each of which is communicatively coupled to at least one of the intermediate sensors and has stored therein one flow model, which is a synchronized machine-learning model designed to estimate fluid condition attribute at the one location of the first route, as a function of time.

[0170] In these present systems, one or more of the intermediate RTUs are designed to produce, for the climate event and based upon the storm event forecast and one or more of the intermediate values, one or more RTU estimated range of intermediate values. In certain of these present systems, a server also provides a server estimated range of values as explained below

[0171] A server may be communicatively coupled to the initial RTU, the subsequent RTU and one or more of the intermediate RTUs and may have stored therein a digital twin of the initial flow model, the subsequent flow model and the one flow model. The digital twin of each of the initial flow model, the subsequent flow model and the one flow model is substantially similar to the initial flow model, the subsequent flow model and the one flow model stored on the initial RTU, the subsequent RTU and one of the intermediate RTUs. In this arrangement of the present systems, the server is designed to provide, for the climate event and based upon the storm event forecast and one or more of the initial values, the subsequent values, and intermediate values, server estimated range of initial values, server estimated range of subsequent values, and server estimated range of intermediate values, respectively. As explained above, based on certain criteria, initial values, subsequent values and intermediate values may be present on the server.

[0172] One or more flow controllers in these present arrangements are designed to be communicatively coupled to receive from the server, in real-time, the server estimated range of initial values or one or more of the initial values, the server estimated range of subsequent values or one or more of the subsequent values, and the server estimated range of intermediate values or one or more of the intermediate values. Furthermore, based upon these values received from the server, one or more of the flow controllers are programmed to determine, in real-time, an estimated stress value at each of the initial location, the subsequent location and the one location of the first route, respectively.

[0173] One or more flow-distributing components in the present arrangements are designed to receive information from one or more of the flow controllers. One or more of the flow-distributing components are disposed at one or more fluid flow intersections, which, inside infrastructure, are located downstream from and in fluid communication through an initial route with the initial location, such that fluid flow exiting the initial location flows through the initial route and into one or more of the flow-distributing components. In one configuration of the underlying infrastructure, a fluid flow intersection location represents an intersection of the initial route and the first route. In this infrastructure configuration, the initial location is the constraint location on the initialroute. Furthermore, the subsequent location and the one location of the first route are constraint locations on the first route.

[0174] Based upon the estimated stress value at each of the initial location, the subsequent condition, and the one location of the first route received from one or more of the flow controllers, each of these flow-distributing components implement, during a climate event and in real time, one of the flow redistributing strategies of redistributing fluid flow at the fluid flow intersection location between the initial route and the first route to effectively modify the estimated stress value obtained at one location of the first route to be below a predetermined tolerable threshold attribute value that is assigned to one location of the first route and / or to effectively modify the estimated stress value obtained at the initial location to be below a predetermined tolerable threshold attribute value that is assigned to the initial location.

[0175] In these present systems and in connection with the initial route and the first routes available as options for relieving undesirable stress, as shown in Figure 5, one or more of the flow controllers are programmed to implement the following instructions: (1 ) determining an estimated route stress value for each of the initial route and the first route by adding estimated stress values for constraint locations present along each of the initial route and the first route to produce an estimated initial route stress value and an estimated first route stress value; (2) identifying which one of the estimated initial route stress value and the estimated first route stress value has highest magnitude to provide a highest stress route value; and (3) redistributing, using one or more flow redistributing strategies, and during the storm event in real time, fluid flow in at least one of the fluid flow intersections among the initial route and the first route to effectively reduce magnitude of the highest stress route value. Accordingly, where each of the initial location, the one location of the first route and the subsequent location is deemed to be a constraint location in infrastructure, the estimated initial route stress value is represented by the estimated stress value at the initial location and the estimated first route stress value represents a sum of the estimated stress value for each of the subsequent location and the one location of the first route.

[0176] In these present systems, one or more of the flow controllers may be programmed for a different infrastructure configuration, in which each of one location ofthe first route, one location of the second route and the subsequent location are constraint locations present in infrastructure. In this underlying infrastructure configuration, a fluid flow intersection represents an intersection of the first route and the second route, as shown in Figure 4. Furthermore, one or more of the flow controllers, involved in managing this configuration, are programmed to implement the following instructions: (1 ) determining an estimated route stress value for each of the first route and the second route by adding estimated stress values for constraint locations present along each of the first route and the second route to produce an estimated first route stress value and an estimated second route stress value; (2) identifying which one of the estimated first route stress value and the estimated second route stress value has highest magnitude to provide a highest stress route value; and (3) redistributing, using one or more flow redistributing strategies, and during the climate event in real time, fluid flow in at least one of the fluid flow intersections, between the first route and the second route to effectively reduce magnitude of the highest stress route value. Accordingly, in the infrastructure configuration shown in Figure 4, where each of the one location of the first route, the one location of the second route and the subsequent location is deemed to be a constraint location in infrastructure, the estimated first route stress value represents a sum of the estimated stress value for each of the subsequent location and the one location of the first route and the estimated second route stress value represents a sum of the estimated stress value for each of the subsequent location and the one location of the second route.

[0177] The present teachings also offer novel present methods of infrastructure management. Although implementation of these present methods does not require a specific system configuration, but novel methods implemented using the structural details described in Figures 15-19 represent preferred embodiments of the present arrangements.

[0178] In connection with estimated sensor measurement values, one exemplar infrastructure management method, preferably, begins with an “obtaining a digital twin model” element, which includes obtaining, inside each of a server (e.g., server 1104 of Figure 15) and an RTU (e.g., RTU 1102 of Figure 15), a digital twin model. As explained above, the digital twin models provide, for an instance in time or for a period of time,one or more estimates of a fluid condition attribute inside a fluid infrastructure item.Next, the exemplar method advances to a receiving element that includes receiving, for the instance in time or for the period of time, a forecast of an environmental condition around an area surrounding a sensor (e.g., sensor 1112 of Figure 15). Then, an estimating element is carried out and uses, for the instance in time or for the period of time, a forecast of the environmental condition (obtained in the receiving element) and the digital twin models (obtained in “obtaining a digital twin model” element), at the RTU to generate a RTU estimated range of values for a fluid infrastructure item disposed on a constraint location.

[0179] The estimating element may also include estimating, at the server, for the instance in time or for the period of time, using the forecast of environmental condition and the digital twin models, to generate one or more server’s range of values for the fluid infrastructure item. In another embodiment, another element, which is different from the estimating element, in the exemplar method, is implemented to arrive at one or more server’s estimated range of values for the fluid infrastructure item. As a result, generating these two estimates, i.e., the RTU’s and the server’s estimated range of values of the fluid infrastructure item, may be thought of as two separate elements or as a single element of the exemplar method.

[0180] Regardless of whether one or two elements are implemented to generate these estimated fluid condition attribute values, the exemplar method proceeds to an “obtaining at RTU sensor measurement” element, which involves obtaining, using the sensor (e.g., sensor 1112 of Figure 15), at the RTU a sensor measurement of a fluid condition attribute inside the fluid infrastructure item. Then, the exemplar method advances to a comparing element of comparing, at the RTU, the sensor measurement with the RTU estimated range of values. In the comparing element, at the RTU, the sensor measurement of the fluid condition attribute inside the fluid infrastructure item is compared with one or more RTU estimated range of values. By way of example, Figure 18 shows a graphical representation 1424 as an exemplar illustration of “comparing” carried out under the comparing element.

[0181] Preferably, after the comparing element has concluded, a reporting element is carried out. According to one embodiment of the exemplar method, the reportingelement includes reporting, for the instance in time or for the period of time, the server estimated range of values being or being an estimate of the sensor measurement of a fluid condition attribute inside the fluid infrastructure item, if an absolute value of a difference between the sensor measurement and the RTU estimated range of values is equal to or less than a predefined threshold tolerance value, or if, for the instance in time or for the period of time, the sensor measurement falls within a predefined confidence interval of the RTU’s estimated range of values. By way of example, Figure 18 shows a graphical representation 1426 as an exemplar illustration of “reporting” carried out under the reporting element.

[0182] In another preferred embodiment of the present teachings, the reporting element involves, after a lapse of the instance in time or a lapse of the period of time, reporting the server’s estimated fluid condition attribute being provided in place of the sensor measurement of the fluid infrastructure item, if a sensor measurement of a fluid condition attribute inside the fluid infrastructure item is not received at the server. In one implementation of this embodiment, the RTU does not convey the sensor measurement of the fluid infrastructure item to the server, if the RTU determines that the absolute value of the difference between the sensor measurement and the RTU estimated range of values is equal to or less than a predefined threshold tolerance value, or determines that the sensor measurement, for the instance in time or for the period of time, falls within a predefined confidence interval of the RTU’s multiple estimated fluid condition attribute values of the fluid infrastructure item.

[0183] Prior to the implementation of the comparing element and / or reporting element, the exemplar method, more preferably, does not include conveying the sensor measurement of the fluid condition attribute inside the fluid infrastructure item, from the RTU to the server.

[0184] Another exemplar method, according to another embodiment of the present teachings includes carrying out “obtaining a digital twin model” element, the receiving element, the estimating element, the “obtaining at RTU sensor measurement” element, the comparing element and the reporting element, as described above. Instead of carrying out the comparing element, this exemplar method offers a conveying element,as it provides for a situation, in which the RTU conveys a sensor measurement, of a fluid condition attribute inside the fluid infrastructure item, to a server.

[0185] Accordingly, the conveying element involves conveying, from the RTU to the server, the sensor measurement for the instance in time or for the period of time, if the absolute value of the difference between the sensor measurement and one of the RTU estimated range of values is greater than the predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside the predefined confidence interval of the RTU estimated fluid condition attribute values. By way of example, Figure 18 shows a graphical representation 1524 as an exemplar illustration of the underlying computation before “conveying,” as described in the conveying element.

[0186] This exemplar method includes a “receiving information regarding a realized environmental condition” element involves receiving at the server, after lapse of the instance in time or a period of time, information regarding a realized environmental condition, / .e., realized around an area surrounding the fluid infrastructure item and the sensor for the instance in time or during the period of time. However, in one embodiment of this exemplar method, the “receiving information regarding a realized environmental condition” element of the present teachings may be carried out prior to the lapse of instance in time or prior to a period of time.

[0187] Next, this exemplar method involves carrying out a determining element that involves determining, based upon the information regarding the realized environmental condition (obtained from the “receiving information regarding a realized environmental condition” element) and the digital twin model present at the server, a server’s new estimated fluid condition attribute values inside the fluid infrastructure item for the instance in time or for the period of time.

[0188] Then, this exemplar method includes a comparing element that includes comparing, at the server, the sensor measurement (obtained from the conveying element) with one of the server’s new estimated fluid condition attribute values (obtained from the determining element).

[0189] This exemplar method then advances to a maintaining element, which involves maintaining the digital twin model at the server, if an absolute value of the differencebetween the sensor measurement and one of the server’s new estimated fluid condition attribute values is equal to or greater than a check predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside a check predefined confidence interval of multiple of the server’s new estimated range of values. By way of example, Figure 19 shows a graphical representation 1526 to illustrate the underlying computation performed before “maintaining,” as described under maintaining. Moreover, if an absolute value of the difference between the sensor measurement and one of the server’s new estimated fluid condition attribute values is equal to or greater than a check predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside a check predefined confidence interval of the server’s new estimated range of values, then the sensor measurement is conveyed from the server to one or more of the fluid-flow controllers of the present teachings.

[0190] The above-mentioned elements in connection with the exemplar method and another exemplar method may be implemented in a wide variety of different embodiments. By way of example, “obtaining a digital twin model” element includes building, inside the server or the RTU, the digital twin model providing, for the instance in time or for the period of time, one or more estimated fluid condition attribute values of the fluid infrastructure item. In one preferred embodiment, “obtaining a digital twin model” element of the present teachings comprises building a stochastic predictive model using sensor parameter information, a probability distribution function of environmental information in the area surrounding the sensor, input information and output information relating to the fluid infrastructure item. To this end, Figure 16 shows an exemplar digital twin model 1208 formed at server 1204.

[0191] The sensor parameter information includes at least one item chosen from a group comprising location of sensor, type of sensor, critical high fluid condition attribute that is detectable by the sensor, critical low fluid condition attribute that is detectable by the sensor, transmission rate of sensor data and battery level of the sensor.

[0192] The input information includes at least one information chosen from a group comprising precipitation information in an area surrounding the sensor associated withthe RTU, fluid level of one or more different inputs into the fluid infrastructure item and flow rate of one or more different inputs into the fluid infrastructure item.

[0193] The output information includes at least one information chosen from a group comprising evaporation information around the sensor associated with the RTU, fluid level of one or more different outputs exiting the fluid infrastructure item and flow rate of one or more different outputs exiting the fluid infrastructure item.

[0194] In addition to fluid level and / or fluid flowrate, fluid condition attribute of input information and output information may also include at least one attribute chosen from a group comprising hydraulic head, groundwater flux, rate of groundwater flux, pH, conductivity, concentration of total organic compounds, amount of total suspended solids and turbidity.

[0195] Building, as contemplated under “obtaining a digital twin model” element, preferably, includes generating, using a machine learning module, a probability distribution function of the estimated sensor measurements of the fluid condition attribute inside the fluid infrastructure item.

[0196] Regardless of the manner in which the digital twin model is obtained, “obtaining a digital twin model” element may include modifying, using the RTU and the sensor (e.g., sensor measurements provide insight into the reliability of the digital twin model’s estimate) the digital twin model until it reliably estimates the fluid condition attribute inside the fluid infrastructure item. By way of example, modifying of the digital twin model includes revising values of one or more parameters, associated with the fluid infrastructure item that is used to build an initial version of the digital twin model, until one or more of the estimates of the fluid condition attribute obtained from the digital twin model are equal or close to the sensor measurement (e.g., sensor measurements obtained from sensor 1212 of Figure 16).

[0197] In one preferred embodiment of the present teachings, modifying of the digital twin model includes determining that a Nash-Sutcliff coefficient of the digital twin model is greater than a predefined acceptable value, or determining that a root mean squared deviation, between the estimates of the fluid condition attribute and sensor measurements of the fluid condition attribute obtained for different instances in time or for different periods of time, is less than or equal to a predefined error value.

[0198] The present teachings recognize that building and modifying, if these elements are implemented, preferably, provides at least one of the digital twin models (e.g., digital twin model 1208 of Figure 16) inside the server (e.g., server 1204 of Figure 16). Further, the server (e.g., server 1204 of Figure 16) has installed therein or is communicatively coupled to a machine learning engine (e.g., machine learning engine 1206 of Figure 16) that builds the digital twin model and confirms that the digital twin model is an acceptable model for reliably estimating fluid condition attributes inside a fluid infrastructure item.

[0199] According to certain preferred embodiments of the present teachings, once an acceptable digital twin model is present at the server, the exemplar method includes a conveying element that involves conveying or transmitting a copy of the digital twin model from the server to the remote telemetry unit (e.g., server 1304 conveys a copy of digital twin model 1308, through network 1310, to RTU 1302 such that the copy is stored as digital twin model 1318 therein as shown in Figure 17).

[0200] After an acceptable digital twin model is obtained at the server, the exemplar method, preferably, further comprises storing the digital twin model on a memory (e.g., database 1142 of Figure 15) associated with the server (e.g., server 1104 of Figure 15), and on a remote memory (e.g., RTU’s memory 1130 of Figure 15) that is remotely located relative to the memory (e.g., database 1142 of Figure 15) or the server (e.g., server 1104 of Figure 15).

[0201] In one aspect of the receiving element, the exemplar method includes receiving a probability distribution function, for the instance in time or for the period of time, forecasting an amount of precipitation to be realized around an area surrounding the sensor. The probability distribution function, preferably, provides multiple estimated values for the amount of precipitation to be realized around the area surrounding the sensor.

[0202] According to preferred implementations of the present teachings, when implementing the estimating element of the exemplar method, a neural network computes the server estimated range of values for the instance in time or for the period of time. Further, a machine learning engine, disposed inside the RTU, computes the RTU estimated range of values for the instance in time or for the period of time. Furtherstill, each of the server estimated range of values and the RTU estimated range of values, preferably, is a probability distribution function. By way of example, in Figure 18, each of graphical representation 1426 at server 1404 and graphical representation 1424 at RTU 1402 show a probability distribution function estimating fluid condition attribute values inside the fluid infrastructure item.

[0203] Continuing with this example and in connection with the “obtaining at RTU sensor measurement” element described in connection with the exemplar embodiment, preferably, includes comparing, at the RTU, the sensor measurement of the fluid condition attribute with the RTU’s probability distribution function, estimated range of values for the fluid infrastructure item at a constraint location, for the instance in time or for the period of time.

[0204] A reporting element of the present methods, preferably, includes reporting, for the instance in time or for the period of time, a mean value of the server’s probability distribution function as being the sensor measurement or being an estimate of the fluid condition attribute inside the fluid infrastructure item, if the sensor measurement for the instance in time or for the period of time, falls within a predefined confidence interval of a mean value of the RTU’s probability distribution function. In one embodiment, the present teachings recognize that the confidence interval spans a predefined range of estimated fluid condition attribute values, which deviates from a mean value of the RTU’s probability distribution function.

[0205] In one preferred implementation of the exemplar method, the receiving element includes receiving, at a periodic rate, the forecast of the environmental condition around an area surrounding the sensor. In one implementation of this embodiment, the estimating element of the present teachings includes estimating, at the periodic rate or less than the periodic rate, and at the RTU fluid condition attribute inside the fluid infrastructure item to generate one or more RTU estimated range of values. Continuing with this embodiment, the “obtaining at RTU sensor measurement” of the present teachings includes obtaining, at a sampling rate of the sensor, the sensor measurement. In this embodiment, the sampling rate is greater than the periodic rate.

[0206] Further, if the absolute value of the difference between the sensor measurement and one of the RTU estimated range of values is greater than thepredefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside the predefined confidence interval of the RTU’s multiple estimated fluid condition attribute values, then the management method of the present teachings, preferably, further includes the conveying element described in connection with another exemplar method, at least at or less than the sampling rate, from the RTU to the server, the sensor measurement taken for the instance in time or for the period of time.

[0207] These preferred embodiments further include a receiving element (e.g., substantially similar to the receiving element described in connection with another exemplar method), after lapse of the instance in time or after lapse of the period of time and at the server, information regarding a realized environmental condition (e.g., amount of precipitation) realized in the area surrounding the sensor for the instance in time or for during the period of time. Next, like the determining element described in connection with another exemplar method, based upon the information regarding the realized environmental condition and the digital twin model present at the server, management methods of the present teachings provide a similar determining element that include determining a server’s new estimated range of values for the instance in time or for the period of time. In one embodiment of the similar determining element, the server’s new estimated range of values are a probability distribution function (e.g., the probability distribution functions shown in graphical representation 1526 of Figure 19).

[0208] Then, at the server, management methods of the present teachings implement a similar comparing element (e.g., substantially similar to the comparing element described in connection with another exemplar method), which involves comparing the sensor measurement with the server’s new estimated range of values. Management methods of the present teachings then advance to maintaining the digital twin model at the server, if an absolute value of the difference between the sensor measurement and one of the server’s new estimated range of values is equal to or greater than a check predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside a check predefined confidence interval of multiple of the server’s new estimated range of values. If the digital twin model is maintained at the server, then management methods of the present teachings includemaintaining the copy of digital twin model at the RTU. Moreover, if an absolute value of the difference between the sensor measurement and one of the server’s new estimated range of values is equal to or greater than a check predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls outside a check predefined confidence interval of the server’s estimated range of values, then the sensor measurement is conveyed from the server to one or more of the fluid flow controllers of the present teachings.

[0209] In preferred embodiments, management methods of the present teachings include obtaining, inside each of the server and inside the RTU, a new digital twin model different from the (original) digital twin model, if the absolute value of the difference between the sensor measurement and one of the server’s new estimated range of values is less than a check predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls inside the check predefined confidence interval of multiple of the server’s new estimated range of values.

[0210] In connection with another exemplar method, the present teachings offer additional different embodiments for effective management of a fluid network. In one such embodiment, another exemplar method includes obtaining, inside the RTU, a new digital twin model, if the absolute value of the difference between the sensor measurement and one of the RTU’s new estimated range of values is less than a check predefined threshold tolerance value, or if the sensor measurement, for the instance in time or for the period of time, falls inside the check predefined confidence interval of multiple of the RTU’s new estimated range of values.

