Method and device for determining structure of hydraulic pipe network, and electronic equipment

Abstract

The application relates to the technical field of drainage optimization, and discloses a method and device for determining a hydraulic pipe network structure and electronic equipment, the method comprising the following steps: acquiring a pipe network topological structure and catchment parameters corresponding to a target drainage area; performing hydraulic simulation of the pipe network of the target drainage area based on the pipe network topological structure and the catchment parameters, to obtain hydraulic response results of each pipe section and its associated nodes under a preset rainfall condition; determining a to-be-optimized key pipe section from a plurality of pipe sections based on the hydraulic response results; determining multi-target decision variables based on attribute parameters of the to-be-optimized key pipe section; and determining a pipe network structure corresponding to the target drainage area based on the multi-target decision variables. According to the hydraulic response results of each pipe section under the preset rainfall condition, the to-be-optimized key pipe section can be selected from a plurality of initial pipe sections, and the decision variables can be set according to the attribute parameters of the to-be-optimized key pipe section, so that the dimension of the decision variables is effectively reduced, and the determination efficiency of the hydraulic pipe network structure is improved.

Description

Technical Field

[0001] This invention relates to the field of drainage system optimization design technology, specifically to a method, apparatus, and electronic equipment for determining the structure of a hydraulic pipeline network. Background Technology

[0002] Urban stormwater drainage networks are a crucial component of urban drainage and flood control systems, and their hydraulic design directly impacts the region's capacity for collecting, transporting, and discharging stormwater runoff. With increasing urban construction intensity and the frequency of extreme rainfall events, traditional design methods relying on experience-based alignment, single-section trial calculations, and segment-by-segment verification are no longer sufficient to meet the optimization needs of complex network systems.

[0003] In related technologies, multi-objective optimization algorithms combined with hydrodynamic models are commonly used to optimize the structure of urban stormwater pipe networks. However, in actual operation, since the above methods directly include all pipe segments in the optimization variables, there will be a large number of decision variables, resulting in low computational efficiency when determining the pipe network structure. Summary of the Invention

[0004] This invention provides a method, apparatus, and electronic device for determining the structure of a hydraulic pipeline network, in order to solve the problems of a large number of decision variables and low computational efficiency in optimizing the structure of urban stormwater pipeline networks in related technologies.

[0005] In a first aspect, the present invention provides a method for determining the structure of a hydraulic pipeline network, comprising: obtaining the pipeline network topology and catchment parameters corresponding to a target drainage area; the pipeline network topology including multiple nodes connected by pipe segments; performing hydraulic simulation of the pipeline network in the target drainage area based on the pipeline network topology and the catchment parameters to obtain the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions; determining key pipe segments to be optimized from the multiple pipe segments based on the hydraulic response results; determining multi-objective decision variables based on the attribute parameters of the key pipe segments to be optimized; and determining the pipeline network structure corresponding to the target drainage area based on the multi-objective decision variables.

[0006] The method for determining the hydraulic pipeline network structure provided in this embodiment of the invention selects key pipeline segments to be optimized from multiple initial pipeline segments based on the hydraulic response results of each pipeline segment and its associated nodes under preset rainfall conditions, and sets decision variables based on the attribute parameters of the key pipeline segments to be optimized. Compared with the method of including all pipeline segments in the optimization of decision variables, this method can effectively reduce the dimensionality of decision variables and improve the efficiency of determining the hydraulic pipeline network structure.

[0007] In one optional implementation, the process of determining the key pipe segment to be optimized from multiple pipe segments based on the hydraulic response results includes: determining the hydraulic response index corresponding to each pipe segment based on the hydraulic response results; the hydraulic response index being used to characterize the hydraulic load of the corresponding pipe segment; determining the priority corresponding to each pipe segment based on the hydraulic response index; and determining the key pipe segment to be optimized from multiple pipe segments based on the priority corresponding to each pipe segment.

[0008] The method for determining the hydraulic pipeline network structure provided in this invention calculates the hydraulic response index of each pipe segment based on the hydraulic response results, determines the priority according to the index, and then screens the key pipe segments to be optimized, thereby realizing the quantification and automation of the key pipe segment screening process.

[0009] In one optional implementation, determining the priority of each pipe segment based on the hydraulic response indicators includes: normalizing each of the hydraulic response indicators to obtain a normalized index corresponding to each indicator; the hydraulic response indicators include at least one of the pipe segment load rate, maximum fullness, full flow duration ratio, upstream overflow contribution index, and drainage outlet correlation influence index for the corresponding pipe segment; weighting each of the normalized indicators to obtain a hydraulic response index; and the hydraulic response index characterizes the priority of the pipe segment.

[0010] The method for determining the hydraulic pipeline structure provided in this invention normalizes and weights multiple hydraulic response indicators with different dimensions and numerical ranges into a unified optimization priority index by normalizing and weighting multiple indicators such as pipeline load rate, maximum fullness, full flow duration ratio, upstream overflow contribution index and drainage outlet correlation influence index.