[0211] Continuing with this embodiment, another exemplar method preferably, further includes conveying the new digital twin model, formed at the RTU, to the server. In this embodiment, the function of conveying is carried out using a communicative coupling between the RTU and the server. In this configuration, the server is communicatively coupled to multiple RTUs and has stored thereon one copy of the digital twin model that is also stored on one of the RTUs, Further, each RTU is coupled to a sensor that measures a particular type of fluid condition attribute inside a fluid infrastructure item disposed at or near a constraint location. The digital twin model at the server allows the server to use, after lapse of the instance in time or the period of time, informationregarding the amount of realized precipitation to arrive at the server’s new estimated range of values and operate, in certain instances, independently of the RTU, thereby conserving energy.

[0212] Regardless of whether an actual sensor measurement is available, or an estimated sensor value is relied upon, the present teachings offer infrastructure management methods that are capable of using either to effectively relieve stress in infrastructure.

[0213] Figure 20 shows an infrastructure management method 2000, according to one embodiment of the present teachings. Method 2000, preferably, begins with an “obtaining initial values” element 2002 that includes obtaining initial values using an initial sensor disposed at or near and measuring a fluid condition attribute at an initial location. In this element, the initial values may be obtained at one or more fluid flow controllers (e.g., decision support engine 406 of Figure 13 receives sensor information through components involved in low-level control and local control 552 shown in Figure 14). By way of example, sensors 412 shown in Figure 13 and 14 or sensor 512 shown in Figure 14 disposed at or near and measuring a fluid condition attribute at initial location 306 shown in Figure 5 provide the initial values to one or more fluid flow controllers.

[0214] As shown in Figure 20, method 2000 further includes an “obtaining subsequent values” 2004 that includes obtaining subsequent values using a subsequent sensor disposed at or near and measuring the fluid condition attribute at a subsequent location. By way of example, sensors 412 shown in Figure 13 and 14 or sensor 512 shown in Figure 14 disposed at or near and measuring the fluid condition attribute at subsequent location 328 shown in Figure 5 provide the subsequent values to one or more fluid flow controllers. Consistent with the configuration of the underlying infrastructure, the subsequent sensor is located downstream from the initial sensor.

[0215] Method 2000 further still includes an “obtaining intermediate values” 2006. Intermediate values element 2006 includes obtaining one or more intermediate values using one or more intermediate sensors at least one of which is disposed on and measuring fluid flowing in or stored at one location of a first route. By way of example, sensors 412 shown in Figure 13 and 14 or sensor 512 shown in Figure 14 disposed onintermediate location 318 of first route 312 shown in Figure 5 provide the intermediate values to one or more fluid flow controllers.

[0216] “Obtaining initial values” element 2002, “obtaining subsequent values” element 2004, and “obtaining intermediate values” element 2006 are not carried out in any specific order and are, preferably, carried out contemporaneously.

[0217] Method 2000 then proceeds to a determining element 2008 that involves determining a stress value at each of the initial location, one location of the first route and the subsequent location to produce an initial route stress value and a first route stress value. This element is based upon initial values, one or more of the intermediate values, and the subsequent values obtained in the preceding elements. In one implementation of element 2008, as it is discussed in connection with the underlying infrastructure configuration of Figure 5, the initial route stress value represents the stress value of at least the initial location (e.g., 306 shown in Figure 5) as it is the only shown constraint location on the initial route (e.g., initial route 310 shown in Figure 5). If additional constraint locations were present on the initial route, then the initial route stress value would represent the sum of the stress values of the initial location and the additional constraint locations on the initial route.

[0218] Accordingly, the first route stress value represents a sum of the stress values of at least one location (e.g., first location 318 shown in Figure 5) on the first route (e.g., first route 312 shown in Figure 5) and the subsequent location (e.g., subsequent location 328 shown in Figure 5) because, according to the embodiment of Figure 5, the one location of the first route and the subsequent locations are the only shown constraint locations on the first route. If additional constraint locations were present on the first route, then the initial route stress value would represent the sum of the stress values of the one location of the first route, the subsequent location and the additional constraint locations on the initial route.

[0219] Method 2000 then proceeds to an identifying element 2010 that involves identifying, which one of the initial route stress value and the first route stress value is of highest magnitude and generating a highest stress route value. Next, method 2000 advances to a redistributing element 2012 that includes redistributing fluid flow, during a climate event, using one or more flow-distributing components and based upon one ormore flow redistributing strategies, in the initial route and / or the first route to effectively reduce magnitude of the highest stress route value.

[0220] In this exemplar method, one or more of the flow-distributing components are disposed at one or more fluid flow intersections (e.g., location where flow-distributing component 316 shown in Figure 5 is disposed). A fluid flow intersection is located downstream from the initial location (e.g., initial location 306 shown in Figure 5) such that fluid flow exiting the initial location flows through the initial route (e.g., initial route 310 shown in Figure 5) into one or more of the flow-distributing components. In one configuration of the underlying infrastructure as shown in Figure 5, each of the fluid flow intersections intersects the initial route and the first route (e.g., initial route 310 and first route 312 shown in Figure 5).

[0221] In the present systems, one or more of the flow-distributing components (e g., flow-distributing components 116, 216, 316, 438 and 516 shown in Figures 3-5, 13 and 14, respectively) are communicatively coupled to one or more of the fluid flow controllers (e.g., digital support engine 406 and 506 shown in Figures 13 and 14, respectively) so that information may flow between one or more of the fluid flow controllers and one or more of the flow-distributing components.

[0222] The present real-time methods of managing infrastructure apply to the infrastructure configuration shown in Figure 5, where each of the initial location, the one location of the first route and the subsequent location is deemed to be a constraint location in infrastructure. They are so deemed because measurement of fluid condition attribute at the constraint location, during the storm event, is capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to the constraint location. The excessive fluid flow, in the initial route and the first route, is at least partially due to excessive fluid flow into the initial flow route and the first route from multiple intermediate streams (e.g., intermediate streams 58 shown in Figure 2).

[0223] The present teachings address the problems caused by at least two different types of climate events, e.g., a big storm event and small storm event. The present teachings, under one approach, set a fluid condition attribute at the constraint locations to equal to or less than a relatively high predetermined threshold tolerable attribute value, or a relatively low predetermined threshold tolerable attribute value, dependingon the flow redistribution strategies implemented to relieve stress on infrastructure during a certain type of climate event. In preferred embodiments, the redistributing element 2012 shown in Figure 20 includes reducing, during a big storm, the stress value of at least one of the constraint locations (e g., the initial location, one location of the first route and the subsequent location) to be equal to or below a relatively low predetermined tolerable threshold attribute value (e.g., Figure 12A and 12B). During a small storm, the redistributing includes implementing one of the flow redistributing strategies that reduces the stress value of at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or below a relatively high predetermined tolerable threshold attribute value (e.g., Figure 11A and 11 B).

[0224] Under this approach, the present teachings also allow for methods of infrastructure management should the storm conditions change. To this end, the present teachings also allow for adaptive control strategies to maintain the integrity of the infrastructure management systems and methods during variable weather conditions. When there is a departure from the predicted climate conditions, then redistributing element 2012 shown in Figure 20 may include replacing, during a small storm event that evolves into an unexpected big storm event, implementation of one flow redistributing strategy with another flow distributing strategy. In this adaptive control strategy, the one flow redistributing strategy modifies fluid condition attribute through at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of the constraint locations. The adaptive control strategy’s replacement with another flow distributing strategy modifies fluid condition attribute through at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of the constraint locations. In other words, during a transition from a small storm to a big storm event, the redistributing element 2012 shown in Figure 20, replaces predefined stress threshold settings of the relatively high predetermined tolerablethreshold attribute value (e.g., Figures 11 and 11 B) with relatively low predetermined tolerable threshold attribute value (e.g., Figures 12A and 12B).

[0225] In the configuration of the underlying infrastructure, where each of the fluid flow intersections intersects the initial route and the first route, the present teachings offer alternate embodiments to reduce stress in infrastructure. According to certain alternate embodiments of the present teachings, the redistributing element 2012 shown in Figure 20 need not focus on reducing the highest stress route value, rather the focus may be to reduce the stress values at one or more critical locations disposed along one or more routes in infrastructure.

[0226] By way of example, in the infrastructure configuration shown in Figure 5, an alternate redistributing element of the present teachings, redistributes fluid flow, by effectively modifying fluid flow through one of the flow-distribution components, disposed on at least one fluid flow intersections between the initial route and the first route, such that the stress value obtained at one location of the first route (e.g., intermediate location 318 of first route 312 shown in Figure 5) to be below a predetermined tolerable threshold attribute value that is assigned to the one location of the first flow route and / or the stress value obtained at the initial location (e.g., initial location 306 shown in Figure 3) to be below a predetermined tolerable threshold attribute value that is assigned to the initial location.

[0227] As another example, in the infrastructure configuration shown in Figure 5, yet another alternate redistributing element of the present teachings, redistributes fluid flow, by effectively modifying fluid flow through one of the flow-distribution components, disposed on at least one fluid flow intersections, to reduce a combination of the stress values of the initial location and one location on the first route to arrive at a “combined reduced stress values of the initial location and one location of the first route.” In the “combined reduced stress values of the initial location and one location of the first route,” either the stress value of the initial location is reduced and the stress value of the one location of the first route is increased, but within a predetermined tolerable threshold level, or the stress value of the one location of the first route is reduced and the stress value of the initial location is increased, but within the predetermined tolerable threshold level.

[0228] In certain embodiments of the present methods and in connection with the infrastructure configurations shown in Figures 3 and 4, multiple intermediate sensor measurements from one route and / or different routes (e.g., first route, second routes in each of Figures 3 and 4) are obtained. In these embodiments of the present methods, the “obtaining intermediate values” obtaining intermediate values 2006 includes obtaining multiple intermediate measurement values using multiple intermediate sensors. As explained above, at least one of the multiple intermediate sensors is disposed on and measures fluid flowing in or stored at one location of a first route to produce the intermediate measurement values. Further, in these embodiments of the present methods, at least another of the multiple intermediate sensors is disposed on and measures fluid flowing in or stored at one location of a second route to produce one or more additional intermediate values. In the context of the underlying infrastructure shown in Figure 3 and 4, the second route facilitates fluid flow from the initial location to the subsequent location.

[0229] In these embodiments of the present methods, in addition to the first route stress value, a determining element includes producing a second route stress value, which represents a sum of at least a stress value for one location on the second route (e.g., intermediate location 120 of first route 114 shown in Figure 3 and intermediate location 220 of first route 214 shown in Figure 4) and the stress value of the subsequent location (e.g., subsequent locations 128 and 228 shown in Figure 3 and 4, respectively). Furthermore, in connection with the infrastructure configuration shown in Figure 3, the determining element 2008 shown in Figure 20 includes identifying which one of the initial route stress value, the first route stress value and the second route stress value has highest magnitude to arrive at a highest stress route value. In connection with the infrastructure configuration shown in Figure 3, further still, redistributing element 2012 shown in Figure 20 includes redistributing fluid flow, based upon one or more of the flow redistributing strategies, in one route chosen from a group comprising the initial route, the first route and the second route to effectively reduce magnitude of the highest stress route value.

[0230] In connection with Figure 3 and adaptive control strategies offered by the present teachings, during a big storm event, redistributing element 2012 of Figure 20includes implementing, one of the flow redistributing strategies that reduces the stress value of at least one of the initial route, the first route and the second route to be equal to or below a relatively low predetermined tolerable threshold route stress value assigned to each of the initial route, the first route and the second route, respectively. During a small storm, the redistributing element 2012 of Figure 20 includes implementing, one of the flow redistributing strategies that reduces the stress value of at least one of the initial route, the first route and the second route to be equal to or below a relatively high predetermined tolerable threshold attribute value assigned to each of the initial route, the first route and the second route, respectively.

[0231] As shown in Figure 5, the present methods recognize that the underlying infrastructure configuration may not have a second route available as an option for relieving stress in infrastructure. In such circumstances, the redistributing element 2012 shown in Figure 20 effectively modifies fluid flow through one of the flow-distributing components (e.g., flow-distributing component 316 shown in Figure 5) such that the stress value obtained at one location of the first route (e.g., intermediate location 318 of first route 312 shown in Figure 5) to be below a predetermined tolerable threshold attribute value that is assigned to one location of the first flow route and / or the stress value obtained at the initial location (e.g., initial location 306 shown in Figure 5) below a predetermined tolerable threshold attribute value that is assigned to the initial location.

[0232] However, if the second route is available as shown in Figure 5, for example, in the underlying infrastructure, as an option for stress relief, then, in the present methods, redistributing element 2012 shown in Figure 20 includes reducing, based on one or more of the flow redistributing strategies, at least one route stress value chosen from a group comprising the initial route stress value, the first route stress value and the second route stress value. In these embodiments of the present methods, each of the initial location, one location of the first route, one location of the second route, and the subsequent location is, preferably, deemed to be a constraint location in infrastructure.

[0233] According yet another embodiment, the redistributing element of the present methods reduces a combined stress of multiple constraint locations. In these embodiments of the present methods, the redistributing element includes reducing a combination of the stress values of the constraint locations, within their assignedpredefined tolerable threshold stress values, to arrive at a “combined reduced stress values of the constraint locations.” Stated another way, in the “combined reduced stress values of the constraint locations,” it is possible to reduce stress at one constraint location at the expense of another constraint location but hold the increased stress value of another constraint location within its assigned predetermined tolerable threshold attribute value. This still accomplishes the present teachings’ goal of reducing undesirable stress in infrastructure.

[0234] By way of example, in connection with Figure 3, in the “combined reduced stress values of the constraint locations,” the stress value of one initial location 106 is reduced and the stress value of at least one of intermediate location 118 of first route 112 and / or intermediate location 120 of second route 114 is increased, but within a predetermined tolerable threshold level assigned to intermediate locations 118 and / or 120, or the stress value of at least one of intermediate locations 118 and / or 120 is reduced and the stress value at initial location 106 is increased, but within the predetermined tolerable threshold level assigned to initial location 106.

[0235] As another example, in connection with Figure 4, in the “combined reduced stress values of the constraint locations,” the stress value at intermediate location 218 of first route 212 is reduced and the stress value at intermediate location 220 of second route 214 is increased, but within a predetermined tolerable threshold level assigned to intermediate location 220, or the stress value of at intermediate location 220 is reduced and the stress value at intermediate location 218 is increased, but within the predetermined tolerable threshold level assigned to intermediate location 218.

[0236] As yet another example, in connection with Figure 5, in the “combined reduced stress values of the constraint locations,” the stress value at initial location 306 is reduced and the stress value at intermediate location 318 of first route 312 is increased, but within a predetermined tolerable threshold level assigned to intermediate location 318, or the stress value of at intermediate location 318 is reduced and the stress value at initial location 306 is increased, but within the predetermined tolerable threshold level assigned to intermediate location 306.

[0237] The present methods recognize that the underlying infrastructure configurations may not have an initial route available as an option for stress relief as shown in theinfrastructure configuration of Figure 4. In these embodiments of the present methods, redistributing element 2012 shown in Figure 20 includes reducing fluid flow rate through first route 212 and / or through second route 214. Under another approach in such circumstances, the redistributing element of the present methods for relieving stress in infrastructure does not consider the routes involved. Rather, the redistributing element of the present methods is based upon a combined stress value of multiple constraint locations. In connection with Figure 4, a “reduced combination of stress values of the constraint locations,” includes reducing from a combination of the stress values of the one location on the first route and the one location on the second route to arrive at a “reduced combination of stress values of the one location on the first route and the one location on the second route.” In the “reduced combination of stress values of the one location on the first route and the one location on the second route,” the stress value of intermediate location 318 on first route 312 is reduced and the stress value of intermediate location 320 on second route 314 is increased, but within a predetermined tolerable threshold level assigned to intermediate location 320, or the stress value of intermediate location 320 on second route 314 is reduced and the stress value of intermediate location 318 on first route 312 is increased, but within the predetermined tolerable threshold level assigned to intermediate location 318.

[0238] Regardless of the infrastructure configuration, a fluid condition attribute is at least one attribute chosen from a group comprising fluid flow rate, fluid height, fluid volume, hydraulic capacity, time of fluid retention, storage capacity, and fluid quality.

[0239] After the redistributing element 2012 shown in Figure 20 concludes, the present methods of infrastructure management may advance to carrying out other elements. By way of example, a comparing element of the present methods includes comparing outcomes resulting from implementing, during the storm event, each of the infrastructure management strategies. In one implementation of this example, comparing includes using one or more as measure of success in reducing the stress value at the one location of the first route and the one location of the second route. Key point indicators provide insight into the efficacy of an infrastructure management strategy by evaluating such infrastructure metrics as reducing overflow volume, reducing flooding volume, reducing energy consumption and increasing river waterquality. The present methods, next, preferably, store, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies.

[0240] Next, the present methods, preferably, perform a determining element. In preferred embodiments of the present teachings, the determining element includes determining, based on the comparing element, one or more successful infrastructure management strategies that effectively reduce the stress value, during the storm event, at one or more of the constraint locations. By way of example, in Figures 3 and 4, where the underlying infrastructure configuration includes, among other locations, one location of the first route and one location of the second route as constraint locations, the determining element includes determining one or more successful infrastructure management strategies that effectively reduce the stress value at one location of the first route and one location of the second route. As another example, in the configuration of the underlying infrastructure, as shown in Figure 5, where the constraint locations, among other locations, include the initial location and one location of the first route, the determining element includes determining one or more successful infrastructure management strategies that effectively reduce the stress value at the initial location and one location of the first route.

[0241] Regardless of how many and the nature of the constraint locations, after the determining element, a storing element may be carried out. The storing element includes storing, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies.

[0242] The present teachings offer present methods of implementing infrastructure management strategies, for example, for a current instance in time and in the absence of sensor measurement values and / or for a future instance in time. Figure 21 shows a method of implementing method of implementing infrastructure management strategies 2100, according to certain embodiments of the present teachings. Method 2100 includes an “obtaining initial values” element 2102 that involves obtaining initial values using an initial sensor disposed at or near and measuring a fluid condition attribute at an initial location. “Obtaining initial values” element 2102 is substantially similar to “obtaining initial values” 2002 shown in Figure 20. Method 2100 includes an “obtaining subsequent values” 2104 that involves obtaining subsequent values using a subsequentsensor disposed at or near and measuring the fluid condition attribute at the subsequent location. “Obtaining subsequent values” element 2104 is substantially similar to “obtaining subsequent values” element 2004 shown in Figure 20.

[0243] As shown in Figure 21 , method 2100 includes an “obtaining estimated intermediate values” element 2106 that involves obtaining , based upon a climate event forecast and one or more intermediate values, one or more server estimated intermediate range of values. This element is carried out using a server operating in conjunction with one or more intermediate sensors, at least one of which is disposed at or near and measures the fluid condition attribute at one location of the first route to produce one or more of the intermediate values. By way of example, a digital twin model server 408 or 508 or server 1504 of Figures 13, 14 and 15 may provide estimated range of values based upon a climate event forecast and one or more intermediate values. As shown in Figure 15, server 1504 computes, using precipitation data 1516, e.g., the actual amount of precipitation realized around areas surrounding one or more sensors (e.g., sensor 1512), one or more server estimated range of intermediate values (e.g., see curve in graphical representation 1526).

[0244] In preferred embodiments of the present methods of implementing infrastructure management strategies, the subsequent sensor is downstream from the initial sensor. Furthermore, “obtaining estimated intermediate values” 2106 element includes using a server operating in conjunction with one or more intermediate sensors (e.g., server 1304 operating in conjunction with multiple RTUs 1314A, 1314B and 1314C, each of which are associated with an intermediate sensor). At least one of the intermediate sensors is disposed at one location on a first route (e.g., sensor 1512 shown in Figure 19 is disposed at intermediate location 318 of route 312 shown in Figure 5) and measures the fluid condition attribute at the one location of the first route to produce one or more of the intermediate values (e.g., sensor 1512 disposed at intermediate location 318 of route 312 shown in Figure 5 would produce intermediate values). Furthermore, in these embodiments relying upon the infrastructure configuration shown in Figure 5, each of the initial location, one location on a first route and the subsequent location is a constraint location and the first route facilitates fluid communication between the initial location and the subsequent location.