[0011] In an optional implementation, the method further includes: for any given node, obtaining the total overflow amount of the node under a preset rainfall condition; if the total overflow amount is determined to be greater than a preset threshold, then determining the node as an overflow node; determining the set of upstream control nodes for the pipe segment based on the pipe network topology; determining the set of overflow nodes within the upstream control range corresponding to the pipe segment based on the overflow nodes and the set of upstream control nodes; and then determining the upstream overflow contribution index based on the set of overflow nodes within the upstream control range.

[0012] The method for determining the hydraulic pipeline network structure provided in this invention identifies overflow nodes based on a total overflow threshold and determines the set of upstream control nodes for a pipeline segment based on the pipeline network topology. By using the overflow nodes and the set of upstream control nodes, the method determines the set of overflow nodes within the upstream control range corresponding to the pipeline segment, thereby accurately tracing the contribution of the upstream control area of ​​each pipeline segment to the system overflow problem.

[0013] In an optional implementation, the method further includes: for any given pipe segment, determining the set of drainage outlets downstream of the drainage path to which the pipe segment belongs based on the pipe network topology; obtaining hydraulic boundary parameters corresponding to each drainage outlet in the set of drainage outlets; the hydraulic boundary parameters being used to characterize the hydraulic state of the corresponding drainage outlet at the downstream boundary of the target drainage area; and determining the drainage outlet correlation influence index corresponding to the pipe segment based on each of the hydraulic boundary parameters.

[0014] The method for determining the hydraulic pipeline network structure provided in this invention determines the set of downstream drainage outlets of a pipeline segment based on the pipeline network topology, obtains the hydraulic boundary parameters of each drainage outlet, and then determines the drainage outlet correlation influence index corresponding to the pipeline segment. This method can effectively identify pipeline segments affected by unfavorable hydraulic conditions such as downstream external river water level backwater, restricted drainage outlet outflow, or elevated boundary water level.

[0015] In one optional implementation, determining the pipe network structure corresponding to the target drainage area based on the multi-objective decision variables includes: processing the multi-objective decision variables using a multi-objective optimization algorithm to obtain multiple candidate pipe network structures; generating a hydraulic model file corresponding to any candidate pipe network structure based on the attribute parameters of the key pipe segment to be optimized; running the hydraulic model file to obtain hydraulic response evaluation results for each candidate pipe network structure; and determining the target pipe network structure corresponding to the target drainage area from the multiple candidate pipe network structures based on the hydraulic response evaluation results and the project cost.

[0016] The method for determining the hydraulic pipeline network structure provided in this invention searches for the decision variables of key pipe sections by calling a multi-objective optimization algorithm, and automatically generates the corresponding hydraulic model file for hydraulic simulation evaluation after the candidate pipeline network structure is generated, thereby realizing automatic closed-loop iteration of optimization search and hydraulic simulation.

[0017] In an optional implementation, the method further includes: acquiring drainage system data of the design area; dividing the design area into drainage boundaries based on the drainage system data to obtain multiple drainage zones, and flow generation and confluence parameters corresponding to each drainage zone; constructing a pipe network topology corresponding to each drainage zone based on the flow generation and confluence parameters and the drainage system data; wherein the drainage zones include the target drainage area.

[0018] The method for determining the hydraulic pipeline structure provided in this embodiment of the invention obtains drainage zones and their runoff generation and confluence parameters by dividing the drainage boundary based on drainage system data, and constructs a corresponding pipeline topology for each drainage zone. This method can decompose a large and complex design area into several relatively independent drainage units, enabling subsequent hydraulic simulation and key pipe section selection to be carried out in parallel at the zone scale.

[0019] Secondly, the present invention provides a device for determining the structure of a hydraulic pipeline network. The device includes: an acquisition module for acquiring the pipeline network topology and catchment parameters corresponding to a target drainage area; the pipeline network topology includes multiple nodes connected by pipe segments; a simulation module for performing a hydraulic simulation of the pipeline network in the target drainage area based on the pipeline network topology and catchment parameters, obtaining the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions; a first determination module for determining a key pipe segment to be optimized from multiple pipe segments based on the hydraulic response results; a second determination module for determining multi-objective decision variables based on the attribute parameters of the key pipe segment to be optimized; and a third determination module for determining the pipeline network structure corresponding to the target drainage area based on the multi-objective decision variables.

[0020] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the method for determining the hydraulic pipeline structure described in the first aspect or any corresponding embodiment thereof.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the method for determining the hydraulic pipeline network structure described in the first aspect or any corresponding embodiment thereof.

[0022] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the method for determining the hydraulic pipeline network structure described in the first aspect or any corresponding embodiment. Attached Figure Description

[0023] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention.