[0245] In the present methods of implementing infrastructure management strategies, the server may be communicatively coupled to one or more of the fluid flow controllers (e.g., server 1404 of Figure 18 is the same as digital twin model server 408 shown in Figure 13 that is communicatively coupled to decision support engine 406 which is a fluid flow controller).

[0246] The present methods of implementing method of implementing infrastructure management strategies 2100 include a determining element 2108 that involves determining, preferably, in real time and using one or more of the fluid flow controllers, a stress value at each of the initial location and the subsequent location and an estimated stress value for the one location of the first route, based upon the initial value, the subsequent value, and one or more of the estimated intermediate values, respectively, to produce an initial route stress value and an estimated first route stress value.

[0247] The server and / or one or more of the flow controllers may carry out an identifying element 2110 that includes identifying - which one of the initial route stress value and the estimated first route stress value - is of highest magnitude and arriving at a highest stress route value. The initial route stress value, preferably, represents the stress value of at least the initial location. The estimated first route stress value, preferably, represents a sum of at least the estimated stress value of one location of the first route and the stress value of the subsequent location. Based upon the highest flow stress value, the present methods proceed to carrying out a formulating element 2112 that includes formulating one or more infrastructure management strategies that reduce the highest stress route value.

[0248] The preferred embodiments of the present methods of implementing method of implementing infrastructure management strategies 2100 next performs a comparing element 2114 that includes comparing each of the infrastructure management strategies to an outcome of the storm event. Comparing element 2114 is, preferably, performed using one or more key point indicators of success in reducing the highest flow stress value. The key point indicators include at least one metric chosen from a group comprising overflow volume, flooding volume, energy consumption and river water quality.

[0249] Then, present methods of implementing method of implementing infrastructure management strategies 2100 perform a determining element 2116 that includes determining one or more successful infrastructure management strategies that effectively reduce the highest flow stress value. This element is, preferably, based upon the comparing using one or more of the key point indicators of success in reducing the highest flow stress value. Next, as part of a storing element 2118, present method of implementing infrastructure management strategies 2100 management strategies 2100, preferably, store one or more of the successful infrastructure management strategies in one or more of the fluid flow controllers.

[0250] During a subsequent climate event and from one or more of the fluid flow controllers (e.g., decision support engines 406 or 506 shown in Figures 13 and 14), present methods of implementing method of implementing infrastructure management strategies 2100 perform a retrieving element 2120. In this element, one or more of the fluid flow controllers retrieve one or more of the successful infrastructure management strategies. Based upon one or more of the successful infrastructure management strategies, the present methods redistribute fluid flow, during the subsequent storm event, in real time, using one or more flow-distributing components redistributing fluid flow in the initial route and / or the first route to effectively reduce magnitude of the highest stress route value (e.g., flow-distributing component 316 redistributing fluid flow in initial route 310 and first route 312 shown in Figure 5).

[0251] In certain embodiments of the present teachings, the “obtaining estimated intermediate values” 2106 includes: (1 ) using one or more intermediate sensors, each of which are operating in conjunction with an intermediate RTU communicatively coupled to the server (e.g., sensor 1412 operating in conjunction with RTU 1402 that is communicatively coupled to server 1404 shown in Figure 18 or sensor 1512 operating in conjunction with RTU 1502 that is communicatively coupled to server 1504 shown in Figure 19); and (2) receiving from the server one of the estimated intermediate values based upon the intermediate remote telemetry unit (e.g., receiving from server 1404 an output of assumed sensor data 1426 shown in Figure 18 or receiving from server 1504 an output of RTU’s estimated sensor data 1526 shown in Figure 19). In theseembodiments, each of the initial location, the one location of the first route and the subsequent location is deemed to be a constraint location in infrastructure.

[0252] In connection with the adaptive control strategies using estimated stress values, certain embodiments of the present methods of implementing method of implementing infrastructure management strategies 2100 provide redistributing element 2122 to include implementing, during a small storm, one of the flow redistributing strategies that reduces the stress value and / or the estimated stress value of at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or below a relatively high predetermined tolerable threshold attribute value (e.g., Figures 11 A and 11 B). During a big storm event, redistributing element 2122 includes implementing, one of the flow redistributing strategies that reduces the stress value and / or the estimated stress value of at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or below a relatively low predetermined tolerable threshold attribute value (e.g., Figures 12A and 12B).

[0253] During the climate event, redistributing element 2122 shown in Figure 21 , of the preferred embodiments of the present teachings, includes replacing implementation of one flow redistributing strategy with another flow distributing strategy. In redistributing element 2122, when a small storm unexpectedly evolves in a big storm, the one flow redistributing strategy modifies fluid condition attribute through at least one of the constraint locations such that the modified fluid condition attribute value of at least one of the constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of the constraint locations, and another flow distributing strategy modifies fluid condition attribute through at least one of the constraint locations such that the modified fluid condition attribute value of at least one of the constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0254] By way of example, when the initial location and one location of the first route are constraint locations as shown in Figure 5, the redistributing element effectively modifies fluid flow through one of the flow-distribution components such that the stressvalue and / or the estimated stress value obtained at the one location of the first route to be below a predetermined tolerable threshold attribute value that is assigned to the one location of the first flow route and / or the stress value and / or the estimated stress value obtained at the initial location below a predetermined tolerable threshold attribute value that is assigned to the initial location. Instead of focusing on reduction of stress value at a particular constraint location, the present teachings also recognizing reducing magnitude of the highest stress route value using similar techniques.

[0255] In connection with the infrastructure configurations shown in Figure 3, the present methods may rely upon multiple estimated intermediate values, i.e., at least one more sensor in addition to at least one sensor disposed on one location of the first route. In certain embodiments of the present methods, the element of obtaining one or more estimated intermediate range of values includes using multiple intermediate sensors, at least another of which is disposed on and measuring fluid flowing in or stored at one location of a second route to produce another estimated intermediate value (e.g., sensors 1412 or 1512 shown in Figure 18 and 19, respectively, are disposed at an intermediate location 120 of second route 114 shown in Figure 3). The second route provides fluid communication between the initial location and the subsequent location.

[0256] In these embodiments, the determining element of the present methods includes producing an estimated second route stress value, which represents a sum of at least an estimated stress value at the one location on the second route and the stress value at the subsequent location, as these are the known constraint locations in the infrastructure configuration of Figure 3. The estimated stress value at the one location on the second route is based upon another estimated intermediate value. In this scenario, the determining element of the present methods includes identifying which one of the initial route stress value, the estimated first route stress value and the estimated second route stress value has highest magnitude to arrive at a highest stress route value.

[0257] Accordingly, when three different routes, initial route, the first route and the second route, are available as options in reducing stress in infrastructure, redistributing element 2122 shown in Figure 21 , preferably, includes redistributing fluid flow, basedupon one or more of the flow redistributing strategies, in one route chosen from a group comprising the initial route, the first route and the second route to effectively reduce magnitude of the highest stress route value.

[0258] In connection with the adaptive control strategies, redistributing element 2122 shown in Figure 21 , preferably, includes implementing, during a small storm event, one of the flow redistributing strategies that reduces the stress value of at least one of the initial route, the estimated first route stress value and the estimated second route stress value to be equal to or below a relatively high predetermined tolerable threshold attribute value. During a big storm, the redistributing element of the present methods, preferably, includes implementing one of the flow redistributing strategies that reduces the stress value of at least one of the initial route, the first route and the second route to be equal to or below a relatively low predetermined tolerable threshold attribute value.

[0259] Continuing with the adaptive control strategies, during a climate event, the redistributing element of the present methods may include replacing implementation of one flow redistributing strategy with another flow distributing strategy. The one flow redistributing strategy modifies fluid condition attribute through at least one of the initial route, the first route and the second route, such that each of the initial route stress value, the estimated first route stress value and the estimated second route stress value is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to one of the initial route, the first route and the second route, respectively. Furthermore, another flow distributing strategy modifies fluid condition attribute through at least one of the initial route, the first route and the second route, such that each of the initial route stress value, the estimated first route stress value and the estimated second route stress value is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to one of the initial route, the first route and the second route, respectively.

[0260] In the present methods of implementing infrastructure management strategies, redistributing element 2122 shown in Figure 21 , in the context of the constraint locations, / .e., initial location, one location of the first route and one location of the second route as shown in Figure 3, effectively modifies fluid flow through one of the flow-distribution components to produce at least one reduced stress condition.

[0261] Under one approach, a redistributing element of the present methods of implementing infrastructure management strategies may include reducing a combination of the stress values of the constraint locations to a “reduced combination of stress values of the constraint locations.” In the “reduced combination of stress values of the constraint locations” as it is applied to the infrastructure configuration shown in Figure 3, the stress value of the initial location is reduced and the stress values and / or the estimated stress values of at least others of the constraint locations, i.e., one location of the first route and one location of the second route is increased, but within a predetermined tolerable threshold level, or the estimated stress value of the one location of the first route is reduced and the stress value and / or the estimated stress values of at least others of the constraint locations, i.e., initial location and one location of the second route is increased, but within the predetermined tolerable threshold level, or the estimated stress value of the one location of the second route is reduced and the stress value and / or the estimated stress values of at least others of the constraint locations, i.e., initial location and one location of the first route is increased, but within the predetermined tolerable threshold level.

[0262] From a point of view of analyzing the amount of stress placed on each of the three routes involved, e.g., the initial route, the first route and the second route, a redistributing element of the present methods of implementing infrastructure management strategies, preferably, includes reducing, based on one or more of the flow redistributing strategies, one route stress value chosen from a group comprising the initial route stress value, the estimated first route stress value and the estimated second route stress value.

[0263] When the two routes, e.g., the first route and the second route are available as options to reduce stress on infrastructure as shown in Figure 4, then the redistributing element of the present methods includes reducing fluid flow rate through the first route and / or through the second route (e.g., first route 212 and second route 21 shown in Figure 4). In the configuration of these two routes, the element of obtaining one or more of the estimated intermediate fluid condition attribute values, preferably, includes obtaining multiple estimated intermediate fluid condition attribute values, using the server operating in conjunction with multiple intermediate sensors. At least one of themultiple intermediate sensors is disposed at the one location of the first route and another of the multiple intermediate sensors is disposed at one location of a second route, (e.g., sensors of the type denoted by reference numerals “1412” or “1512” shown in Figures 18 and 19, respectively, are disposed on intermediate location 218 of first route 212 and intermediate location 220 of second route 214 shown in Figure 4). Further, as mentioned above in connection with Figure 21 , at least one of the intermediate sensors measure fluid condition attribute at one location of the first route and at least another of the intermediate sensors measure fluid condition attribute at one location of the second route. In addition to an estimated stress value for the one location of the first route, the determining element of the present methods may include providing, based upon the multiple of the estimated intermediate values, an estimated stress value for the one location of the second route.

[0264] In a scenario where each of the fluid flow intersection location intersects the initial route, the first route, and the second route as shown in Figure 3, a redistributing element of the present methods of implementing infrastructure management strategies includes redistributing fluid flow between the first route and the second route, to effectively reduce stress along the first route and / or the second route and thereby reducing the estimated stress values at the one location of the first route and / or the one location of the second route. This redistributing element is based upon the stress value for each of the initial location and the subsequent location and the estimated stress value for the one location of the first route and the estimated stress value for the one location of the second route. In certain embodiments of the present methods, the redistributing element may be thought of as reducing fluid flow rate through the first route and / or reducing fluid flow through the second route.

[0265] When the three routes, e.g., the initial route, the first route and the second route as shown in Figure 3, are available as options to reduce stress on infrastructure, then the redistributing element of the present methods includes redistributing by implementing at least one strategy chosen from a group comprising reducing fluid flow rate through the initial route, reducing fluid flow rate through the first route, and reducing fluid flow rate through the second route.

[0266] In some aspects, the present teachings provide methods of implementing infrastructure management strategies, which rely upon estimated sensor measurement values not only at intermediate locations of a route, but also at an initial location inside infrastructure. One such exemplar method 2200, as shown in Figure 22, relies upon estimating sensor measurement values at an initial location and one location on a first route to reduce stress in infrastructure. This exemplar method features an “obtaining estimated initial values” element 2202, which includes obtaining based upon an initial value and a climate event forecast, a server estimated initial value using a server operating in conjunction with one or more initial sensors (e.g., server 1404 or 1504 operating in conjunction with one or more of sensors 1412 or 1512 shown in Figures 18 and 19). At least one of initial sensors is disposed at or near and measuring a fluid condition attribute at an initial location to produce the initial value (e.g., sensors 1412 or 1512 shown in Figures 18 and 19, disposed at initial location 106 shown in Figure 3).

[0267] As shown in Figure 22, method 2200 includes an “obtaining estimated subsequent values” element 2204, which involves obtaining a subsequent value using a subsequent sensor disposed at or near and measuring the fluid condition attribute at the subsequent location. The subsequent sensor is downstream from the initial sensor.“Obtaining a subsequent value” element 2204 shown in Figure 22 is substantially similar to “obtaining a subsequent value” obtaining subsequent values element 2104 shown in Figure 21 .

[0268] Present methods of implementing infrastructure management strategies 2200 provides an “obtaining estimated intermediate values” element 2206 that includes obtaining based upon the storm event forecast and one or more intermediate values, one or more server estimated range of intermediate values. The “obtaining intermediate values” element 2206 obtains one or more of the estimated intermediate values includes using the server operating in conjunction with one or more intermediate sensors. At least one of the intermediate sensors is disposed at one location on a first route and measure the fluid condition attribute at the one location of the first route to produce one or more of the intermediate values. “Obtaining intermediate values” element 2206 of Figure 22 is substantially similar to “obtaining intermediate values” obtaining intermediate values element 2106 shown in Figure 21.

[0269] In the underlying infrastructure configuration shown in Figure 5, the first route provides fluid communication between the initial location and the subsequent location and the server is communicatively coupled to one or more of the fluid flow controllers (e.g., digital twin server 408 or 508 are communicatively coupled to decision support engine 406 or 506 shown in Figures 13 and 14, respectively). When the sensor measurement values for the initial location and one location of the first route are estimated, a determining element 2208 is carried out.

[0270] Determining element 2208 includes determining a stress value for the subsequent location and an estimated stress value for each of the initial location and one location of the first route based upon the subsequent value, the server estimated range of initial values, and one or more of the server estimated range of intermediate values, respectively.

[0271] In preferred embodiments of determining element 2208, determining element produces an initial route stress value and an estimated first route stress value that are based upon stress value for the subsequent location and the server estimated range of stress value for each of the initial location and one location of the first route.

[0272] Next, present methods of implementing infrastructure management strategies 2200 carries out an identifying element 2210, which involves identifying which of the initial route stress value and the estimated first route stress value is of the highest magnitude and arriving at a highest flow stress value.

[0273] The present methods of implementing infrastructure management strategies 2200 then performs a formulating element 2212. In this element, based upon the two routes, e.g., initial route and the first route, available as options for reducing stress in infrastructure and the stress value for the subsequent location and the estimated stress value for each of the initial location and the one location of the first route, present methods of implementing infrastructure management strategies 2200 provides formulating one or more infrastructure management strategies that reduce stress along the initial route and / or the first route. As a result, formulating element 2210, preferably, reduces the server estimated range of stress value at the initial route and / or the server estimated range of stress value at one location of the first route.

[0274] Next, a comparing element 2214 involves comparing each of the infrastructure management strategies to an outcome of the storm event. This element is performed using one or more key point indicators of success in reducing the estimated stress value at the initial route and / or the estimated stress value at the one location of the first route.

[0275] Methods of implementing infrastructure management strategies 2200 includes a determining element 2216, which includes determining one or more successful infrastructure management strategies that effectively reduce the estimated stress along the initial route and / or the first route. Determining element 2216 is performed based on comparing the infrastructure management strategies using one or more of the key point indicators and evaluating which of the infrastructure management strategies reduce the estimated stress value at each of the initial route and / or first route.

[0276] A storing element 2218 then, preferably, includes, storing one or more of the successful infrastructure management strategies. In certain embodiments of the present methods of implementing infrastructure management strategies 2200, storing element 2218 is carried out using one or more of the fluid flow controllers (e.g., decision support engines 406 or 506 shown in Figures 13 and 14).

[0277] During a subsequent storm event and from one or more of the fluid flow controllers, if one or more fluid flow controllers are used for storing one or more of the successful infrastructure management strategies, a retrieving element 2220 retrieving one or more of the successful infrastructure management strategies.

[0278] Methods of implementing infrastructure management strategies 2200 features a redistributing element 2222, which includes redistributing fluid flow between the initial route and the first route, using one or more of the successful infrastructure management strategies, to effectively reduce stress along the initial route and / or the first route and thereby reduce the stress value at the initial location and / or one location of the first route during the subsequent storm event.

[0279] Redistributing element 2222 is carried out using one or more flow-distributing components (e.g., flow-distributing component 316 shown in Figure 5) disposed at one or more flow intersections. Each of the flow-distributing components is disposed downstream from the initial location such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components.

[0280] In the underlying infrastructure configuration shown in Figure 5, each of the fluid flow intersection location intersects the initial route and the first route. Moreover, in this infrastructure configuration, each of the initial location, one location of the first route and the subsequent location is deemed to be a constraint location in infrastructure.

[0281] Another redistributing element, in the present methods of implementing infrastructure management strategies, may include implementing, during a small storm event, one of the flow redistributing strategy that reduces the stress value and / or the estimated stress value of at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or below a relatively high predetermined tolerable threshold attribute value. During a big storm event, the redistributing includes implementing one of the flow redistributing strategies that reduces the stress value and / or the estimated stress value of at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or below a relatively low predetermined tolerable threshold attribute value.

[0282] During a climate event, yet another redistributing element includes replacing implementation of one flow redistributing strategy with another flow distributing strategy. In this embodiment of the redistributing element, when a small storm unexpectedly evolves into a big storm, one flow redistributing strategy modifies fluid condition attribute through at least one of the constraint locations such that the fluid condition attribute value of at least one of the constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of the constraint locations, and another flow distributing strategy modifies fluid condition attribute through at least one of the constraint locations such that the modified fluid condition attribute value of at least one of the constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0283] From a point of view of initial location 306 and intermediate location 318 of first route 312 as they are shown in Figure 5, the redistributing feature of the present methods may effectively modify fluid flow through one of flow-distribution components 316 such that the stress value and / or the estimated stress value obtained at onelocation of the first route to be below a predetermined tolerable threshold attribute value that is assigned to one location of the first flow route and / or the stress value and / or the estimated stress value obtained at the initial location to be below a predetermined tolerable threshold attribute value that is assigned to the initial location.

[0284] The redistributing feature of the present methods, under another approach, includes reducing a combination of the estimated stress values of the initial location and the one location on the first route to a “combination of reduced estimated stress values of the initial location and the one location of the first route.” In the “combination of reduced estimated stress values of the initial location and the one location of the first route,” the estimated stress value of the initial location is reduced and the estimated stress value of the one location of the first route is increased, but within a predetermined tolerable threshold level, or the estimated stress value of the one location of the first route is reduced and the estimated stress value of the initial location is increased, but within the predetermined tolerable threshold level.

[0285] Methods of implementing infrastructure management strategies 2200 shown in Figure 22 apply to the underlying infrastructure configuration shown in Figure 3. In certain embodiments of the present teachings, “obtaining intermediate estimated values” element 2206 may include obtaining multiple intermediate estimated values using multiple intermediate sensors. In these embodiments, in addition to the intermediate sensor disposed on the first route, at least another intermediate sensor is disposed on the first route and / or on the second route. Furthermore, in addition to at least one intermediate estimated value, obtaining multiple intermediate estimated values includes producing an additional intermediate estimated value using at least another of the multiple intermediate sensors that is operating in conjunction with the server. Another of the multiple intermediate sensors is disposed and measures fluid flowing in or stored at one location of a second route.