[0025] Figure 2 This is a schematic diagram of the first method for determining the hydraulic pipeline network structure according to an embodiment of the present invention.

[0026] Figure 3 This is a schematic diagram of the second method for determining the hydraulic pipeline network structure according to an embodiment of the present invention. Figure 4 This is a structural block diagram of a device for determining the hydraulic pipeline network structure according to an embodiment of the present invention.

[0027] Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0030] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0031] In related technologies, multi-objective optimization algorithms combined with hydrodynamic models are commonly used to optimize the structure of urban stormwater pipe networks. However, in actual operation, since the above methods directly include all pipe segments in the optimization variables, there will be a large number of decision variables, resulting in low computational efficiency when determining the pipe network structure.

[0032] Therefore, this invention provides a method for determining the structure of a hydraulic pipeline network. It can select key pipeline segments to be optimized from multiple initial pipeline segments based on the hydraulic response results of each pipeline segment and its associated nodes under preset rainfall conditions, and set decision variables based on the attribute parameters of the key pipeline segments to be optimized. Compared with the method of including all pipeline segments in the optimization of decision variables, it can effectively reduce the dimensionality of decision variables and improve the efficiency of determining the structure of the hydraulic pipeline network.

[0033] The method for determining the hydraulic pipeline structure provided in this invention can be applied to hydraulic pipeline structure optimization design scenarios such as urban stormwater pipelines, drainage and flood control pipelines, regional drainage systems, park drainage systems, and sponge city drainage systems.

[0034] As an optional application scenario of this invention, such as Figure 1 The diagram shown illustrates the system architecture used in the drainage risk determination method provided in this embodiment of the invention. The system may include at least one electronic device and at least one server. Figure 1 The system is illustrated in the example, which includes an electronic device 101 and a server 102, with the electronic device 101 connected to the server 102 via a network 110.

[0035] Among them, electronic device 101 can be a workstation, personal computer, server, high-performance computing cluster, drainage model calculation platform, urban drainage and flood control design platform, or other equipment with hydraulic model calculation and optimization solution capabilities. Server 102 can be an independent physical server, a server cluster or a distributed system, or a cloud server providing cloud services. Network 110 can be a wired network or a wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0036] According to an embodiment of the present invention, a method for determining a hydraulic pipeline network structure is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0037] This invention provides a method for determining the structure of a hydraulic pipeline network, which can be used in the aforementioned electronic device equipped with a hydraulic pipeline network structure optimization system. Figure 2 This is a flowchart of a method for determining the hydraulic pipeline network structure according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Obtain the pipe network topology and water catchment parameters corresponding to the target drainage area.

[0038] The pipeline network topology includes multiple nodes, which are connected by pipe segments.

[0039] The target drainage area can be an urban drainage zone, a planned drainage area, the service area of ​​an existing stormwater pipe network, the service area of ​​a pumping station, or the control area of ​​a drainage outlet. The pipe network topology can include sets of nodes and sets of pipe segments. Nodes can include manhole nodes, inflow nodes, drainage outlet nodes, pumping station nodes, storage facility nodes, or boundary nodes. Pipe segments can include stormwater branch pipes, trunk pipes, main trunk pipes, box culverts, or other hydraulic connection units used to transport stormwater runoff.

[0040] Catchment parameters can include parameters such as catchment area, overall runoff coefficient, impermeability, slope, runoff path length, runoff time, underlying surface type, inflow node, and drainage direction for each catchment unit within the target drainage area. These parameters are used to describe the runoff generation and flow characteristics of the target drainage area in subsequent hydraulic simulations.

[0041] In this embodiment of the invention, by obtaining the pipe network topology and water catchment parameters corresponding to the target drainage area, the basic input of the hydraulic model corresponding to the target drainage area can be obtained, including the connection relationship between nodes and pipe segments, pipe segment length, pipe diameter, slope, pipe bottom elevation, soil cover depth, node ground elevation, water catchment area, runoff coefficient, and inflow node, so that hydraulic simulation and key pipe segment selection can be performed based on the pipe network topology and water catchment parameters.

[0042] It should be noted that when the target drainage area is a design area where the final stormwater pipe network has not yet been formed, the pipe network topology is obtained through drainage boundary delineation, pipe network alignment, and preliminary engineering design. The initial pipe diameter, initial slope, initial pipe bottom elevation, and initial cover depth of each pipe segment are determined according to relevant engineering design specifications, and are not assigned values ​​using uniform or arbitrary parameters.

[0043] Step S202: Based on the pipe network topology and water catchment parameters, perform a hydraulic simulation of the pipe network in the target drainage area to obtain the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions.

[0044] Preset rainfall conditions can include design storm intensity formulas, rainfall duration, return period, Chicago rainfall pattern, measured rainfall events, combinations of rainfall with different return periods, or drainage and flood control verification conditions. Hydraulic simulation can be achieved using SWMM (Storm Water Management Model) or other drainage network hydrodynamic models.

[0045] In this embodiment of the invention, an initial hydraulic simulation model corresponding to the target drainage area can be constructed based on the pipeline network topology, water catchment parameters, design rainfall data, drainage outlet boundary conditions, and pump station or storage facility parameters. The electronic equipment runs a hydraulic simulation under preset rainfall conditions, extracting the hydraulic response results of each pipe segment, associated node, and drainage outlet.

[0046] The hydraulic response results can include data such as pipe segment flow process, pipe segment full flow state, pipe segment fullness, pipe segment flow velocity, pipe segment water level, node water depth, node overflow total amount, node maximum water depth, outlet water level, outlet discharge flow, downstream boundary water level, tide level or river level, etc.

[0047] In this embodiment of the invention, by performing hydraulic simulation on the target drainage area, the dynamic hydraulic response results of each pipe segment and its associated nodes under the design rainfall conditions can be obtained. This allows for the identification of pipe segments with high hydraulic loads and strong relationships with overflow problems or unfavorable boundaries of drainage outlets from multiple pipe segments based on the hydraulic response results.

[0048] Step S203: Based on the hydraulic response results, identify the key pipe segments to be optimized from multiple pipe segments.

[0049] The critical pipe sections to be optimized refer to the pipe sections that have a high impact on the system's drainage capacity, node overflow risk, pipe section full flow risk, or unfavorable hydraulic conditions at downstream drainage outlets in the target drainage area.

[0050] Unlike the traditional approach that treats all pipe sections or a large number of main pipes as optimization targets, the embodiments of the present invention can adaptively screen key pipe sections based on the hydraulic response results obtained from hydraulic simulation, so that subsequent optimization decision variables are focused on pipe sections that are more necessary to be further optimized.

[0051] It should be noted that the other pipe sections not identified as key pipe sections to be optimized are not used with arbitrary parameters, but rather the initial engineering parameters have been determined based on the design flow and engineering design requirements when constructing the initial pipe network topology, and they meet the preset basic engineering design constraints.

[0052] Step S204: Determine multi-objective decision variables based on the attribute parameters of the key pipe segment to be optimized.

[0053] The attribute parameters of the key pipe sections to be optimized may include pipe diameter, slope, soil cover depth, pipe bottom elevation, pipe section cross-sectional dimensions, pipe section material, roughness coefficient, or other parameters that affect the hydraulic performance and project cost of the pipe section.

[0054] In multi-objective optimization problems, decision variables refer to unknown parameters that the decision-maker or optimization algorithm can control and adjust autonomously. Multi-objective means that there are at least two optimization objectives, and these objectives are usually conflicting. For example, the larger the total overflow of a node, the worse the performance of the drainage system tends to be. Multi-objective decision variables refer to the controllable parameters that the decision-maker needs to adjust and search in order to optimize multiple conflicting objectives at the same time.

[0055] In this embodiment of the invention, the pipe diameter, slope and soil cover depth of the key pipe section to be optimized can be used as multi-objective decision variables so that the pipe network structure corresponding to the target drainage area can be determined based on the multi-objective decision variables.

[0056] Step S205: Based on multi-objective decision variables, determine the pipe network structure corresponding to the target drainage area.

[0057] In this embodiment of the invention, a multi-objective optimization algorithm can be invoked to process the multi-objective decision variables, resulting in multiple candidate pipeline structures. The multi-objective optimization algorithm can be NSGA-II (Non-dominated Sorting Genetic Algorithm II), NSGA-III (Non-dominated Sorting Genetic Algorithm III), multi-objective particle swarm optimization, multi-objective genetic algorithm, multi-objective differential evolution algorithm, or other algorithms capable of solving multi-objective optimization problems.

[0058] For any candidate pipe network structure, the electronic device can update the pipe diameter, slope, soil cover depth or pipe bottom elevation of the corresponding pipe segment based on the attribute parameters of the key pipe segment to be optimized, and generate the hydraulic model file corresponding to the candidate pipe network structure.

[0059] When generating the complete hydraulic model file, the electronic equipment performs consistency checks on the bottom elevation of the entire pipeline network, the depth of the manholes, the inlet and outlet offsets of the pipe sections, the soil cover depth, and the model input parameters.

[0060] Furthermore, the complete hydraulic model file described above is run to re-simulate the hydraulic performance of all pipe segments, nodes, and drainage outlets of the candidate pipe network structure, thereby obtaining the hydraulic response evaluation results corresponding to the candidate pipe network structure.

[0061] For other pipe segments not identified as critical segments to be optimized, although their pipe diameter, slope, and overburden depth are not involved in the optimization search, they still participate in the complete hydraulic simulation and hydraulic constraint verification of each candidate pipe network structure. When changes in the parameters of the critical pipe segment to be optimized cause other pipe segments to fail to meet the preset hydraulic constraints, the corresponding candidate pipe network structure can be judged as an infeasible candidate pipe network structure, or a constraint penalty can be imposed on its objective function value.