[0286] A determining element, as it is applied to the underlying infrastructure configuration shown in Figure 3, includes producing an estimated second route stress value, which may represent a sum of at least an estimated stress value for one location on the second route and the stress value of the subsequent location. The estimated stress value for the one location on the second route may be based upon anotherintermediate estimated value. In these embodiments, identifying element 2210, preferably, includes identifying which one of the initial route stress value, the estimated first route stress value and the estimated second route stress value has highest magnitude to arrive at a highest stress route value. Accordingly, the redistributing feature, as it applies to the underlying infrastructure configuration shown in Figure 3, includes redistributing fluid flow, based upon one or more of the flow redistributing strategies, in one route chosen from a group comprising the initial route, the first route and the second route to effectively reduce magnitude of the highest stress route value.

[0287] The present teachings recognize that certain embodiments of the present methods include RTU for estimating sensor results. By of example, “obtaining estimated intermediate values” element 2206 includes: (1 ) obtaining, at the server, the additional RTU estimated range of intermediate values using one or more intermediate RTUs, each of which are operating in conjunction with one or more intermediate sensors and also communicatively coupled to the server; and (2) receiving from the server one or more of the RTU estimated range of intermediate values based upon certain criteria.

[0288] In connection with the adaptive flow control strategies as they are implemented in the underlying infrastructure configuration shown in Figure 3, a redistributing element of the present methods include implementing, during a small storm, one of the flow redistributing strategies that reduces the stress value of at least one of the initial route, the first route and the second route to be equal to or below a relatively high predetermined tolerable threshold attribute value. During a big storm, the redistributing element includes implementing one of the flow redistributing strategies that reduces the stress value of the initial route and / or the estimated stress value of at least one of the first route and the second route to be equal to or below a relatively low predetermined tolerable threshold attribute value.

[0289] During a climate event, the redistributing element in connection with the underlying infrastructure configuration shown in Figure 3, may include replacing, implementation of one flow redistributing strategy with another flow distributing strategy. When a small storm unexpectedly evolves into a big storm, one of the flow redistributing strategies modifies fluid condition attribute through at least one of the initial route, the first route and the second route, such that at least one of the estimated initial routestress value, the estimated first route stress value and the estimated second route stress value is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of the initial route, the first route and the second route, and another flow redistributing strategy modifies fluid condition attribute through at least one of the initial route, the first route and the second route, such that at least one of the estimated initial route stress value, the estimated first route stress value and the estimated second route stress value is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of the constraint locations.

[0290] In connection with the constraint locations shown in Figure 5, e.g., initial location and one location of the first route, a redistributing element of the present methods, preferably, effectively modifies fluid flow through one of the flow-distribution components such that the estimated stress value obtained at the initial location is below a predetermined tolerable threshold attribute value that is assigned to the initial location and / or the estimated stress value obtained at the one location of the first route is below a predetermined tolerable threshold attribute value that is assigned to the one location of the first flow route.

[0291] In connection with the available three routes, e.g., the initial route, the first route and the second route, as options for relieving stress in infrastructure as shown in Figure 3, the redistributing feature of the present method includes reducing, based on one or more of the flow redistributing strategies, one estimated route stress value chosen from a group comprising the estimated initial route stress value, the estimated first route stress value and the estimated second route stress value.

[0292] Each of the initial location, the one location on the first route, one location on the second route, and the subsequent location is deemed to be a constraint location in infrastructure. In certain embodiments of the present methods, the redistributing includes reducing a combination of the estimated stress values of the constraint locations to a “combination of reduced estimated stress values of the constraint locations.” In the “combination of reduced stress values of the constraint locations,” as it may apply to Figure 3, the estimated stress value of one constraint location, i.e., the initial location is reduced and the stress value or the estimated stress values of at leastothers of the constraint locations is increased, but within a predetermined tolerable threshold level, or the estimated stress value of the other constrain location, e.g., one location of the first route, is reduced and the stress value and / or the estimated stress values of at least others of the constraint locations (which now includes the initial location) is increased, but within the predetermined tolerable threshold level, or the estimated stress value of the one location of the second route is reduced and the stress value and / or the estimated stress values of at least others of the constraint locations is increased, but within the predetermined tolerable threshold level.

[0293] In those instances, where two routes, e.g., the first route and the second route are available as options for reducing stress on infrastructure as shown in Figure 4, the redistributing features of the present methods includes reducing fluid flow rate through the first route and / or through the second route.

[0294] In the preferred embodiments of the present methods of implementing infrastructure strategies do not include or are not based upon: (1 ) determining or establishing a cost function of flow inside the infrastructure; (2) a cost function of realizing one or more potential outcomes of the infrastructure during the storm event; (3) minimizing a difference between a cost function of realizing one or more potential outcomes of the infrastructure and a cost function of flow inside the infrastructure; (4) do not include redistributing the fluid flow at a fluid flow intersection location of a high- quality treatment scheme and a low-quality treatment scheme; and (5) do not include redistributing for minimizing a difference between a cost function of realizing one or more potential outcomes of the fluid flow infrastructure and a cost function of flow inside the fluid flow infrastructure.

[0295] The present methods of implementing infrastructure management strategies may further include a comparing element, as it applies to the underlying infrastructure configuration shown in Figure 4. This element includes comparing outcomes resulting from implementing, during the climate event, each of the infrastructure management strategies. In these embodiments, this comparing element of the present methods, preferably, includes using one or more key point indicators as measure of success in reducing the estimated stress values at the one location of the first route and the one location of the second route. After the comparing element, the present methods ofimplementing infrastructure management strategies then feature a determining element that involves determining one or more successful infrastructure management strategies that effectively reduce the estimated stress values, during the climate event, at the one location of the first route and the one location of the second route. The present methods of implementing infrastructure management strategies may then proceed to storing, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies.

[0296] During a subsequent climate event, the present methods of implementing infrastructure management strategies feature a redistributing element that may be carried out in connection with the underlying infrastructure configuration shown in Figure 3. In this embodiment, the redistribution element includes redistributing fluid flow, in real time and during the subsequent climate event, using one or more flow-distributing components, and based upon one or more of the successful infrastructure management strategies, in at least one route chosen from a group comprising the initial route, the first route and the second route to effectively reduce magnitude of the highest stress route value. In this embodiment of the present methods, three routes, e.g., the initial route, the first route and the second route, are available as options for relieving stress in infrastructure.

[0297] In those instances where two routes, e.g., the initial route and the first route, are available as options for reducing stress on infrastructure as shown in Figure 5, the redistributing features of the present methods provide redistributing using one or more of the flow-distributing components that are disposed at one or more fluid flow intersections, each of which is located downstream from the initial location such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components. In this configuration, each of the fluid flow intersections intersects the initial route and the first route, and one or more of the flow-distributing components are communicatively coupled to one or more of the fluid flow controllers.

[0298] Figure 23 shows a method of implementing infrastructure management strategies 2300, according to certain embodiments of the present teachings. Method 2300 includes an “obtaining estimated initial values” element 2302 that include obtaining, based upon initial values and a climate event forecast, one or more serverestimated range of initial values. “Obtaining estimated initial values” element 2302 is carried out using a server operating in conjunction with one or more initial sensors. At least one of the initial sensors is disposed at or near and measuring a fluid condition attribute at an initial location to produce the initial values. “Obtaining estimated initial values” element 2302 is substantially similar to “obtaining estimated initial values” element 2202 shown in Figure 22.

[0299] Method 2300 also includes an “obtaining estimated subsequent values” element 2304, which involves obtaining, based upon subsequent values and a climate event forecast, one or more server estimated range of subsequent values. “Obtaining estimated subsequent values” element 2304 uses a server operating in conjunction with one or more subsequent sensors. At least one of the subsequent sensors is disposed at or near and measuring a fluid condition attribute at a subsequent location to produce subsequent values.

[0300] Method 2300 also includes an “obtaining estimated intermediate values” element, which includes obtaining, based upon the climate event forecast and one or more intermediate values, one or more server estimated range of intermediate values. “Obtaining estimated intermediate values” element 2306 uses the server operating in conjunction with one or more intermediate sensors. At least one of the intermediate sensors is disposed at one location on a first route and measures the fluid condition attribute at the one location of the first route to produce one or more of the intermediate values. “Obtaining estimated intermediate values” element 2306 is substantially similar to “obtaining estimated intermediate values” obtaining intermediate values element 2106 shown in Figure 21.

[0301] In the underlying infrastructure shown in Figures 3-5, the first route provides fluid communication between the initial location and the subsequent location. The server used in the present methods is communicatively coupled to one or more of the fluid flow controllers.

[0302] The present methods of implementing infrastructure management strategies include a determining element 2308 that is carried out using one or more of the fluid flow controllers. Determining element 2308 includes determining an estimated stress value for each of the initial location, the one location of the first route and thesubsequent location based upon the estimated initial value, one or more of the estimated intermediate values, and the estimated subsequent value, respectively. Each of the initial location, the one location of the first route and the subsequent location is deemed to be the constraint location in infrastructure.

[0303] When two routes, e.g., the initial route and the first route, are available as options for relieving stress on infrastructure as shown in Figure 5, methods 2300 then proceed to an establishing element 2310, which involves establishing an estimated route stress value for each of the initial route and the first route by adding the stress values for constraint locations present along each of the initial route and the first route to produce an estimated initial route stress value and an estimated first route stress value. The estimated initial route stress value, preferably, includes at least the estimated stress value at the initial location and the estimated first route stress value, preferably, represents a sum of at least the estimated stress value at the one location of the first route and the estimated stress value at the subsequent location.

[0304] Next, method 2300 carried out an identifying element 2312 that involves identifying which one of the estimated initial route stress value and the first route stress value has highest magnitude to arrive at least one highest stress route value.

[0305] Method 2300 features a redistributing element 2314 that includes redistributing, during a subsequent climate event, in real time and based upon one or more of the flow redistributing strategies, fluid flow in the initial route and / or the first route, to effectively reduce magnitude of at least one of the highest stress route values.

[0306] In certain embodiments of the present methods of implementing infrastructure management strategies include additional elements. In certain embodiments of the present teachings, method 2300 further includes a formulating element that involves formulating, based upon the estimated stress value for each of the initial location, the one location of the first route, and the subsequent location one or more infrastructure management strategies that reduce the estimated initial route stress value and / or the estimated first route stress value.

[0307] These embodiments, preferably, further include comparing, using one or more key point indicators of success in reducing the estimated initial route stress value and / or the estimated first route stress value, each of the infrastructure management strategiesto an outcome of the climate event. Then, these methods proceed to determining, based on the comparing using one or more of the key point indicators of success in reducing the estimated initial route stress value and / or the estimated first route stress value, one or more successful infrastructure management strategies that effectively reduce the highest stress value.

[0308] Next, the present methods include storing, in one or more of the fluid flow controllers, one or more of the successful infrastructure management strategies. During a subsequent storm event and from one or more of the fluid flow controllers, the present methods teach retrieving one or more of the successful infrastructure management strategies and redistributing fluid flow between the initial route and the first route, using one or more of the successful infrastructure management strategies to effectively reduce stress along the initial route and / or the first route. As a result, the present methods reduce the estimated initial route stress value and / or the estimated first route stress value during the subsequent climate event. The redistributing feature of the present methods is carried out using one or more flow-distributing components disposed at one or more flow intersections, each being downstream from the initial location such that fluid flow exiting the initial location flows through the initial route into one or more of the flow-distributing components and each of the fluid flow intersection location intersects the initial route and the first route.

[0309] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present teachings and arrangements. It will be apparent, however, to one skilled in the art that the present teachings and arrangements may be practiced without limitation to some or all of these specific details.

Claims

CLAIMSWhat is claimed is:1 . A real-time infrastructure management system comprising: an initial sensor disposed at or near an initial location and measuring fluid condition attribute at said initial location to produce initial values; a subsequent sensor disposed at or near a subsequent location and measuring said fluid condition attribute at said subsequent location to produce subsequent values, and wherein said subsequent sensor is located downstream from said initial sensor; multiple intermediate sensors, at least one of which is disposed at or near and measures said fluid condition attribute at one location of a first route to produce intermediate values, and at least another of said multiple intermediate sensors is disposed at or near and measures said fluid condition attribute at one location of a second route to produce additional intermediate values, wherein each of said first route and said second route facilitate fluid communication between said initial location and said subsequent location, and said second route is different from said first route, and wherein each of said initial location, said one location of said first route, said one location of said second route, and said subsequent location is a constraint location in infrastructure as measurement of said fluid condition attribute at each of said initial location, said one location of said first route, said one location of said second route, and said subsequent location, during a climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route, said one location of said second route, and said subsequent location, respectively; one or more flow controllers communicatively coupled to receive, in real time, said initial values from said initial sensor, said subsequent values from said subsequent sensor, and said intermediate values and said additional intermediate values from said multiple intermediate sensors, and based upon said initial values, said subsequent values, said intermediate values and said additional intermediate values, determine, during said climate event and in real time, a stress value for each of said constraintlocations, and implement one or more flow redistributing strategies that are based upon at least one of said stress values of at least one of said constraint locations; and one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route into one or more of said flow-distributing components, wherein each of said fluid flow intersections represents an intersection of said initial route, said first route and said second route, and at least one of said flow-distributing components, based upon one or more of flow distributing strategies received from one or more of said flow controllers during said climate event and in real time, redistribute fluid flow through at least one of said fluid flow intersections and among said initial route, said first route and said second route to effectively modify at least one of said stress values obtained from at least one of said constraint locations such that said fluid condition attribute values obtained from at least one of said constraint locations is equal to or below said predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

2. The real-time infrastructure management system of claim 1 , wherein each of said initial sensor, said subsequent sensor, and said multiple intermediate sensors is any sensor chosen from a group comprising level meter for measuring height or level value of fluid stored in said constraint location, flow rate meter for measuring flow rate of fluid flowing in said constraint location, and a contaminant sensor for measuring contaminant concentration of fluid flowing in said constraint location.

3. The real-time infrastructure management system of claim 1 , wherein one or more said flow controllers is a proportional-integral-derivative controller that controls an operation at said constraint location, and said operation is chosen from a group comprising pump rate, gate opening, valve opening and weir opening.

4. The real-time infrastructure management system of claim 1 , wherein each of said initial sensor, said subsequent sensor and said intermediate sensors measures at least one said fluid condition attribute chosen from a group comprising fluid flow rate, fluid height, fluid volume, hydraulic capacity, time of fluid retention, fluid storage capacity, contaminant concentration and fluid quality.

5. The real-time infrastructure management system of claim 1 , wherein one or more of said flow-distributing components include at least one item chosen from a group comprising fluid facility, fluid pump station, gate, inflatable dam, weir, pump and valve.

6. The real-time infrastructure management system of claim 1 , wherein said subsequent location includes a wastewater treatment facility providing therein a high- quality treatment scheme and / or a low-quality treatment scheme.

7. The real-time infrastructure management system of claim 6, wherein based upon said stress value at each of said initial location, said one location of said first route, said one location of said second route and said wastewater treatment plant, one or more of said flow-distributing components do not redistribute fluid flow between said high-quality treatment scheme and said low-quality treatment scheme, and wherein said low-quality treatment scheme is disposed at a separate location from location of said high-quality treatment scheme.

8. The real-time infrastructure management system of claim 1 , wherein one or more of said flow controllers being programmed to implement following functions: determining a route stress value for each of said initial route, said first route and said second route by adding said stress values for constraint locations present along each of said initial route, said first route and said second route to produce an initial route stress value, a first route stress value and a second route stress value; identifying which one of said initial route stress value, first route stress value, and said second route stress value has highest magnitude to generate at least one highest stress route value; and redistributing, during said climate event, in real time and based upon one of said flow redistributing strategies, fluid flow in one route chosen from a group comprising said initial route, said first route and said second route, that effectively reduces magnitude of at least one of said highest stress route value.

9. The real-time infrastructure management system of claim 8, wherein said initial route stress value represents said stress value at said initial location, said first route stress value represents a summation of said stress values at each of said one location of said first route and said subsequent location, said second route stress valuerepresents a summation of said stress values at each of said one location of said second route and said subsequent location, and wherein one or more of said flow controllers being programmed to: (i) effectively modify said stress value obtained at said initial location to be below a predetermined tolerable threshold attribute value that is assigned to said initial location, if said initial route stress value is said highest stress route value; (ii) effectively modify said stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first route, if said first route stress value is said highest stress route value; and (iii) effectively modify said stress value obtained at said one location of said second route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said second route, if said second route stress value is said highest stress route value.

10. The real-time infrastructure management system of claim 1 , wherein said flowdistributing components is integrated into one provision chosen from a group comprising dynamic underflow control, outfall storage, offline storage and storm tank.

11. A real-time infrastructure management system comprising: an initial sensor disposed at or near an initial location and measuring fluid condition attribute at said initial location to produce initial values; a subsequent sensor disposed at or near a subsequent location and measuring said fluid condition attribute at said subsequent location to produce subsequent values, and wherein said subsequent sensor is located downstream from said initial sensor; one or more intermediate sensors disposed at or near and measuring said fluid condition attribute at one location of said first route to produce intermediate values, wherein said first route facilitates fluid communication between said initial location and said subsequent location, and wherein each of said initial location, said one location of said first route and said subsequent location is a constraint location in infrastructure as measurement of said fluid condition attribute at each of said initial location, said one location of said first route and said subsequent location, during a climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned toeach of said initial location, said one location of said first route and said subsequent location, respectively; one or more flow controllers communicatively coupled to receive, in real time, said initial values from said initial sensor, said subsequent values from said subsequent sensor and said intermediate values from one or more of said intermediate sensors, and based upon said initial values, said subsequent values and said intermediate values, determine, during said climate event and in real time, a stress value at each of said constraint locations, and implement one or more flow redistributing strategies that are based upon at least one of said stress values of at least one of said constraint locations; and one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route into one or more of said flow-distributing components, wherein each of said fluid flow intersections represents an intersection of said initial route and said first route, and at least one of said flow-distributing components, based upon one or more of flow distributing strategies received from one or more of said flow controllers, during said climate event and in real time, redistribute fluid flow through at least one of said fluid flow intersections and between said initial route and said first route to effectively modify at least one of said stress values obtained from at least one of said constraint locations such that said fluid condition attribute values obtained from at least one of said constraint locations is equal to or below said predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

12. The real-time infrastructure management system of claim 11 , wherein said subsequent location includes a wastewater treatment facility providing therein a high-quality treatment scheme and / or a low-quality treatment scheme, and wherein based upon said stress value at each of said initial location, said one location of said first route and said wastewater treatment plant, one or more of said flow-distributing components do not redistribute fluid flow between said high-quality treatment scheme and said low-quality treatment scheme.

13. The real-time infrastructure management system of claim 11 , wherein one or more of said flow controllers being programmed to implement following functions: determining a route stress value for each of said initial route and said first route by adding said stress values for constraint locations present along each of said initial route and said first route to produce an initial route stress value and a first route stress value; identifying which one of said initial route stress value and said first route stress value has highest magnitude to arrive at least one highest stress route value; and redistributing, during said climate event, in real time and based upon one of said flow redistributing strategies, modifying fluid flow between said initial route and said first route to effectively reduce magnitude of at least one of said highest stress route value.

14. The real-time infrastructure management system of claim 13, wherein said initial route stress value represents said stress value at said initial location and said first route stress value represents a summation of said stress values at each of said one location of said first route and said subsequent location, and wherein one or more of said flow controllers being programmed to: (i) effectively modify said stress value obtained at said initial location to be below a predetermined tolerable threshold attribute value that is assigned to said initial location, if said initial route stress value is said highest stress value; and (ii) effectively modify said stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first route, if said first route stress value is said highest stress value.