[0062] The method for determining the hydraulic pipeline network structure provided in this embodiment of the invention selects key pipeline segments to be optimized from multiple initial pipeline segments based on the hydraulic response results of each pipeline segment and its associated nodes under preset rainfall conditions, and sets decision variables based on the attribute parameters of the key pipeline segments to be optimized. Compared with the method of including all pipeline segments in the optimization of decision variables, this method can effectively reduce the dimensionality of decision variables and improve the efficiency of determining the hydraulic pipeline network structure.

[0063] In one alternative implementation, before obtaining the pipe network topology corresponding to the target drainage area, the initial design area can be divided into drainage boundaries to obtain multiple drainage zones. The target drainage area is then determined from the multiple drainage zones to determine the hydraulic pipe network structure corresponding to the target drainage area.

[0064] Specifically, the drainage system data of the design area is obtained; based on the drainage system data, the drainage boundary of the design area is divided to obtain multiple drainage zones, as well as the flow generation and confluence parameters corresponding to each drainage zone; based on the flow generation and confluence parameters and the drainage system data, the pipe network topology corresponding to each drainage zone is constructed; the drainage zone includes the target drainage area.

[0065] In this embodiment, the design area can be a new urban area, an old city renovation area, an industrial park, a residential area, a road drainage service area, or an urban drainage and flood control special planning area. Drainage system data can include at least one of the following: topographic elevation data, road vertical data, planned land use data, land use data, surface water system data, river cross-section data, receiving water body water level data, existing or planned stormwater pipe network data, drainage outlet location, inspection well location, digital elevation model data, design rainfall data, and pump station design parameters.

[0066] Electronic equipment can divide the design area into multiple drainage zones based on terrain conditions, road slope, location of receiving water bodies, location of drainage outlets, service area of ​​pumping stations, and planned drainage boundaries. For areas with significant topographic relief, drainage zones can be divided by combining natural watersheds, road verticality, and location of receiving water bodies; for relatively flat areas, drainage zones can be divided by combining road orientation, planned land boundaries, and location of drainage outlets.

[0067] Each drainage zone can be further divided into several catchment units, and the area, runoff coefficient, inflow node, and drainage direction of each catchment unit can be determined. Then, based on the runoff generation and runoff parameters and drainage system data, the corresponding pipe network topology for each drainage zone can be constructed, including the connection relationships between main pipes, branch pipes, manhole nodes, and drainage outlet nodes.

[0068] For example, in order to transform the spatial drainage boundary into a catchment unit that can be recognized by the subsequent hydraulic model, this embodiment uses the following formula to transform the first... Each drainage zone is represented as a set of several catchment units.

[0069] ; in, Indicates the first r A collection of catchment units within a drainage zone; Indicates the first r Within the first drainage zone k One catchment unit; n r This indicates the number of water collection units within the drainage zone.

[0070] After determining the set of catchment units, it is necessary to further obtain the catchment size of the drainage zone. Therefore, the first... The total catchment area of ​​each drainage zone is: ; in, Indicates the first r The total catchment area of ​​each drainage zone. This indicator is used for subsequent calculations of drainage zone flow, setting sub-catchment parameters, and establishing the catchment input for hydraulic models.

[0071] Because different catchment units have different underlying surface types and runoff generation capacities, calculating only the total area is insufficient to describe the runoff generation characteristics of a drainage zone. Therefore, this embodiment further calculates the comprehensive runoff coefficient of the drainage zone based on the area and runoff coefficient of each catchment unit: ; in, For the first r The comprehensive runoff coefficient of each drainage zone; For the first r Within the first drainage zone k Runoff coefficient of each catchment unit; To prevent extremely small positive numbers with a denominator of zero.

[0072] In this way, electronic devices can obtain data such as the spatial range, catchment area, comprehensive runoff coefficient, inflow node and drainage direction of each drainage zone, so that the pipeline topology can be constructed based on the above data, and hydraulic simulation can be performed using the basic input data of the initial hydraulic model.

[0073] In another alternative implementation, after completing the division of drainage boundaries and catchment units, the catchment areas can be mapped to the stormwater pipe network system to form a pipe network topology capable of supporting hydraulic calculations. Specifically, electronic equipment can perform the plan layout and pipe network alignment of the drainage pipe system based on the road system, terrain elevation, location of receiving water bodies, drainage outlet control conditions, and pump station service range.

[0074] Pipeline network routing includes determining the location and direction of main pipes, trunk pipes, and branch pipes. In areas with gravity drainage capabilities, priority is given to utilizing topographical features to allow rainwater to flow by gravity into rivers or receiving water bodies. In low-lying areas or areas where drainage outlets are controlled by external river water levels, rainwater lifting pump stations can be installed at drainage ends, storage facilities, or drainage control nodes. For example, the pipeline network topology can be represented as follows: ; in, G This diagram represents the topology of the rainwater drainage network. V Represents a set of nodes. ; E Represents a set of pipe segments. , N Indicates the number of nodes; M This indicates the number of pipe segments. Nodes include stormwater inspection wells, stormwater inlets, drainage outlets, pumping station nodes, and water storage facility nodes. Pipe segments represent the water flow channels between nodes.