15. A real-time infrastructure management system comprising: a subsequent sensor disposed at or near a subsequent location and measuring fluid condition attribute at said subsequent location to produce subsequent values, and wherein said subsequent sensor is located downstream from an initial location; multiple intermediate sensors, at least one of which is disposed at or near and measures said fluid condition attribute at said one location of a_first route to produce intermediate values, and at least another of said multiple intermediate sensors is disposed at or near one location of a second route and measures said fluid conditionattribute at said one location of a second route to produce additional intermediate values, wherein each of said first route and said second route facilitate fluid communication between said initial location and said subsequent location, and said second route is different from said first route, and wherein each of said one location of said first route, said one location of said second route, and said subsequent location is a constraint location in infrastructure as measurement of said fluid condition attribute at each of said one location of said first route, said one location of said second route, and said subsequent location, during said climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable threshold attribute value assigned to each of said one location of said first route, said one location of said second route, and said subsequent location, respectively; one or more flow controllers communicatively coupled to receive, in real time, said subsequent values from said subsequent sensor, and said intermediate values and said additional intermediate values from said multiple intermediate sensors, and based thereupon upon said subsequent values, said intermediate values and said additional intermediate values±determine, during said climate event and in real time, a stress value at each of said constraint locations, and implement one or more flow redistributing strategies that are based upon at least one of said stress values of at least one of said constraint locations; and one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route into one or more of said flow-distributing components, wherein each of said fluid flow intersections represents an intersection of said first route and said second route, and at least one of said flow-distributing components, based upon one or more of said flow distributing strategies received from one or more of said flow controllers during said climate event and in real time, redistribute fluid flow through at least one of said fluid flow intersections and between said first route and said second route to effectively modify at least one of said stress values obtained from at least one of said constraint locations such that said fluid condition attribute values obtained fromat least one of said constraint locations is equal to or below said predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

16. The real-time infrastructure management system of claim 15, wherein said subsequent location includes a wastewater treatment facility providing therein a high-quality treatment scheme and / or a low-quality treatment scheme, and wherein based upon said stress value at each of said one location of said first route, said one location of said second route and said wastewater treatment plant, one or more of said flow-distributing components do not redistribute fluid flow between said high-quality treatment scheme and said low-quality treatment scheme.

17. The real-time infrastructure management system of claim 16, wherein one or more of said flow controllers being programmed to implement following functions: determining a route stress value for each of said first route and said second route by adding said stress values for constraint locations present along each of said first route and said second route to produce a first route stress value and a second route stress value; identifying which one of said first route stress value and said second route stress value has highest magnitude to arrive at least one highest stress route value; and redistributing, during said climate event, in real time and based on one of said flow redistributing strategies, fluid flow in said first route and said second route to effectively reduce magnitude of at least one of said highest stress route value.

18. The real-time infrastructure management system of claim 17, wherein said first route stress value represents said stress value at each of said one location of said first route and said subsequent location and said second route stress value represents a summation of said stress values at each of said one location of said second route and said subsequent location, and wherein, to carry out said redistributing function, one or more of said flow controllers being programmed to: (i) effectively modify said stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first route, if said first route stressvalue is said highest stress value; and (ii) effectively modify said stress value obtained at said one location of said second route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said second route, if said second route stress value is said highest stress value.

19. A real-time infrastructure management system comprising: an initial sensor designed to be disposed at or near an initial location for measuring said fluid condition attribute at said initial location and producing initial values; a subsequent sensor designed to be disposed at or near a subsequent location for measuring said fluid condition attribute at said subsequent location and producing subsequent values, and wherein said subsequent sensor is downstream from said initial sensor; one or more intermediate sensors, at least one of which is designed to be disposed at or near and measures said fluid condition attribute at said one location of said first route to produce one or more intermediate values, and said first route facilitates fluid communication between said initial location and said subsequent location, wherein said fluid condition attribute at said one location of said first route is affected by one or more intermediate streams flowing into said first route prior to said one location of said first route; one or more intermediate remote telemetry units (“RTUs”), each of which is communicatively coupled to at least one of said intermediate sensors and has stored therein one flow model, which is a synchronized machine-learning model designed to generate an RTU estimated range of intermediate values for said one location of said first route, as a function of time, wherein one or more of said intermediate RTUs are designed to convey one or more of said intermediate values if one or more of said intermediate values are not within said RTU estimated range of intermediate values for one location of said first route; a server designed for communicatively coupling with one or more of said intermediate RTUs and having stored therein a digital twin model of said one flow model, wherein said digital twin of said one flow model is substantially similar to said one flow model stored on one of said intermediate RTUs, wherein said server isdesigned to estimate, based upon said climate event forecast and one or more of said intermediate values, said fluid condition attribute at or near said one location of said first route, and provide, for said climate event, at least one server estimated range of intermediate values, and said server is designed to receive, from one or more intermediate RTUs, one or more of said intermediate values that are not within said RTU estimated range of intermediate values for said one location of said first route and said server is designed to convey one or more of said intermediate values that are not within said server estimated range of intermediate values for said one location of said first route; one or more flow controllers designed to be communicatively coupled for receiving, in real-time, initial values from said initial sensor, subsequent values from said subsequent sensor, and one or more of said intermediate values or at least one of said server estimated range of intermediate values from said server, and one of said flow controllers is programmed to determine, in real-time, a stress value for each of said initial location and said subsequent location, and a stress value or an estimated stress value for said one location of said first route based upon said initial value, said subsequent value, one or more of said intermediate values or at least one of said server estimated range of intermediate values, respectively; and one or more flow-distributing components designed to be disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route and into one or more of said flow-distributing components, wherein said fluid flow intersection represents an intersection of said initial route and said first route, and wherein each of said flowdistributing components receive, from one or more of said flow controllers, one or more flow redistributing strategies that are based upon said stress value at each of said initial location and said subsequent condition, and stress value or said estimated stress value for said one location of said first route, and during said climate event and in real time, at least one of said flow-distributing components is designed to redistribute fluid flow, through said fluid flow intersection location and between said initial route and said first route, based upon one of said flow redistributing strategies that effectively modifies saidstress value and / or said estimated stress value of at least one constraint location such that said fluid condition attribute of at least one of said constraint locations in infrastructure is equal to or below a predetermined tolerable threshold attribute value that is assigned to at least one said constraint location; and wherein said constraint location is one location chosen from a group comprising said initial location, said one location of said first route and said subsequent location, and measurement or estimate of said fluid condition attribute at said location, during said climate event, is capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said location.

20. The real-time infrastructure management system of claim 19, wherein one or more of said flow controllers programmed to implement the following instructions: determining a route stress value for each of said first route and said initial route by adding said stress value for each of said constraint locations present along said initial route to produce an initial route stress value and adding said stress value or said estimated stress value for each of said constraint locations present along said first route to produce a first route stress value or an estimated first route stress value, and identifying which one of said initial route stress value and said first route stress value or said estimated first route stress value has highest magnitude to provide a highest stress route value; redistributing, using one or more of said flow redistributing strategies, fluid flow through at least one of said fluid flow intersections and between said first route and said initial route to effectively reduce magnitude of said highest stress route value.21 . The real-time infrastructure management system of claim 20, wherein said estimated first route stress value represents a sum of at least said stress value for said subsequent location and said estimated stress value at said one location of said first route, said first route stress value represents a sum of at least said stress value for said subsequent location and said stress value at said one location of said first route, and said initial route stress value includes said stress value of said initial route.

22. The real-time infrastructure management system of claim 20, further comprising:multiple intermediate sensors, at least another of which is designed to be disposed at or near and measures said fluid condition attribute at said one location of said second route to produce one or more additional intermediate values, and wherein said second route facilitates fluid communication between said initial location and said subsequent location, wherein said fluid condition attribute at said one location of said second route is affected by one or more intermediate streams flowing into said second route prior to said one location of said second route; multiple intermediate RTUs, at least two of which are communicatively coupled to two or more of said intermediate sensors and at least one of said multiple RTUs has stored therein another flow model, which is a synchronized machine-learning model designed to generate an additional RTU estimated range of intermediate values for said one location of said second route, as a function of time, and wherein one or more of said RTUs are designed to convey one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional RTU estimated range of intermediate values for said one location of said second route; wherein said server is designed to communicatively couple with multiple of said intermediate RTUs and has stored therein a digital twin of said another flow model, wherein said digital twin of said another flow model is substantially similar to said another flow model stored on one of said intermediate RTUs monitoring said one location of said second route, wherein said server produces additional server estimated range of intermediate values based upon said climate event forecast and one or more of said additional intermediate values, and said server is designed to receive, one or more of said additional intermediate values that are not within said additional RTU estimated range of intermediate values for said one location of said second route, and said server is designed to convey one or more of said additional intermediate values that are not within said additional server estimated range of intermediate values for said one location of said second route; wherein one or more of said flow controllers communicatively coupled to receive, in real-time, one or more of said additional intermediate values or at least one said additional server estimated range of intermediate values from said server, and one of said flow controllers is programmed to determine said stress value for each of said initiallocation and said subsequent location, and a stress value or an estimated stress value for each of said one location of said first route and said one location of said second route, respectively, based upon said initial value, said subsequent value, one or more of said intermediate values or at least one of said server estimated range of intermediate values, and one or more of said additional intermediate values or at least one of said additional server estimated range of intermediate values; and wherein, based upon said stress value for each of said initial location and said subsequent location, and stress value or said estimated stress value for each of said one location of said first route and said one location of said second route, at least one of said flow-distributing components, during said climate event and in real time, redistribute fluid flow through said fluid flow intersection among said initial route, said first route and said second route to effectively modify said stress value and / or said estimated stress value of at least one of said constraint locations in infrastructure such that said fluid condition attribute of at least one of said constraint locations is equal to or below a predetermined tolerable threshold attribute value that is assigned to at least one of said constraint locations; and wherein said constraint location is said one location chosen from a group comprising said initial location, said one location of said first route, said one location of said second route and said subsequent location, and measurement of said fluid condition attribute at said location, during said climate event, are capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said location.

23. The real-time infrastructure management system of claim 22, wherein one or more of said flow controllers programmed to implement the following instructions: determining a route stress value for each of said initial route, said first route, and said second route by adding stress value for each of said constraint locations present along said initial route to produce an initial route stress value, adding said stress value or said estimated stress value for each of constraint locations present along said first route to produce a first route stress value or an estimated first route stress value and adding said stress value or said estimated stress value for each of constraint locationspresent along said second route to produce a second route stress value or an estimated second route stress value; identifying which one of said initial route stress value, said first route stress value or said estimated first route stress value, and said second route stress value or said estimated second route stress value has highest magnitude to provide a highest stress route value; redistributing, using one or more of said flow redistributing strategies, fluid flow through at least one of said fluid flow intersections and among said first route, said second route and said initial route to effectively reduce magnitude of said highest stress route value.

24. A real-time infrastructure management system comprising: a subsequent sensor designed to be disposed at or near and measuring fluid condition attribute at a subsequent location to produce subsequent values, and wherein said subsequent sensor is downstream from an initial location; multiple intermediate sensors, at least one of which is designed to be disposed at or near and measuring said fluid condition attribute at one location of said first route to produce one or more intermediate values, and at least another of said multiple intermediate sensors is designed to be disposed at or near and measuring said fluid condition attribute at one location of said second route to produce one or more additional intermediate values, and wherein said first route and said second route facilitate fluid communication between said initial location and said subsequent location, wherein said fluid condition attribute at said one location of said first route and said one location of said second route is affected by one or more intermediate streams flowing into said first route and said second route prior to said one location of said first route and prior to said one location of said second route, respectively; multiple intermediate remote telemetry units (“RTUs”), at least two of which are communicatively coupled to said multiple intermediate sensors and at least one of said multiple intermediate RTUs has stored therein one flow model, which is a synchronized machine-learning model designed to estimate and generate an RTU estimated range of intermediate values for said one location of said first route, as a function of time and based upon a climate event forecast and one or more of said intermediate values atsaid one location of said first route, and at least another of said multiple intermediate RTUs has stored therein another flow model, which is a synchronized machine-learning model designed to estimate and generate an additional RTU estimated range of intermediate values for said one location of said second route, as a function of time and based upon said climate event forecast and one or more of said additional intermediate values at said one location of said second route, and wherein said multiple intermediate RTUs are designed to convey one or more of said intermediate values, if one or more of said intermediate values are not within said RTU estimated range of intermediate values for said one location of said first route and also designed to convey one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional RTU estimated range of intermediate values for said one location of said second route; a server designed for communicatively coupling with said multiple intermediate RTUs, and said server having stored therein a digital twin model of said one flow model, wherein said digital twin of said one flow model is substantially similar to said one flow model stored on one of said intermediate RTUs, wherein said server is designed to estimate, based upon said climate event forecast and one or more of said intermediate values, said fluid condition attribute at or near said one location of said first route and provide a server estimated range of intermediate values for said one location of said first route, and said server has also stored therein a digital twin of said another flow model, wherein said digital twin of said another flow model is substantially similar to said another flow model stored on another of said multiple intermediate RTUs monitoring said one location of said second route, wherein said server produces at least one additional server estimated range of intermediate values based upon said climate storm event forecast and one or more of said additional intermediate values, and said server is designed to receive, from one or more of said multiple intermediate RTUs, one or more of said intermediate values that are not within said RTU estimated range of intermediate values for said one location of said first route and also designed to receive one or more of said additional intermediate values that are not within said additional RTU estimated range of intermediate values for said one location of said second route, and said server is designed to convey one or more of said intermediate values that arenot within said server estimated range of intermediate values for said one location of said first route and also designed to convey one or more of said additional intermediate values that are not within said additional server estimated range of intermediate values for said one location of said second route; one or more flow controllers designed to be communicatively coupled for receiving, in real-time, initial values from said initial sensor, subsequent values from said subsequent sensor, one or more of said intermediate values or at least one of said server estimated range of intermediate values, or one or more of said additional intermediate value or at least one said server estimated additional intermediate values from said server, and one of said flow controllers is programmed to determine, in realtime, a stress value for each of said initial location and said subsequent location, a stress value or an estimated stress value for each of said one location of said first route and said one location of second first route based upon said initial value, said subsequent value, one or more of said intermediate values or at least one of said server estimated range of intermediate values, or one or more of said additional intermediate value or at least one said additional server estimated range of intermediate values, respectively; and one or more flow-distributing components designed to be disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route and into one or more of said flow-distributing components, wherein said fluid flow intersection represents an intersection of said initial route, said first route and said second route, and wherein each of said flow-distributing components receive, from one or more of said flow controllers, one or more flow redistributing strategies that are based upon said stress value at each of said initial location and said subsequent condition, said stress value or said estimated stress value for each of said one location of said first route and said one location of said second route, and during said climate event and in real time, at least one of said flowdistributing components is designed to redistribute fluid flow through said fluid flow intersection location and among said initial route, said first route and said second route, based upon one of said flow redistributing strategies that effectively modifies said stressvalue and / or said estimated stress value of at least one of constraint locations in infrastructure such that said fluid condition attribute of at least one of said constraint locations is equal to or below a predetermined tolerable threshold attribute value that is assigned to at least one of said constraint locations; and wherein said constraint location is one location chosen from a group comprising said initial location, said one location of said first route, said one location of said second route and said subsequent location, and measurement of said fluid condition attribute at said location, during said climate event, are capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said location.

25. The real-time infrastructure management system of claim 24, wherein one or more of said flow controllers programmed to implement the following instructions: determining a route stress value for each of said first route and said second route by adding said stress value or said estimated stress value for each of said constraint locations present along said first route to produce a first route stress value or an estimated first route stress value, and adding said stress value or said estimated stress value for each of said constraint locations present along said second route to produce a second route stress value or an estimated second route stress value; identifying which one of said first route stress value or said estimated first route stress value and said second route stress value or said estimated second route stress value has highest magnitude to provide a highest stress route value; and redistributing, using one or more of said flow redistributing strategies, fluid flow through at least one of said fluid flow intersections and between said first route and said second route to effectively reduce magnitude of said highest stress route value.

26. The real-time infrastructure management system of claim 25, wherein said estimated second route stress value represents a sum of said stress value for said subsequent location and said stress value or said estimated stress value at said one location of said second route.

27. A real-time infrastructure management system comprising: an initial sensor designed to be disposed at or near and measuring fluid condition attribute at an initial location, located on an initial route, to produce initial values,wherein said fluid condition attribute at said initial location is affected by one or more intermediate streams flowing into said initial route prior to said initial location; an initial remote telemetry unit (“RTU”) communicatively coupled to said initial sensor and has stored therein an initial flow model, which is a synchronized machinelearning model designed to estimate said fluid condition attribute at said initial location, as a function of time, and to produce, for a climate event, an RTU estimated range of initial values based upon said climate event forecast and said initial values, and wherein said initial RTU is designed to convey said initial values if said initial values are not within said RTU estimated range of initial values; a subsequent sensor designed to be disposed at or near and measuring said fluid condition attribute at said subsequent location to produce subsequent values, and wherein said subsequent sensor is downstream from said initial sensor, wherein said fluid condition attribute at said subsequent location is affected by one or more intermediate streams flowing into said subsequent location; a subsequent RTU communicatively coupled to said subsequent sensor and has stored therein a subsequent flow model, which is a synchronized machine-learning model designed to estimate said fluid condition attribute at said subsequent location, as a function of time, wherein said subsequent RTU is designed to produce, based upon said climate event forecast and subsequent values, an RTU estimated range of subsequent values, and wherein said subsequent RTU is designed to convey said subsequent values, if said subsequent values are not within said RTU estimated range of subsequent values; one or more intermediate sensors, at least one of which is designed to be disposed at or near and measuring said fluid condition attribute at one location of said first route to produce one or more intermediate values, and said first route facilitates fluid communication between said initial location and said subsequent location, wherein said fluid condition attribute at said one location of said first route is affected by one or more intermediate streams flowing into said first route prior to said one location of said first route; one or more intermediate RTUs, each of which is communicatively coupled to at least one of said intermediate sensors and has stored therein one flow model, which isa synchronized machine-learning model designed to estimate said fluid condition attribute at said one location of said first route, as a function of time, wherein one or more of said intermediate RTUs are designed to produce, for said climate event and based upon said climate event forecast and one or more of said intermediate values, an RTU estimated range of intermediate values, and wherein said intermediate RTU is designed to convey one or more of said intermediate values if one or more of said intermediate values are not within said RTU estimated range of intermediate values; a server designed for communicatively coupling with said initial RTU, said subsequent RTU and one or more of said intermediate RTUs and having stored therein a digital twin of said initial flow model, said subsequent flow model and said one flow model, wherein said digital twin of each of said initial flow model, said subsequent flow model and said one flow model is substantially similar to said initial flow model, said subsequent flow model and said one flow model stored on said initial RTU, said subsequent RTU and one of said intermediate RTUs, respectively, wherein said server is designed to estimate, for said climate event and based upon said climate event forecast and one or more of said initial values, said subsequent values, and said intermediate values, said fluid condition attribute at said initial location, said subsequent location and said one location of said first route, respectively, to provide a server estimated range of initial values, a server estimated range of subsequent values and a server estimated range of intermediate values, and said server is designed to receive from said initial RTU said initial values if said initial values are not within said RTU estimated range of initial values, receive from said subsequent RTU said subsequent values, if said subsequent values are not within said RTU estimated range of subsequent values, and receive from said intermediate RTU one or more of said intermediate values, if said intermediate values are not within said RTU estimated range of intermediate values, and said server is designed to convey those of said initial values, said subsequent values and said intermediate values that are not within said server estimates range of initial values, said server estimates range of subsequent values and said server estimates range of intermediate values, respectively; one or more flow controllers designed to be communicatively coupled to receive from said server, in real-time, said initial values or said server estimated range of initialvalues, said subsequent values or said server estimated range of subsequent values, said intermediate values or said server estimates range of intermediate values, and one of said flow controllers is programmed to determine, in real-time, a stress value or an estimated stress value for each of said initial location, said subsequent location and said one location of said first route, respectively, based upon said initial values or said server estimated range of initial values, said subsequent values or said server estimated range of subsequent values, said intermediate values of said server estimates range of intermediate values; one or more flow-distributing components designed to be disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through said initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route and into one or more of said flow-distributing components, wherein said fluid flow intersection represents an intersection of said initial route and said first route, and each of said flow-distributing components implement one of said flow redistributing strategies, received from one or more of said flow controllers, that redistribute during said climate event and in real time, based upon said stress value or said estimated stress value at each of said initial location, said subsequent condition, and said one location of said first route, fluid flow through said fluid flow intersection location and between said initial route and said first route to effectively modify said stress value or said estimated stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first route and / or to effectively modify said estimated stress value obtained at said initial location to be below a predetermined tolerable threshold attribute value that is assigned to said initial location; wherein each of said initial location, said one location of said first route and said subsequent location is a constraint location in infrastructure as measurement or estimate of said fluid condition attribute at said constraint location, during said climate event, is capable of reaching or exceeding, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

28. The real-time infrastructure management system of claim 27, wherein one or more of said flow controllers programmed to implement the following instructions: determining a route stress value for each of said initial route and said first route by adding said stress value or said estimated stress value for each of said constraint locations present along said first route to produce a first route stress value or an estimated first route stress value, and adding said stress value or said estimated stress value for each of said constraint locations present along said second route to produce a second route stress value or an estimated second route stress value; identifying which one of said first route stress value or said estimated first route stress value and said second route stress value or said estimated second route stress value has highest magnitude to provide a highest stress route value; and redistributing, using one or more of said flow redistributing strategies, fluid flow through at least one of said fluid flow intersections and between said first route and said second route to effectively reduce magnitude of said highest stress route value.

29. The real-time infrastructure management system of claim 28, wherein said estimated first route stress value represents a sum of said estimated stress value for said subsequent location and said estimated stress value at said one location of said first route and said estimated initial route stress value represents an estimated stress value at said initial location.

30. The real-time infrastructure management system of claim 27, further comprising: multiple intermediate sensors, at least one of which is designed to be disposed at or near and measuring said fluid condition attribute at one location of said second route to produce one or more additional intermediate values, and wherein said second route facilitates fluid communication between said initial location and said subsequent location, wherein said fluid condition attribute at said one location of said second route is affected by one or more intermediate streams flowing into said second route prior to said one location of said second route; multiple intermediate RTUs, at least two of which are communicatively coupled to two or more of said intermediate sensors and at least one of which has stored therein another flow model, which is a synchronized machine-learning model designed to generate an additional RTU’s estimated range of intermediate values for said onelocation of said second route, as a function of time, and wherein one or more of said RTUs are designed to convey one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional RTU estimated range of intermediate values for said one location of said second route; wherein said server is designed to communicatively couple with multiple of said intermediate RTUs and has stored therein a digital twin of said another flow model, wherein said digital twin of said another flow model is substantially similar to said another flow model stored on one of said intermediate RTUs monitoring said one location of said second route, wherein said server produces an additional server estimated range of intermediate value based upon a climate event forecast and one or more of said additional intermediate values, and said server is designed to receive from one or more of said RTUs, one or more of said additional intermediate values that are not within said additional RTU estimated range of intermediate values for said one location of said second route, and said server is designed to convey one or more of said additional intermediate values that are not within said server estimated range of intermediate values for said one location of said second route; wherein one or more of said flow controllers communicatively coupled to receive, in real-time, one or more of said additional intermediate values at least one said additional server estimated range of intermediate values from said server, and one of said flow controllers is programmed to determine said stress value or said estimated stress value for each of said initial location and said subsequent location, said one location of said first route, and said one location of said second route, respectively, based upon said initial value, said subsequent value, one or more of said intermediate values or at least one of said server estimated range of intermediate values, one or more of said additional intermediate values or at least one of said additional server estimated range of intermediate values; and wherein, based upon said stress value or estimates stress value for each of said initial location, said subsequent location, said one location of said first route and said one location of said second route, at least one of said flow-distributing components, during said climate event and in real time, redistribute fluid flow through said fluid flow intersection location among said initial location, said first route and said second route toeffectively modify said stress value and / or said estimated stress value of at least one said constraint locations in infrastructure such that said fluid condition attribute value of at least one of said constraint locations is equal to or below a predetermined tolerable threshold attribute value that is assigned to at least one of said constraint locations; and wherein said constraint location is said one location chosen from a group comprising said initial location, said one location of said first route, said one location of said second route and said subsequent location, and measurement of said fluid condition attribute at said location, during said climate event, are capable of reaching or exceeding, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said location. 31 . The real-time infrastructure management system of claim 30, wherein one or more of said flow controllers programmed to implement the following instructions: determining a route stress value for each of said initial route, said first route and said second route by adding said stress value or said estimated stress value for each of said constraint locations present along said initial route to produce an initial route stress value or an estimated initial route stress value, adding said stress value or said estimated stress value for each of said constraint locations present along said first route to produce a first route stress value or an estimated first route stress value, and adding said stress value or said estimated stress value for each of said constraint locations present along said second route to produce a second route stress value or an estimated second route stress value; identifying which one of said initial route stress value or estimated initial route stress value, said first route stress value or said estimated first route stress value and said second route stress value or said estimated second route stress value has highest magnitude to provide a highest stress route value; and redistributing, using one or more of said flow redistributing strategies, fluid flow through at least one of said fluid flow intersections and among said initial route, said first route and said second route to effectively reduce magnitude of said highest stress route value.

32. The real-time infrastructure management system of claim 31 , wherein said estimated second route stress value represents a sum of said estimated stress value for each of said subsequent location and said one location of said second route.

33. A real-time infrastructure management system comprising: a subsequent sensor disposed at or near and measuring fluid condition attribute at a subsequent location to produce subsequent values, and wherein said subsequent sensor is located downstream from an initial location, wherein said fluid condition attribute at said subsequent location is affected by one or more intermediate streams flowing into said subsequent location; a subsequent RTU communicatively coupled to said subsequent sensor and has stored therein a subsequent flow model, which is a synchronized machine-learning model designed to estimate said fluid condition attribute at said subsequent location, as a function of time, wherein said subsequent RTU is designed to produce, for a climate event, an RTU estimated range of subsequent values based upon said climate event forecast and said subsequent values, and wherein said subsequent RTU is designed to convey said subsequent values if said subsequent values are not within at least one of said RTU estimated range of subsequent values; multiple intermediate sensors, at least one of which is disposed at or near and measures said fluid condition attribute at said one location of a first route to produce intermediate values of said first intermediate sensor, and at least another of said multiple intermediate sensors is disposed at or near one location of a second route and measures said fluid condition attribute at said one location of a second route to produce intermediate values of said second intermediate sensor, wherein each of said first route and said second route facilitate fluid communication between said initial location and said subsequent location, and said second route is different from said first route, and wherein each of said one location of said first route, said one location of said second route, and said subsequent location is a constraint location in infrastructure as measurement of said fluid condition attribute at each of said one location of said first route, said one location of said second route, and said subsequent location, during said climate event and at least partially due to receiving fluid flow from multiple intermediate streams, are capable of reaching or exceeding a predetermined tolerable thresholdattribute value assigned to each of said one location of said first route, said one location of said second route, and said subsequent location, respectively; multiple intermediate RTUs, at least two of which are communicatively coupled to two or more of said intermediate sensors and at least one of which has stored therein one flow model, which is a synchronized machine-learning model designed to generate an RTU estimated range of intermediate value for said one location of said first route, as a function of time, and at least another of said multiple intermediate RTUs has stored therein another flow model, which is a synchronized machine-learning model designed to generate, as a function of time, an additional RTU estimated range of intermediate values for said one location of said second route, and wherein at least one said RTUs is designed to convey one or more of said intermediate values, if one or more of said intermediate values is not within said RTU estimated range of intermediate value for said one location of said first route, and at least another of said multiple intermediate RTUs is designed to convey one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional RTU estimated range of intermediate values for said one location of said second route; a server designed for communicatively coupling with said subsequent RTU and one or more of said intermediate RTUs and having stored therein a digital twin of each of said subsequent flow model, said one flow model, and another flow model wherein said digital twin of each of said subsequent flow model, said one flow model and another flow model is substantially similar to said subsequent flow model, said one flow model and said another flow model stored on said subsequent RTU, one of said intermediate RTUs, and another of said RTUs, respectively, wherein said server is designed to estimate, for said climate event and based upon said climate event forecast and said subsequent values, said intermediate values, and said additional intermediate values, said fluid condition attribute at said subsequent location, said one location of said first route, and said one location of said second route, respectively, to provide a server estimated range of subsequent values, a server estimated range of intermediate values, and an additional server estimated range of intermediate values, and said server is designed to receive from receive from said subsequent RTU said subsequent values, if said subsequent values are not within said RTU estimated range ofsubsequent values, and receive from said intermediate RTU one or more of said intermediate values, if said intermediate values are not within said RTU estimated range of intermediate values, and receive from said another intermediate RTU said additional intermediate values, if said additional intermediate values are not within said additional RTU estimated range of intermediate values and said server is designed to convey those of said subsequent values, said intermediate values and said additional intermediate values that are not within said server estimates range of subsequent values, said server estimates range of intermediate values, and said additional server estimates range of intermediate values, respectively; one or more flow controllers communicatively coupled to receive from said server, in real-time, said subsequent values or said server estimated range of subsequent values, said intermediate values or said server estimates range of intermediate values, and said additional intermediate values or said additional server estimates range of intermediate values, and one of said flow controllers is programmed to determine, in real-time, a stress value or an estimated stress value for each of said subsequent location, said one location of said first route, and said one location of said second route, respectively, based upon said subsequent values or said server estimated range of subsequent values, said intermediate values of said server estimates range of intermediate values, and said additional intermediate values or said additional server estimates range of intermediate values; and one or more flow-distributing components disposed at one or more fluid flow intersections, which are located downstream from and in fluid communication through an initial route with said initial location, such that fluid flow exiting said initial location flows through said initial route into one or more of said flow-distributing components, wherein each of said fluid flow intersections represents an intersection of said first route and said second route, and at least one of said flow-distributing components, based upon one or more of said flow distributing strategies received from one or more of said flow controllers during said climate event and in real time, redistributes fluid flow through at least one of said fluid flow intersections and between said first route and said second route to effectively modify said stress value or said estimated stress value obtained forat least one of said constraint locations to be below said predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

34. The real-time infrastructure management system of claim 33, wherein one or more of said flow controllers programmed to implement the following instructions: determining a route stress value for each of said first route and said second route by adding said stress value or said estimated stress value for each of said constraint locations present along said first route to produce a first route stress value or an estimated first route stress value, and adding said stress value or said estimated stress value for each of said constraint locations present along said second route to produce a second route stress value or an estimated second route stress value; identifying which one of said first route stress value or said estimated first route stress value, and said second route stress value or said estimated second route stress value has highest magnitude to provide a highest stress route value; and redistributing, using one or more of said flow redistributing strategies, fluid flow through at least one of said fluid flow intersections and between said first route and said second route to effectively reduce magnitude of said highest stress route value.

35. The real-time infrastructure management system of claim 34, wherein said first route stress value or said estimated first route stress value represents a sum of said stress value or said estimated stress value for each of said subsequent location and said one location of said first route , and said second route stress value or said estimated second route stress value represents a sum of said stress value or said estimated stress value for each of said subsequent location and said one location of said second route.

36. A real-time method of infrastructure management, said method comprising: obtaining, at one or more fluid flow controllers, initial values using an initial sensor disposed at or near and measuring a fluid condition attribute at an initial location; obtaining, at one or more of said fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring said fluid condition attribute at said subsequent location, and wherein said subsequent sensor is located downstream from said initial sensor;obtaining, at one or more of said fluid flow controllers, one or more intermediate values using one or more intermediate sensors, at least one of which is disposed at or near and measuring fluid flowing in or stored at one location of a first route providing fluid communication between said initial location and said subsequent location; determining, in real time and using one or more of said fluid flow controllers, a stress value at each of said initial location, said one location on said first route and said subsequent location based upon said initial values, one or more of said intermediate values and said subsequent values, respectively, to produce an initial route stress value and a first route stress value and identifying which one of said initial route stress value and said first route stress value is of highest magnitude and arriving at a highest stress route value, wherein said initial route stress value represents said stress value of at least said initial location, and said first route stress value represents a sum of said stress values at each of at least said one location on said first route and said subsequent location; and redistributing fluid flow, during a climate event, in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, in said initial route and said first route to effectively reduce magnitude of said highest stress route value, wherein one or more of said flow-distributing components being disposed at one or more fluid flow intersections, each of which is located downstream from said initial location such that fluid flow exiting said initial location flows through said initial route into one or more of said flow-distributing components and each of said fluid flow intersections intersects said initial route and said first route, and wherein one or more of said flow-distributing components are communicatively coupled to one or more of said fluid flow controllers.

37. The real-time method of infrastructure management of claim 36, wherein each of said initial location, said one location of said first route and said subsequent location is a constraint location in infrastructure as measurement of fluid condition attribute at said constraint location, during said climate event, are capable of reaching or exceeding, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

38. The real time method of managing infrastructure of claim 36, wherein said redistributing fluid flow includes implementing, during a big storm event, one of said flow redistributing strategy that reduces said stress value of at least one of said constraint locations to be equal to or below a relatively low predetermined tolerable threshold attribute value.

39. The real time method of managing infrastructure of claim 36, wherein said redistributing fluid flow includes implementing, during a small storm event, one of said flow redistributing strategy that reduces said stress value of at least one of said constraint locations to be equal to or below a relatively high predetermined tolerable threshold attribute value.

40. The real time method of managing infrastructure of claim 36, wherein said redistributing fluid flow includes replacing, during said climate event, implementation of one flow redistributing strategy with another flow distributing strategy.41 . The real-time method of infrastructure management of claim 40, wherein in said redistributing fluid flow, when a small storm event evolves to a big storm event, said one flow redistributing strategy modifies fluid condition attribute through at least one of said constraint locations such that said stress value of at least one of said constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations, and wherein said another flow distributing strategy modifies fluid condition attribute through at least one of said constraint locations such that said stress value of at least one of said constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

42. The real-time method of infrastructure management of claim 40, wherein in said redistributing fluid flow, when instead of a big storm event a small storm is realized, said one flow redistributing strategy modifies fluid condition attribute through at least one of said constraint locations such that said stress value of at least one of said constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations, and wherein said another flow distributing strategy modifies fluid condition attribute through at least one of said constraint locations such that said stress value of at least one of said constraintlocations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

43. The real-time method of infrastructure management of claim 36, wherein said redistributing fluid flow effectively modifies fluid flow through one of said flow-distribution components such that said stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first flow route and / or said stress value obtained at said initial location below a predetermined tolerable threshold attribute value that is assigned to said initial location.

44. The real-time method of infrastructure management of claim 36, wherein said redistributing includes reducing a combination of said stress value, which represents a summation of stress values for each of said initial location and said one location on said first route, to a reduced combination of stress values of said initial location and said one location of said first route, such that in said combined reduced stress values of said initial location and said one location of said first route, said stress value of said initial location is reduced and said stress value of said one location of said first route is increased and within a predetermined tolerable threshold level, or said stress value of said one location of said first route is reduced and said stress value of said initial location is increased and within said predetermined tolerable threshold level.

45. The real-time method of managing said infrastructure of claim 36, wherein said obtaining one or more intermediate fluid condition attribute measurement values includes obtaining multiple intermediate values using multiple intermediate sensors, at least another of which is disposed at or near and measuring fluid condition attribute at one location of a second route, providing fluid communication between said initial location and said subsequent location, to produce additional intermediate values; wherein said determining includes producing a second route stress value, which represents a sum of at least a stress value for each of one location on said second route and said subsequent location, and wherein said stress value for said one location on said second route is based upon said additional intermediate values, and said determining includes identifying which one of said initial route stress value, said firstroute stress value and said second route stress value has highest magnitude to arrive at a highest stress route value; and wherein said redistributing includes redistributing fluid flow, based upon one or more of said flow redistributing strategies, in one route chosen from a group comprising said initial route, said first route and said second route to effectively reduce magnitude of said highest stress route value.

46. The real-time method of infrastructure management of claim 45, wherein each of said initial location, said one location on said first route, said one location on said second route, and said subsequent location is a constraint location in infrastructure as measurement of fluid condition attribute at said constraint location, during said climate event, is capable of driving a stress value of said constraint location to reach or exceed, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

47. The real-time method of infrastructure management of claim 46, wherein said redistributing includes reducing a combination value of said stress value, which represents a summation of stress values for each of said constraint locations, to a reduced combination of stress values of said constraint locations, such that in said reduced combination of stress values of said constraint locations, said stress value of said initial location is reduced and said stress value for each of other constraint locations is increased and within a predetermined tolerable threshold level assigned to each of other said constraint locations, or said stress value of said one location of said first route is reduced and said stress value for each of other constraint locations is increased and within a predetermined tolerable threshold level assigned to each of other said constraint locations, or said stress value of said one location of said second route is reduced and said stress value for each of other constraint locations is increased and within a predetermined tolerable threshold level assigned to each of other said constraint locations.

48. The real time method of managing infrastructure of claim 46, wherein said redistributing fluid flow includes replacing, during said climate event, implementation of one flow redistributing strategy with another flow distributing strategy.

49. The real time method of managing infrastructure of claim 45, wherein, in said redistributing, when a small storm evolves to a big storm, one flow redistribution strategy modifies fluid condition attribute through said initial route, said first route and said second route, such that said stress value for each of said initial location, said one location of said first route and said one location of said second route is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively, and wherein said another flow distributing strategy modifies fluid condition attribute through at least one of said initial route, said first route and said second route, such that said stress value for each of said initial location, said one location of said first route and said one location of said second route is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations; and wherein, in said redistributing when instead of a big storm a small storm is realized, said one flow redistribution strategy modifies fluid condition attribute through said initial route, said first route and said second route, such that said stress value for each of said initial location, said one location of said first route and said one location of said second route is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively, and wherein said another flow distributing strategy modifies fluid condition attribute through at least one of said initial route, said first route and said second route, such that said stress value for each of said initial location, said one location of said first route and said one location of said second route is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

50. A real-time method of infrastructure management, said method comprising: obtaining, at one or more of said fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring a fluid condition attribute at said subsequent location, and wherein said subsequent sensor is located downstream from an initial location;obtaining, at one or more of said fluid flow controllers, multiple intermediate values using multiple intermediate sensors, at least one of which is disposed at or near and measuring said fluid condition attribute at one location of a first route to produce one or more intermediate values and at least another of multiple intermediate sensors is disposed on and measuring said fluid condition attribute at one location of a second route to produce one or more additional intermediate values, wherein each of said first route and said second route providing fluid communication between said initial location and said subsequent location; determining, in real time and using one or more of said fluid flow controllers, a stress value at each of said one location on said first route, said one location of said second route and said subsequent location based upon one or more of said intermediate values, one or more of said additional intermediate values and said subsequent values, respectively, to produce a first route stress value and a second route stress value; identifying which one of said first route stress value and said second route stress value is of highest magnitude and generating a highest stress route value, wherein said first route stress value represents a summation of said stress value at each of said one location on said first route and said subsequent location and said second route stress value represents a summation of said stress values at each of said one location on said second route and said subsequent location; and redistributing fluid flow, during a climate event and in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, between said first route and said second route to effectively reduce magnitude of said highest stress route value, wherein one or more of said flowdistributing components being disposed at one or more fluid flow intersections, each of which is located downstream from said initial location such that fluid flow exiting said initial location flows through an initial route into one or more of said flow-distributing components and each of said fluid flow intersections intersects said first route and said second route, and wherein one or more of said flow-distributing components are communicatively coupled to one or more of said fluid flow controllers.51 . The real-time method of managing said infrastructure of claim 50, wherein said redistributing includes reducing fluid flow rate through said first route and / or through said second route.

52. The real-time method of managing said infrastructure of claim 50, wherein said fluid condition attribute values is at least one attribute chosen from a group comprising fluid flow rate, fluid height, fluid volume, hydraulic capacity, time of fluid retention, fluid storage capacity, and fluid quality.

53. The real-time method of managing said infrastructure of claim 50, wherein said determining and said redistributing does not include or is not based upon determining or establishing a cost function of flow inside said infrastructure.

54. The real-time method of managing said infrastructure of claim 50, wherein said determining and said redistributing does not include or is not based upon a cost function of realizing one or more potential outcomes of said infrastructure during said climate event.

55. The real-time method of managing said infrastructure of claim 50, wherein said determining does not include minimizing a difference between a cost function of realizing one or more potential outcomes of said infrastructure and a cost function of flow inside said infrastructure.

56. The real-time method of managing said infrastructure of claim 50, wherein said redistributing does not include redistributing said fluid flow at a fluid flow intersection location of a high-quality treatment scheme and a low-quality treatment scheme.

57. The real-time method of managing said infrastructure of claim 50, wherein said redistributing does not include redistributing for minimizing a difference between a cost function of realizing one or more potential outcomes of said fluid flow infrastructure and a cost function of flow inside said fluid flow infrastructure.

58. The real-time method of managing said infrastructure of claim 50, wherein said redistributing includes reducing from a combination of said stress values, which represents a summation of stress values for each of said one location of said first route and one location of said second route, to a reduced combination of stress values, such that in said reduced combination of stress values, said stress value of said one location on said first route is reduced and said stress value of said one location on said secondroute is increased and within a predetermined tolerable threshold level that is assigned to said one location on said second route, or said stress value of said one location on said second route is reduced and said stress value of said one location on said first route is increased and within a predetermined tolerable threshold level assigned to one location of said first route.