[0075] In order to enable each subsequent pipe segment to participate in hydraulic response calculation and optimization priority evaluation, this embodiment will... i The initial engineering parameters for the root canal segment are expressed as follows: ; in, This refers to the length of the pipe section. This is the initial pipe diameter; This is the initial slope; and These are the initial pipe bottom elevations at the upstream and downstream ends of the pipe segment, respectively. and These represent the initial soil cover depths at the upstream and downstream ends of the pipe section, respectively.

[0076] After obtaining the pipe network topology and catchment parameters corresponding to the target drainage area, the electronic equipment constructs an initial hydraulic simulation model for the target drainage area. This initial hydraulic simulation model can be an SWMM model, an InfoWorks ICM model (InfoWorks Integrated Catchment Modeling), or other models capable of simulating the hydrodynamic processes of urban stormwater pipe networks. The initial hydraulic simulation model includes sub-catchment modules, node modules, pipe segment modules, drainage outlet modules, pumping station modules, storage facility modules, and rainfall input modules.

[0077] To avoid bias in the selection of key pipe sections to be optimized due to a single rainfall condition, this embodiment of the invention can set multiple rainfall conditions.

[0078] ; in, R Indicates the preset rainfall conditions; r k Indicates the first k One rainfall condition; k This indicates the number of rainfall conditions.

[0079] After running the initial hydraulic simulation model, the electronic equipment extracts the hydraulic response results of each pipe segment, node, and drain outlet under various preset rainfall conditions. Since it is necessary to consider different dimensions of indicators such as the pipe segment's own load, node overflow, and drain outlet status when selecting key pipe segments to be optimized, this embodiment first needs to extract the hydraulic response results of the pipe segments, nodes, and drain outlets.

[0080] For the i root canal segment, in the k The hydraulic response under rainfall conditions can be expressed as: ; in, Indicates pipe section i In the k Under rainfall conditions t Flow rate at any given moment; Indicates water depth; Indicates the degree of fullness; Indicates flow rate.

[0081] For the j The node at the node k The hydraulic response under rainfall conditions can be expressed as: ; in, Represents a node j In thek Under rainfall conditions t The water level at that moment; Represents a node j exist t Overflow flow at any given moment.

[0082] To transform the node overflow process into a subsequently statistically measurable overflow metric, the node... j In the k The total overflow under rainfall conditions can be expressed as: ; in, This represents the total number of simulation time steps; This indicates the time step of the model output.

[0083] For the b The first drain outlet, in the... k The boundary or outflow response under rainfall conditions can be expressed as: ; in, Indicates the water level at the boundary of the drainage outlet or receiving water body; Indicates the discharge flow rate from the drain outlet; Indicators representing unfavorable hydraulic conditions at the drainage outlet.

[0084] In some alternative implementations, the unfavorable hydraulic state parameters of the drainage outlet can be determined based on the water level at the drainage outlet, the elevation of the top of the drainage pipe, and the degree of restriction on outflow. For example: ; in, This refers to the elevation of the top of the drainage pipe. The diameter or equivalent height of the drain outlet pipe. It represents a very small positive number.

[0085] This invention provides a dynamic hydraulic basis for optimizing the pipeline network structure by obtaining the pipeline network topology and water catchment parameters corresponding to the target drainage area and performing pipeline network hydraulic simulation under preset rainfall conditions.

[0086] This invention provides a method for determining the structure of a hydraulic pipeline network, which can be used in the aforementioned electronic equipment. Figure 3 This is a flowchart of a method for determining the hydraulic pipeline network structure according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: Step S301: Obtain the pipe network topology and water catchment parameters corresponding to the target drainage area; the pipe network topology includes multiple nodes, and each node is connected by a pipe segment.

[0087] Please see details Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0088] Step S302: Based on the pipeline network topology and water catchment parameters, perform hydraulic simulation of the pipeline network in the target drainage area to obtain the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions.

[0089] Please see details Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0090] Step S303: Based on the hydraulic response results, identify the key pipe segments to be optimized from multiple pipe segments; Specifically, step S303 includes: Step S3031: Based on the hydraulic response results, determine the hydraulic response indicators corresponding to each pipe section.