59. The real-time method of managing said infrastructure of claim 50, further comprising: comparing outcomes resulting from implementing, during said climate event, multiple of said infrastructure management strategies, wherein said comparing includes using one or more key point indicators as measure of success in reducing said stress value at said one location of said first route and said one location of said second route; determining, based on said comparing, one or more successful infrastructure management strategies that effectively reduce said stress value, during said climate event, at said one location of said first route and said one location of said second route below a predetermined tolerable threshold level assigned to each of said one location of said first route and said one location of said second route; and storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies.

60. A method of implementing infrastructure management strategies, said method comprising: obtaining, at one or more fluid flow controllers, initial values using an initial sensor disposed at or near and measuring a fluid condition attribute at an initial location; obtaining, at one or more of said fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring said fluid condition attribute at a subsequent location, and wherein said subsequent sensor is downstream from said initial sensor; obtaining one or more intermediate values using one or more intermediate sensors disposed at or near and measuring said fluid condition attribute at a one location of a first route providing fluid communication between said first location and said subsequent location;obtaining, based upon a climate event forecast and one or more of said intermediate values, one or more server estimated range of intermediate values using a server operating in conjunction with one or more of said intermediate sensors, and wherein said server is designed to receive said one or more of said intermediate values, and said server is communicatively coupled to one or more of said fluid flow controllers to convey said one or more server estimated intermediate values or one or more intermediate values, and said server conveys said intermediate values, if one or more of said intermediate values are not within said server estimated range of intermediate values; determining, in real time and using one or more of said fluid flow controllers, a stress value for each of said initial location and said subsequent location based upon said initial value and said subsequent value, and a stress value or an estimated stress value for said one location of said first route based upon or one or more of said intermediate values and one or more of said server estimated intermediate values, respectively, to produce an initial route stress value and a first route stress value or an estimated first route stress value; identifying which on of said initial route stress value, first route stress value and said estimated first route stress value is of highest magnitude and arriving at a highest stress route value, wherein said initial route stress value represents said stress value of at least said initial location, said first route stress value represents a summation of stress value for each of said one location of said first route and said subsequent location and said estimated first route stress value represents a summation of at least said estimated stress value of said one location of said first route and said stress value of said subsequent location; and formulating, based upon said highest flow stress value, multiple infrastructure management strategies that reduce said highest stress route value; comparing, using one or more key point indicators of success in reducing said highest flow stress value, each of said infrastructure management strategies to an outcome of said climate event; determining, based on said comparing using one or more of said key point indicators of success in reducing said highest flow stress value, one or more successfulinfrastructure management strategies that effectively reduce said highest flow stress value; and storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies.61 . The real-time method of implementing infrastructure management strategies of claim 60, further comprising: generating, using one or more intermediate remote telemetry units (“RTUs”) and based upon said climate event forecast and one or more of said intermediate values, an RTU estimated range of intermediate values; conveying, using one or more of said intermediate RTUs, one or more of said intermediate values from said one or more of said intermediate sensors to said server, if said one or more of said intermediate values are not within said RTU estimated range of intermediate values.

62. The real-time method of implementing infrastructure management strategies of claim 60, wherein each of said initial location, said one location of said first route and said subsequent location is a constraint location in infrastructure as a measurement at and / or a server estimated range of values for said constraint location, during said climate event, is capable of driving stress values or estimated stress values of said constraint locations to reach or exceed, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

63. The method of implementing managing infrastructure strategies of claim 60, further comprising: retrieving, during a subsequent climate event and from one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; and redistributing fluid flow, during said climate event, in real time, using one or more flow-distributing components, and based upon one or more of said successful infrastructure management strategies, between said initial route and said first route to effectively reduce magnitude of said highest stress route value, wherein one or more of said flow-distributing components being disposed at one or more fluid flow intersections,each of which is located downstream from said initial location such that fluid flow exiting said initial location flows through an initial route into one or more of said flow-distributing components and each of said fluid flow intersections intersects said initial route and said first route, and wherein one or more of said flow-distributing components are communicatively coupled to one or more of said fluid flow controllers.

64. The real-time method of implementing infrastructure management strategies of claim 63, wherein said redistributing includes implementing, during a small storm, one of said flow redistributing strategy that reduces said stress value and / or said estimated stress value for at least one of said constraint locations to be equal to or below a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

65. The real-time method of implementing infrastructure management strategies of claim 63, wherein said redistributing includes implementing, during a big storm, one of said flow redistributing strategy that reduces said stress value and / or said estimated stress value for at least one of said constraint locations to be equal to or below a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

66. The real-time method of implementing infrastructure management strategies of claim 63, wherein said redistributing includes replacing, during said climate event, implementation of one flow redistributing strategy with another flow distributing strategy.

67. The real-time method of implementing managing infrastructure strategies of claim 66, wherein, when a small storm evolves into a big storm, said one flow redistributing strategy modifies fluid condition attribute through said initial route and said first route such that said stress value and / or said estimated stress value for at least one of said constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations, and wherein said another flow distributing strategy modifies fluid condition attribute through said initial route and said first route such that said stress value and / or said estimated stress value for at least one of said constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

68. The real-time method of implementing managing infrastructure strategies of claim 66, wherein, when instead of a big storm a small storm is realized, said one flow redistributing strategy modifies fluid condition attribute through said initial route and said first route such that said stress value and / or said estimated stress value for at least one of said constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations, and wherein said another flow distributing strategy modifies fluid condition attribute through said initial route and said first route such that said stress value and / or said estimated stress value of at least one of said constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

69. The real-time method of implementing infrastructure management strategies of claim 63, wherein said redistributing effectively modifies fluid flow through one of said flow-distribution components such that said stress value and / or said estimated stress value for said one location of said first route to be below a predetermined tolerable threshold attribute value assigned to said one location of said first flow route and / or said stress value and / or said estimated stress value obtained at said initial location to be below a predetermined tolerable threshold attribute value that is assigned to said initial location.

70. The real-time method of implementing infrastructure management strategies of claim 63, wherein said redistributing includes reducing a combination of stress value, which represents a summation of stress value for said initial location and stress value or said estimated stress value for said one location on said first route, to a reduced combination of stress value, such that in said reduced combination of stress value, said stress value of said initial location is reduced and stress value or said estimated stress value for said one location of said first route is increased and within a predetermined tolerable threshold level assigned to one location of said first route, or said stress value or said estimated stress value of said one location of said first route is reduced and said stress value of said initial location is increased and within a predetermined tolerable threshold level assigned to said initial location.71 . The real-time method of implementing infrastructure management strategies of claim 60, wherein said obtaining one or more intermediate values using one or more intermediate sensors includes obtaining multiple intermediate values using multiple sensors, at least another of which is disposed at or near and measuring said fluid condition attribute at a one location of a second route to produce one or more additional intermediate values, said second route providing fluid communication between said first location and said subsequent location; wherein said obtaining one or more server estimated intermediate values includes obtaining one or more additional server estimated intermediate values using said server operating in conjunction with another of said intermediate sensors, and wherein said server, for said climate event and based upon said climate event forecast and one or more additional intermediate values, produces an additional server estimated range of intermediate values, and said server conveys to one or more of said fluid flow controllers one or more of said additional server estimated range of intermediate values or one or more of said additional intermediate values, and said server conveys one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said server estimated range of intermediate values; determining, in real time and using one or more of said fluid flow controllers, a stress value or an estimated stress value for said one location of said second route based upon one or more of said additional intermediate values or one or more of said additional server estimated intermediate values, respectively, to produce a stress value or an estimates stress value for said second route; identifying which one of said initial route stress value, said stress value or said estimated stress value for said first route and said stress value or said estimated stress value for said second route is of highest magnitude and arriving at a highest stress route value, wherein said initial route stress value represents said stress value of at least said initial location, said stress value or said estimated stress value for said first route represents a summation of at least said stress value or said estimated stress value for said one location of said first route and said stress value of said subsequentlocation, respectively, and said stress value or said estimated stress value for said second route represents a sum of at least said stress value or said estimated stress value for said one location of said second route and said stress value of said subsequent location, respectively.

72. The real-time method of implementing managing infrastructure strategies of claim 71 , wherein said obtaining one or more of said estimated intermediate values further comprising: generating, using one or more additional intermediate remote telemetry units (“RTUs”) and based upon said climate event forecast and one or more of said additional intermediate values, additional RTU estimated range of intermediate values; and conveying, using one or more of said additional intermediate RTUs, one or more of said additional intermediate values from said one or more of said additional intermediate sensors to said server, if said one or more of said additional intermediate values are not within at least one of said additional RTU estimated range of intermediate values.

73. The real-time method of implementing managing infrastructure strategies of claim 71 , further comprising: formulating, based upon said highest flow stress value, multiple infrastructure management strategies that reduce said highest stress route value; comparing, using one or more key point indicators of success in reducing said highest flow stress value, each of said infrastructure management strategies to an outcome of said climate event; determining, based on said comparing using one or more of said key point indicators of success in reducing said highest flow stress value, one or more successful infrastructure management strategies that effectively reduce said highest flow stress value; and storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies.

74. The real-time method of implementing managing infrastructure strategies of claim 71 , wherein each of said initial location, said one location of said first route, said one location of said second route and said subsequent location is deemed to be a constraintlocation in infrastructure as a measurement and / or an estimate of fluid condition at said constraint location, during said climate event, is capable of driving stress values or estimated stress values of said constraint locations to reach or exceed, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

75. The method of implementing managing infrastructure strategies of claim 71 , further comprising: retrieving, during a subsequent climate event and from one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; and redistributing fluid flow, during said climate event, in real time, using one or more flow-distributing components, and based upon one or more of said successful infrastructure management strategies, among said initial route, said first route and said second route to effectively reduce magnitude of said highest stress route value, wherein one or more of said flow-distributing components being disposed at one or more fluid flow intersections, each of which is located downstream from an initial location such that fluid flow exiting said initial location flows through said initial route into one or more of said flow-distributing components and each of said fluid flow intersections intersects said initial route, said first route and said second route, and wherein one or more of said flow-distributing components are communicatively coupled to one or more of said fluid flow controllers.

76. The real-time method of implementing infrastructure management strategies of claim 75, wherein said redistributing includes implementing, during a small storm event, one of said successful infrastructure management strategies that modify fluid condition attribute inside said initial route, said first route and said second route such that at least one of said stress value of said initial location, said stress value or said estimated stress value of said one location of said first route, and said stress value or said estimated stress value of said one location of said second route to be equal to or below a relatively high predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively.

77. The real-time method of implementing infrastructure management strategies of claim 75, wherein said redistributing includes implementing, during a big storm event, one of said successful infrastructure management strategies that modify fluid condition attribute inside said initial route, said first route and said second route such that at least one of said stress value of said initial location, said stress value or said estimated stress value of said one location of said first route, and said stress value or said estimated stress value of said one location of said second route to be equal to or below a relatively low predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively.

78. The real-time method of implementing infrastructure management strategies of claim 75, wherein said redistributing effectively modifies fluid flow through one of said flow-distribution components to produce at least one reduced stress condition selected from a group comprising said stress value or said estimated stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first flow route, said stress value or said estimated stress value obtained at said one location of said second route is below a predetermined tolerable threshold attribute value that is assigned to said one location of said second flow route and said stress value obtained at said initial location below a predetermined tolerable threshold attribute value that is assigned to said initial location.

79. The real-time method of implementing infrastructure management strategies of claim 75, wherein said redistributing includes reducing, based on one or more of said flow redistributing strategies, one route stress value chosen from a group comprising said initial route stress value, said stress value or said estimated stress value for said first route and said stress value or said estimated stress value for said second route.

80. The real-time method of implementing infrastructure management strategies of claim 75, wherein each of said initial location, said one location on said first route, one location on said second route, and said subsequent location is a constraint location in infrastructure as a measurement and / or an estimate of fluid condition attribute at said constraint location, during said climate event, is capable of driving stress values orestimated stress values of said constraint locations to reach or exceed, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location, and wherein said redistributing includes reducing a combination of stress value, which represents a summation of stress value for said initial location and stress value or said estimated stress value for each of said one location on said first route and said one location of said second route, to a reduced combination of stress value, such that in said reduced combination of stress value, said stress value of said initial location is reduced and stress value or said estimated stress value for at least one of said one location of said first route and said one location of said second route is increased and within a predetermined tolerable threshold level assigned to one location of said first route and one location of said second route, respectively, or said stress value or said estimated stress value of said one location of said first route is reduced and at least one of said stress value of said initial location and stress value or said estimated stress value for at least one of said one location of said second route is increased and within a predetermined tolerable threshold level assigned to said initial location and said one location of said second route, respectively, or said stress value or said estimated stress value of said one location of said second route is reduced and at least one of said stress value of said initial location and stress value or said estimated stress value for at least one of said one location of said first route is increased and within a predetermined tolerable threshold level assigned to said initial location and said one location of said first route, respectively.81 . A real-time method of infrastructure management, said method comprising: obtaining, at one or more of said fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring said fluid condition attribute at a subsequent location, and wherein said subsequent sensor is located downstream from an initial location; obtaining multiple intermediate values using multiple intermediate sensors, at least one of which is disposed at or near and measuring said fluid condition attribute at a one location of a first route to produce one or more intermediate value, and another of said multiple intermediate sensors is disposed at or near and measuring said fluidcondition attribute at a one iocation of a second route to produce one or more additional intermediate values, wherein each of said first route and said second route provide fluid communication between said first location and said subsequent location; obtaining, based upon a climate event forecast and one or more of said intermediate values, one or more server estimated range of intermediate values using a server operating in conjunction with at least one of said intermediate sensors, obtaining, at one or more of said fluid flow controllers and based upon said climate event forecast and one or more of said additional intermediate values, one or more additional server estimated range of intermediate values using said server operating in conjunction with at least another of said intermediate sensors, and wherein said server is designed to receive one or more of said intermediate values and one or more of said additional intermediate values, and said server is communicatively coupled to convey to one or more of said fluid flow controllers one or more of said intermediate values or one or more said server estimated range of intermediate values and one or more of said additional intermediate values or one or more said additional server estimated intermediate values, and said server conveys one or more of said intermediate values, if one or more of said intermediate values are not within said server estimated range of intermediate values and conveys one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional server estimated range of intermediate values; determining, in real time and using one or more of said fluid flow controllers, a stress value of said subsequent location, and a stress value or an estimated stress value for each of said one location of said first route and said one location of said second route based upon one or more of said subsequent values, one or more of said intermediate values or one or more of said server estimated range of intermediate values, one or more of said additional intermediate values or one or more of said additional server estimated range of intermediate values, respectively, and based upon said stress value or said estimated stress value for each of said one location of said first route and said one location of said second route, producing a stress value or an estimated stress value for each of said first route and said second route;identifying which one of said stress value or said estimated stress value for said first route and said stress value or said estimated stress value for said second route is of highest magnitude and arriving at a highest stress route value, wherein said stress value or said estimated stress value for said first route represents a summation of at least said stress value or said estimated stress value for said one location of said first route and said stress value of said subsequent location, respectively, and said stress value or said estimated stress value for said second route represents a summation of at least said stress value or said estimated stress value for said one location of said second route and said stress value of said subsequent location, respectively; redistributing fluid flow, during said climate event and in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, between said first route and said second route to effectively reduce magnitude of said highest stress route value, wherein one or more of said flowdistributing components being disposed at one or more fluid flow intersections, each of which is located downstream from said initial location such that fluid flow exiting said initial location flows through an initial route into one or more of said flow-distributing components and each of said fluid flow intersections intersects said first route and said second route, and wherein one or more of said flow-distributing components are communicatively coupled to one or more of said fluid flow controllers.

82. The real-time method of implementing managing infrastructure strategies of claim 81 , wherein said obtaining one or more of said server estimated intermediate values and one or more of said additional server estimated intermediate values further comprising: generating, using one or more intermediate remote telemetry units (“RTUs”) and additional intermediate RTUs and based upon said climate event forecast, one or more of said intermediate values and one or more of said additional intermediate values, at least one RTU estimated range of intermediate values and at least one additional RTU estimated range of intermediate values, respectively; conveying, using one or more of said intermediate RTUs, one or more of said intermediate values from one or more of said intermediate sensors to said server, if saidone or more of said intermediate values are not within at least one of said RTU estimated range of intermediate values; and conveying, using one or more of said additional intermediate RTUs, one or more of said additional intermediate values from said one or more of said additional intermediate sensors to said server, if said one or more of said additional intermediate values are not within at least one of said additional RTU estimated range of intermediate values.

83. The real-time method of implementing managing infrastructure strategies of claim 81 , wherein said redistributing includes reducing fluid flow rate through said first route and / or through said second route.

84. A method of implementing infrastructure strategies, said method comprising: obtaining, based upon initial values and a climate event forecast, a server estimated range of initial values using a server operating in conjunction with one or more initial sensors, at least one of which is disposed at or near and measures a fluid condition attribute at an initial location to produce said initial values, and wherein said server is communicatively coupled to convey to one or more of said fluid flow controllers said initial values or said server estimated range of initial values, and server conveys said initial values, if said initial values are not within said server estimated range of initial values, obtaining, at one or more of said fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measures said fluid condition attribute at said subsequent location, and wherein said subsequent sensor is downstream from said initial sensor; obtaining, based upon a climate event forecast and intermediate values, a server estimated range of intermediate values using a server operating in conjunction with one or more intermediate sensors, at least one of which is disposed at or near and measures a fluid condition attribute at a location on a first route to produce said intermediate values, and wherein said server is communicatively coupled to convey to one or more of said fluid flow controllers said intermediate values or said server estimated range of intermediate values, and server conveys said intermediate values, if said intermediate values are not within said server estimated range of intermediatevalues, and wherein said first route provides fluid communication between said initial location and said subsequent location; determining, at one or more of said fluid flow controllers, a stress value for said subsequent location based upon said subsequent values and a stress value or an estimated stress value for each of said initial location and said one location of said first route based upon said initial values or said server estimated range of initial values, and one or more of said intermediate values or said server estimated range of intermediate values, respectively; and formulating, based upon said stress value for said subsequent location and said stress value or said estimated stress value for each of said initial location and said one location of said first route, one or more infrastructure management strategies that reduce said stress value or said estimated stress value at said initial location and / or said stress value or estimated stress value at said one location of said first route; comparing each of said infrastructure management strategies to an outcome of said climate event using one or more key point indicators of success in reducing said stress value or said estimated stress value at said initial location and / or said stress value or said estimated stress value at said one location of said first route; determining, based upon said comparing using one or more of said key point indicators of success in reducing said stress value or said estimated stress value at said initial location and / or said stress value or said estimated stress value at said one location of said first route, one or more successful infrastructure management strategies that effectively reduce said stress value or said estimated stress value at said initial location and / or stress value or said estimated stress value at said one location of said first route; and storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; retrieving, during a subsequent climate event and from one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; and redistributing fluid flow between said initial route and said first route, using one or more of said successful infrastructure management strategies, to effectively reducestress at said initial location and / or at said one location of said first route during said subsequent climate event, wherein said redistributing is carried out using one or more flow-distributing components disposed at one or more flow intersections, each being downstream from said initial location such that fluid flow exiting said initial location flows through an initial route into one or more of said flow-distributing components and each of said fluid flow intersection location intersects said initial route and said first route.

85. The method of implementing infrastructure strategies of claim 84, wherein each of said initial location, said one location of said first route and said subsequent location is a constraint location in infrastructure as a measurement and / or an estimated value of fluid condition attribute at or near said constraint location, during said climate event, is capable of driving stress values or estimated stress values of said constraint locations to reach or exceed, at least partially due to excessive fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

86. The method of implementing infrastructure strategies of claim 85, wherein said redistributing includes implementing, during a small storm, one of said successful infrastructure management strategies that modify fluid condition attribute inside said initial route, said first route and said second route such that at least one of said stress value of said initial location, said stress value or said estimated stress value of said one location of said first route, and said stress value or said estimated stress value of said one location of said second route to be equal to or below a relatively high predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively.