[0091] Hydraulic response indices characterize the hydraulic load state of a corresponding pipe segment and the degree of correlation between that segment and upstream overflow issues and unfavorable hydraulic conditions at downstream drainage outlets. Hydraulic response indices can be calculated based on hydraulic simulation results under preset rainfall conditions, combined with pipe segment attribute parameters and network topology. For any given pipe segment, basic data such as flow rate, water depth, fill rate, design water conveyance capacity, cross-sectional height, overflow process at upstream nodes along the drainage path, and downstream drainage outlet boundary conditions can be obtained from hydraulic simulation results and model baseline data. The hydraulic response indices for the corresponding pipe segment are then calculated based on this basic data.

[0092] The hydraulic response indicators may include at least one of the following: pipe section load rate, maximum filling degree, full flow duration ratio, upstream overflow contribution index, and drainage outlet correlation influence index.

[0093] For the pipe section i The pipe section load rate can be calculated using the following formula: ; in, For pipe section i Peak load rate; For pipe section i The design water conveyance capacity. This indicator is used to characterize the degree to which the flow rate of a pipeline section approaches or exceeds its water conveyance capacity.

[0094] After obtaining the peak load rate, the pipe section can be calculated using the following formula. i Maximum fill level: ; in, Indicates pipe section iThe maximum filling degree achieved under all rainfall conditions and simulation periods is used to reflect the degree to which the water depth of the pipe section approaches full capacity.

[0095] In practical applications, relying solely on the maximum fill degree may not reflect the duration of the full flow state. Therefore, this embodiment can also use the following formula to calculate the pipe section. i The percentage of full flow.

[0096] ; in, For pipe section i The percentage of full flow sustained; For pipe section i The corresponding threshold for judging full flow or near full flow; This is an indicator function; it takes the value 1 when the condition within the parentheses is true, and 0 otherwise. The above hydraulic response indicators can describe the hydraulic load of the pipe section itself from three perspectives: flow capacity utilization, maximum water depth, and full-flow duration.

[0097] Step S3032: Based on the hydraulic response index, determine the priority corresponding to each pipe section.

[0098] Pipe segment priority can be used to reflect the necessity of a pipe segment participating in optimization. If a pipe segment has a high load rate, high maximum fill degree, and high full-flow duration, and there is a significant overflow node upstream or an unfavorable drainage outlet boundary downstream, then the corresponding pipe segment has a higher priority and can be prioritized as a key pipe segment to be optimized. Conversely, if a pipe segment has a good hydraulic state and a weak correlation with overflow nodes and unfavorable drainage outlets, it can be excluded from optimization decision variables.

[0099] Step S3033: Based on the priority of each pipe segment, determine the key pipe segment to be optimized from multiple pipe segments.

[0100] The priority of each pipe segment is sorted to obtain the priority ranking result. Based on the priority ranking result, several pipe segments with higher priority are selected as key pipe segments to be optimized.

[0101] In some alternative implementations, the top 10%, top 20%, or top [number missing] of each pipe segment can be selected based on their priority ranking. Each pipe segment is designated as a critical segment to be optimized. Alternatively, a priority threshold can be set to identify pipe segments with a priority greater than the threshold as critical segments to be optimized.

[0102] By using the above method, the pipe segments that truly need optimization can be adaptively selected based on the initial hydraulic simulation results, thereby avoiding including all pipe segments in the optimization variables, reducing invalid searches, and improving the computational efficiency of subsequent multi-objective optimization and the targeted nature of pipeline network optimization design.

[0103] In some optional implementations, step S3033 above includes: Step a1: Normalize each index in the hydraulic response index to obtain the normalized index corresponding to each index.

[0104] In this embodiment of the invention, since the pipe section load rate, maximum fullness, full flow duration ratio, upstream overflow contribution index, and drainage outlet correlation influence index have different dimensions and numerical ranges, normalization processing is required first. After normalization, each index is converted to a unified dimension range, facilitating weighted fusion. For example, the following normalization function can be used to normalize each hydraulic response index: ; in, x i Indicates pipe section i For any corresponding hydraulic response index, N(x i ) This represents the normalized hydraulic response index vector; min(x) and max(x) These represent the minimum and maximum values ​​of the indicator across all pipe sections, respectively.

[0105] Step a2 involves weighting the various normalized indices to obtain the hydraulic response index.

[0106] After obtaining the hydraulic response index of the pipe section itself, the upstream overflow contribution index, and the drainage outlet correlation impact index, the electronic equipment can unify the above multiple dimensions of indicators into a comprehensive index that can be sorted and filtered.

[0107] Specifically, the normalized indicators are weighted to obtain the hydraulic response index, which is then used to characterize the priority of the corresponding pipe section.

[0108] For the pipe section i Its hydraulic response index can be expressed as: ; in, Indicates pipe section i The optimization priority index; Represents the normalization function; Indicates the load rate of the pipe section; Indicates the maximum fill level; Indicates the duration of full flow; Indicates the upstream overflow contribution index; Indicates the correlation impact index of drainage outlets; to Let be the weighting coefficients, and let the weighting coefficients satisfy . , .