87. The real-time method of implementing infrastructure management strategies of claim 85, wherein said redistributing includes implementing, during a big storm, one of said successful infrastructure management strategies that modify fluid condition attribute inside said initial route, said first route and said second route such that at least one of said stress value of said initial location, said stress value or said estimated stress value of said one location of said first route, and said stress value or said estimated stress value of said one location of said second route to be equal to or below a relativelylow predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively.

87. The method of implementing infrastructure strategies of claim 85, wherein said redistributing includes implementing, during a big storm, one of said flow redistributing strategy that reduces said stress value and / or said estimated stress value of fluid condition attribute at or near at least one of said constraint locations to be equal to or below a relatively low predetermined tolerable threshold attribute value assigned to said constraint location.

88. The method of implementing infrastructure strategies of 84, wherein said redistributing includes replacing, during said climate event, implementation of one successful infrastructure management strategy with another successful infrastructure management strategy.

89. The method of implementing infrastructure strategies of 88, wherein, when a small storm evolves into a big storm, said one successful infrastructure management strategy modifies fluid condition attribute at or near at least one of said constraint locations such that said stress value and / or said estimated stress value of at least one of said constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations, and wherein said another successful infrastructure management strategy modifies fluid condition attribute at or near at least one of said constraint locations such that said stress value and / or said estimated stress value of at least one of said constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.

90. The method of implementing infrastructure strategies of 88, wherein, when instead of a big storm a small storm is realized, said one successful infrastructure management strategy modifies fluid condition attribute at or near at least one of said constraint locations such that said stress value and / or said estimated stress value of at least one of said constraint locations is equal to or lower than a relatively low predetermined tolerable threshold attribute value assigned to at least one of said constraint locations, and wherein said another successful infrastructure managementstrategy modifies fluid condition attribute at or near at least one of said constraint locations such that said stress value and / or said estimated stress value of at least one of said constraint locations is equal to or lower than a relatively high predetermined tolerable threshold attribute value assigned to at least one of said constraint locations.91 . The method of implementing infrastructure strategies of claim 84, wherein said redistributing effectively modifies fluid flow through one of said flow-distribution components such that said fluid condition attribute at or near at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first flow route and / or said fluid condition attribute at or near said initial location to be below a predetermined tolerable threshold attribute value that is assigned to said initial location.

92. The method of implementing infrastructure strategies of claim 84, wherein said redistributing includes reducing a combination of said stress value or said estimated stress value of each of said initial location and said one location on said first route to generate a combined reduced estimated stress values of said initial location and said one location of said first route, such that in said combined reduced estimated stress values of said initial location and said one location of said first route, said stress value or said estimated stress value of said initial location is reduced and said stress value or said estimated stress value of said one location of said first route is increased and said fluid condition attribute at or near said one location of said first route is within a predetermined tolerable threshold level that is assigned to said one location of said first route, or said estimated stress value of said one location of said first route is reduced and said stress value or said estimated stress value of said initial location is increased and said fluid condition attribute at or near said initial location is within said predetermined tolerable threshold level that is assigned to said initial location.

93. The method of implementing infrastructure strategies of claim 84, wherein said obtaining one or more of said server estimated intermediate values includes obtaining additional server estimated range of intermediate values using one or more additional intermediate sensors, at least one of which is disposed at or near and measures said fluid condition attribute at one location of a second route to produce one or more additional intermediate values, wherein said second route provides fluidcommunication between said initial location and said subsequent location, and wherein said obtaining said additional server estimated range of intermediate values is based upon said climate event and said additional intermediate values, and are produced using one or more of said additional intermediate sensors operating in conjunction with said server, and said server conveys to one or more of said fluid flow controllers one or more of said additional server estimated range of intermediate values or said additional intermediate values, and said server conveys said additional intermediate values, if one or more of said additional intermediate values are not within said one or more of said additional server estimated range of intermediate values ; wherein said determining includes producing a stress value or an estimated stress value for said one location on said second route based upon one or more of said additional intermediate values or one or more of said additional server estimated range of intermediate values, and said formulating, based upon said stress value for said subsequent location and said stress value or said estimated stress value for each of said initial location, said one location of said first route and said one location of said second route, one or more of said infrastructure management strategies; wherein said redistributing includes redistributing fluid flow, based upon one or more of said infrastructure management strategies, in at least one route chosen from a group comprising said initial route, said first route and said second route to effectively reduce magnitude of said highest stress route value.

94. The method of implementing infrastructure strategies of claim 93, wherein said obtaining one or more of said server estimated intermediate values and one or more of said additional server estimated intermediate values further comprising: generating, using one or more intermediate remote telemetry units (“RTUs”) and additional intermediate RTUs and based upon said climate event forecast, one or more of said intermediate values and one or more of said additional intermediate values, an RTU estimated range of intermediate values and an additional RTU estimated range of intermediate values, respectively; conveying, using one or more of said intermediate RTUs and additional intermediate RTUs, one or more of said intermediate values from one or more of said intermediate sensors to said server, if said one or more of said intermediate values arenot within at least one of said RTU estimated range of intermediate values, and conveying, using one or more of said additional intermediate RTUs, one or more of said additional intermediate values from said one or more of said additional intermediate sensors to said server, if said one or more of said additional intermediate values are not within at least one of said additional RTU estimated range of intermediate values.

95. The method of implementing infrastructure strategies of claim 93, wherein said redistributing includes implementing, during a small storm, one of said flow redistributing strategy that reduces said stress value or said estimated stress value of at least one of said initial location, said one location of said first route and said one location of said second route to be equal to or below a relatively high predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively.

96. The method of implementing infrastructure strategies of claim 93, wherein said redistributing includes implementing, during a big storm, one of said flow redistributing strategy that reduces said stress value or said estimated stress value of at least one of said initial location, said one location of said first route and said one location of said second route to be equal to or below a relatively low predetermined tolerable threshold attribute value assigned to each of said initial location, said one location of said first route and said one location of said second route, respectively.

97. The method of implementing infrastructure strategies of claim 93, wherein said redistributing effectively modifies fluid flow through one of said flow-distribution components such that said stress value or said estimated stress value obtained at said one location of said first route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said first flow route and / or said stress value or said estimated stress value obtained at said one location of said second route to be below a predetermined tolerable threshold attribute value that is assigned to said one location of said second route and / or said estimated stress value obtained at said initial location below a predetermined tolerable threshold attribute value that is assigned to said initial location.

98. The method of implementing infrastructure strategies of claim 93, wherein each of said initial location, said one location on said first route, one location on said secondroute, and said subsequent location is a constraint location in infrastructure as a measurement and / or an estimate of fluid condition attribute at said constraint location, during said climate event, is capable of driving stress values or estimated stress values to reach or exceed, at least partially due to excessive fluid flow into said constraint location from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location.

99. A method of implementing infrastructure strategies, said method comprising: obtaining, at one or more of fluid flow controllers, subsequent values using a subsequent sensor disposed at or near and measuring said fluid condition attribute at a subsequent location, and wherein said subsequent sensor is downstream from an initial location; obtaining multiple intermediate values using multiple intermediate sensors, at least one of which is disposed at or near and measuring said fluid condition attribute at a one location of a first route to produce one or more intermediate value, and another of said multiple intermediate sensors is disposed at or near and measuring said fluid condition attribute at a one location of a second route to produce one or more additional intermediate values, wherein each of said first route and said second route provide fluid communication between said first location and said subsequent location; obtaining, based upon a climate event forecast and one or more of said intermediate values, one or more server estimated range of intermediate values using a server operating in conjunction with at least one of said intermediate sensors, obtaining, at one or more of said fluid flow controllers and based upon said climate event forecast and one or more of said additional intermediate values, one or more additional server estimated range of intermediate values using said server operating in conjunction with at least another of said intermediate sensors, and wherein said server is designed to receive one or more of said intermediate values and one or more of said additional intermediate values, and said server is communicatively coupled to convey to one or more of said fluid flow controllers one or more of said intermediate values or one or more said server estimated range of intermediate values and one or more of said additional intermediate values or one or more said additional server estimated intermediate values, and said server conveys one or more of said intermediate values, ifone or more of said intermediate values are not within said server estimated range of intermediate values and conveys one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional server estimated range of intermediate values; determining, in real time and using one or more of said fluid flow controllers, a stress value of said subsequent location, and a stress value or an estimated stress value for each of said one location of said first route and said one location of said second route based upon one or more of said subsequent values, one or more of said intermediate values or one or more of said server estimated range of intermediate values, one or more of said additional intermediate values or one or more of said additional server estimated range of intermediate values, respectively, and based upon said stress value or said estimated stress value for each of said one location of said first route and said one location of said second route, producing a stress value or an estimated stress value for each of said first route and said second route; identifying which one of said stress value or said estimated stress value for said first route and said stress value or said estimated stress value for said second route is of highest magnitude and arriving at a highest stress route value, wherein said stress value or said estimated stress value for said first route represents a summation of at least said stress value or said estimated stress value for said one location of said first route and said stress value of said subsequent location, respectively, and said stress value or said estimated stress value for said second route represents a summation of at least said stress value or said estimated stress value for said one location of said second route and said stress value of said subsequent location, respectively; redistributing fluid flow, during said climate event and in real time, using one or more flow-distributing components, and based upon one or more flow redistributing strategies, between said first route and said second route to effectively reduce magnitude of said highest stress route value, wherein one or more of said flowdistributing components being disposed at one or more fluid flow intersections, each of which is located downstream from said initial location such that fluid flow exiting said initial location flows through an initial route into one or more of said flow-distributing components and each of said fluid flow intersections intersects said first route and saidsecond route, and wherein one or more of said flow-distributing components are communicatively coupled to one or more of said fluid flow controllers; determining, based upon said comparing using one or more of said key point indicators of success in reducing said stress value or said estimated stress value of each of said first route and said second route or in reducing said stress value or said estimated stress value at each of said one location of said first route and / or one location of said second route, one or more successful infrastructure management strategies; and storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies.

100. The method of implementing infrastructure strategies of claim 99, wherein said redistributing includes reducing fluid flow rate through said first route and / or through said second route, and said method further comprising: retrieving, during a subsequent climate event and from one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; and redistributing, during said subsequent climate event, fluid flow between said first route and said second route, using one or more of said successful infrastructure management strategies, to effectively reduce stress along said first route and / or said second route and thereby reduce said stress value or said estimated stress value at each of said one location of said first route and / or said one location of said second route.

101. The method of implementing infrastructure strategies of claim 99, wherein said fluid condition attribute values is at least one attribute chosen from a group comprising fluid flow rate, fluid height, fluid volume, hydraulic capacity, time of fluid retention, storage capacity, and fluid quality.

102. The method of implementing infrastructure strategies of claim 99, wherein said determining and said redistributing does not include or is not based upon determining or establishing a cost function of flow inside said infrastructure.

103. The method of implementing infrastructure strategies of claim 99, wherein said determining and said redistributing does not include or is not based upon a cost functionof realizing one or more potential outcomes of said infrastructure during said climate event.

104. The method of implementing infrastructure strategies of claim 99, wherein said determining does not include minimizing a difference between a cost function of realizing one or more potential outcomes of said infrastructure and a cost function of flow inside said infrastructure.

105. The method of implementing infrastructure strategies of claim 99, wherein said redistributing does not include redistributing said fluid flow at a fluid flow intersection location of a high-quality treatment scheme and a low-quality treatment scheme.

106. The method of implementing infrastructure strategies of claim 99, wherein said redistributing does not include redistributing for minimizing a difference between a cost function of realizing one or more potential outcomes of said fluid flow infrastructure and a cost function of flow inside said fluid flow infrastructure.

107. The method of implementing infrastructure strategies of claim 99, wherein in said redistributing does not include redistributing for minimizing a difference between a cost function of realizing one or more potential outcomes of said fluid flow infrastructure and a cost function of flow inside said fluid flow infrastructure.

108. The method of implementing infrastructure strategies of claim 99, wherein said redistributing includes reducing from a combination value of said stress values, which represents a summation of said stress values or said estimated stress values for each or each of said one location on said first route and said one location on said second route, to produce a reduced combination of stress values, such that in said reduced combination of stress values, said stress value or said estimated stress value for said one location on said first route is reduced and said stress value or said estimated stress value for said one location on said second route is increased and within a predetermined tolerable threshold level that is assigned to said one location of said second route, or said stress value or said estimated stress value for said one location on said second route is reduced and said stress value or said estimated stress value for said one location on said first route is increased and within said predetermined tolerable threshold level assigned to said one location of said first route.

109. A method of implementing infrastructure strategies, said method comprising:obtaining, based upon initial values and a climate event forecast, a server estimated range of initial values using a server operating in conjunction with one or more initial sensors, at least one of which is disposed at or near and measuring a fluid condition attribute at an initial location to produce said initial values, and wherein said server is communicatively coupled to and conveys to one or more of said fluid flow controllers said initial values or said server estimated range of initial values, and said server conveys said initial values, if said initial values are not within said server estimated range of initial values; obtaining, based upon subsequent values and said climate event forecast, a server estimated range of subsequent values using said server operating in conjunction with one or more subsequent sensors, at least one of which is disposed at or near and measuring a fluid condition attribute at a subsequent location to produce said subsequent values, and wherein said server conveys said subsequent values or said server estimated range of subsequent values, and said server conveys said subsequent values, if said subsequent values are not within server estimated range of subsequent values: obtaining, based upon said climate event forecast and one or more intermediate values, one or more server estimated intermediate range of values using said server operating in conjunction with one or more intermediate sensors, at least one of which is disposed at one location on a first route providing fluid communication between said initial location and said subsequent location, wherein at least one of said intermediate sensors measures said fluid condition attribute at said one location of said first route to produce one or more of said intermediate values, and wherein said server conveys said intermediate values or one or more of said server estimated intermediate range of values to one or more of said fluid flow controllers, and said server conveys said intermediate values, if said intermediate values are not within one or more of said server estimated intermediate range of values; determining a stress value or an estimated stress value for each of said initial location, said one location of said first route and said subsequent location based upon said initial values or said server estimated range of initial values, one or more of said intermediate values or one or more of said server estimated range of intermediatevalues, and said subsequent values or one or more of said server estimated range of subsequent values, respectively, wherein said determining includes using one or more of said fluid flow controllers, and wherein each of said initial location, said one location of said first route and said subsequent location is a constraint location in infrastructure as a measurement or an estimate of fluid condition attribute at or near said constraint location, during said climate event, is capable of driving stress values or estimates stress values of said constraint location to reach or exceed, at least partially due to receiving fluid flow from multiple intermediate streams, a predetermined tolerable threshold attribute value assigned to said constraint location; establishing a stress value or an estimated route stress value for each of said initial route and said first route by adding said stress values or said estimated stress values for constraint locations present along each of said initial route and said first route to produce an initial route stress value or an estimated initial route stress value and a first route stress value or an estimated first route stress value; identifying which one of said initial route stress value or said estimated initial route stress value and said first route stress value or said estimated first route stress value has highest magnitude to arrive at least one highest stress route value; redistributing, during said climate event, in real time and based upon one of said flow redistributing strategies, fluid flow in said initial route and / or said first route, that effectively reduces magnitude of at least one of said highest stress route value.

110. The method of implementing infrastructure strategies of claim 109, said method comprising: formulating, based upon said stress value or said estimated stress value for each of said initial location, said one location of said first route, and said subsequent location, multiple infrastructure management strategies that reduce said initial route stress value or said estimated initial route stress value and / or said first route stress value or said estimated first route stress value; comparing, using one or more key point indicators of success in reducing said initial route stress value or said estimated initial route stress value and / or said first route stress value or said estimated first route stress value, each of said infrastructure management strategies to an outcome of said climate event;determining, based on said comparing using one or more of said key point indicators of success in reducing said estimated initial route stress value and / or said estimated first route stress value, one or more successful infrastructure management strategies that effectively reduce said highest stress value. storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; retrieving, during a subsequent climate event and from one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; and redistributing, during said subsequent climate event, fluid flow between said initial route and said first route, using one or more of said successful infrastructure management strategies, to effectively reduce stress along said initial route and / or said first route and thereby reduce said initial route stress value or said estimated initial route stress value and / or said first route stress value or said estimated first route stress value.111 . The method of implementing infrastructure strategies of claim 109, wherein in said establishing, said initial route stress value or an estimated initial route stress value includes at least said stress value or said estimated stress value at said initial location, and said first route stress value or said estimated first route stress value represents a sum of at least said stress value or said estimated stress value at said one location of said first route and said stress value or said estimated stress value at said subsequent location; and wherein said redistributing effectively reduces said stress value or said estimated stress value at said initial location and / or said stress value or said estimated stress value at said one location of said first route.

112. A method of implementing infrastructure strategies, said method comprising: obtaining, based upon subsequent values and a climate event forecast, one or more server estimated range of subsequent values using said server operating in conjunction with one or more subsequent sensors, at least one of which is disposed at or near and measuring a fluid condition attribute at a subsequent location to produce said subsequent values, and wherein said server conveys said subsequent values orsaid server estimated range of, and said server conveys said subsequent values, if said subsequent values are not within said server estimated range of subsequent values; obtaining, based upon said climate event forecast and multiple intermediate values, a server estimated range of intermediate values and an additional server estimated range of intermediate values using said server operating in conjunction with multiple intermediate sensors, at least one of which is disposed at or near and measures said fluid condition attribute at one location on a first route to produce one or more intermediate values, wherein at least another of said multiple intermediate sensors is disposed at or near and measures said fluid condition attribute at said one location of said second route to produce one or more of said additional intermediate values, wherein said first route and said second route provide fluid communication between said initial location and said subsequent location and wherein said server estimated range of intermediate values are based upon said intermediate values and said additional server estimated range of intermediate values are based upon said additional intermediate values, and said server conveys to one or more of said fluid flow controllers one or more of said intermediate values or said server estimated range of intermediate values and said additional intermediate values or said additional server estimated range of intermediate values, and said server conveys one or more of said intermediate values, if one or more of said intermediate values are not within said server estimated range of intermediate values and said server conveys one or more of said additional intermediate values, if one or more of said additional intermediate values are not within said additional server estimated range of intermediate values; determining, at one or more of said fluid flow controllers, a stress value or an estimated stress value for each of said subsequent location, said one location of said first route and said one location on said second route based upon said subsequent values or said server estimated range of subsequent values, one or more of said intermediate values or said server estimated range of intermediate values, and one or more of said additional intermediate values or said additional server estimated range of intermediate values, respectively; and formulating, based upon said stress value or said estimated stress value for each of said subsequent location, said one location of said first route and said one location ofsaid second route, multiple infrastructure management strategies that reduce stress along said first route and / or said second route; comparing each of said infrastructure management strategies to an outcome of said climate event using one or more key point indicators of success in reducing said stress value or said estimated stress value for said first route and / or said second route; determining, based upon said comparing using one or more of said key point indicators of success in reducing said stress value or said estimated stress value for said first route and / or said second route; and storing, in one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies.

113. The method of implementing infrastructure strategies of claim 112, wherein in said formulating, said multiple infrastructure management strategies reduce said stress value or said estimated stress value at said one location of said first route and / or said stress value or said estimated stress value at said one location of said second route; wherein in said comparing, comparing each of said infrastructure management strategies to an outcome of said climate event using one or more key point indicators of success in reducing said stress value or said estimated stress value for said one location of said first route and / or said stress value or said estimated stress value at for one location of said second route; wherein in said determining, one or more of said successful infrastructure management strategies is based upon said comparing using one or more of said key point indicators of success in reducing said stress value or said estimated stress value for said one location of said first route and / or one location of said second route; and wherein said redistributing includes reducing fluid flow rate through said first route and / or through said second route.

114. The method of implementing infrastructure strategies of claim 112, wherein said formulating includes calculating a first route stress value or an estimated first route stress value and a second route stress value or an estimated second route stress value, and wherein said first route stress value or said estimated first route stress value represents a sum of said stress value or said estimated stress value for each of saidone location on said first route and said subsequent location and said second route stress value or said estimated second route stress value represents a sum of said stress value or said estimated stress value for each of said one location on said second route and said subsequent location; and said method further comprising: retrieving, during a subsequent climate event and from one or more of said fluid flow controllers, one or more of said successful infrastructure management strategies; and redistributing, during said subsequent climate event and using one or more flowdistributing components, fluid flow between said first route and said second route, using one or more of said successful infrastructure management strategies, to effectively reduce stress along said first route and / or said second route.

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