[0109] Weights can be given by engineering experience or determined using the analytic hierarchy process (AHP), entropy weighting, or expert scoring. For example, for areas where drainage and flood control safety are the primary concern, the weights of upstream overflow node indicators and full-flow duration indicators can be increased; for areas where drainage outlets are significantly affected by external river water levels or tides, the weights of the drainage outlet correlation influence index can be increased.

[0110] The above method can comprehensively reflect the hydraulic load of the pipe section itself, the contribution of upstream overflow and the influence of downstream drainage outlet boundary. Compared with the method of screening pipe sections based only on maximum filling degree or node overflow, the embodiments of the present invention can more comprehensively identify key pipe sections that are sensitive to system hydraulic problems, and improve the rationality and interpretability of the selection of optimization objects.

[0111] In some alternative implementations, quantile thresholding can also be used to determine the critical pipe segment to be optimized: ; in, To optimize the priority index threshold; The hydraulic response index (also known as the optimization priority index) represents the hydraulic response index. Quantiles, then the set of critical pipe segments to be optimized can be represented as: ; In other alternative implementations, the pipe segments can be sorted from largest to smallest according to their hydraulic response index (i.e., optimization priority index), and a preset proportion or number of pipe segments at the top of the ranking can be selected as key pipe segments to be optimized. All pipe segments are sorted according to their optimization priority index as follows: If the first option is selected If the root canal segment is considered as the critical segment to be optimized, then the set of critical segments to be optimized can be represented as: ; in, The determination can be based on the pipeline network scale, optimization computing resources, and design accuracy requirements, or it can be determined as a certain proportion of the total number of pipeline segments: ; in, The key pipe section screening ratio, and meets the following requirements. .

[0112] Through the above steps, the electronic equipment can collect data from all pipe sections. The set of key pipe segments to be optimized was obtained through screening. The set of key pipe segments to be optimized will be directly used as the decision variables for the subsequent multi-objective optimization model. In other words, subsequent optimization will no longer set multi-objective decision variables for all pipe segments, but only for the pipe segments in the set of key pipe segments to be optimized, such as pipe diameter, slope, or soil cover depth. This reduces the number of multi-objective decision variables, reduces the number of times the multi-objective optimization model is called, and improves the computational efficiency of electronic equipment.

[0113] Step S304: Determine multi-objective decision variables based on the attribute parameters of the key pipe segment to be optimized.

[0114] In this embodiment of the invention, after determining the critical pipe segment to be optimized, the electronic device can construct multi-objective decision variables based on the attribute parameters of the critical pipe segment to be optimized. For example, for the critical pipe segment to be optimized... Its pipe diameter, slope, and overburden depth can be used as multi-objective decision variables, and the multi-objective decision variable vector can be represented as: ; Where X represents the decision variable vector of the multi-objective optimization model; D i Indicates pipe section i Optimized pipe diameter; S i Indicates pipe section i Optimized slope; H i Indicates pipe section i Optimize the soil cover depth.

[0115] In some alternative implementations, if the initial parameters are used as a baseline, the multi-objective decision variables can also be expressed as adjustment quantities: ; The optimized pipe diameter, slope, and cover depth are obtained by adding the initial values ​​and the adjustment amounts, respectively. ; ; ; in, , , Pipe sections i The initial pipe diameter, initial slope, and initial cover depth; , , These are the adjustments for pipe diameter, slope, and soil cover depth, respectively.

[0116] For other pipe segments that do not belong to the set of critical pipe segments to be optimized The pipe diameter, slope, and cover depth are not considered as optimization decision variables, and the initial design parameters are maintained: , , .in, , , Non-critical pipe sections The initial pipe diameter, initial slope, and initial cover depth.

[0117] In some alternative implementations, the pipe diameter can be encoded using a discrete pipe diameter encoding method: ; in, D For the set of optional pipe diameters, the range of values ​​for slope and soil cover depth can be set according to engineering design specifications, road vertical conditions and pipeline burial depth control requirements.

[0118] In this way, electronic devices can directly construct multi-objective decision variables based on the set of key pipe segments to be optimized, without introducing intermediate links such as related pipe segment expansion or variable mapping masks, thus making the model construction logic more direct, clear and feasible.

[0119] Step S305: Based on multi-objective decision variables, determine the pipe network structure corresponding to the target drainage area.

[0120] Please see details Figure 2 Step S205 of the illustrated embodiment will not be described again here.

[0121] In some optional implementations, before determining the priority of each pipe segment based on the hydraulic response index, for any given node, the total overflow amount of the node under a preset rainfall condition can be obtained first; if the total overflow amount is determined to be greater than a preset threshold, the node is determined to be an overflow node; then, based on the pipeline network topology, the set of upstream control nodes for the pipe segment is determined; next, based on the overflow nodes and the set of upstream control nodes, the set of overflow nodes within the upstream control range corresponding to the pipe segment is determined; further, based on the set of overflow nodes within the upstream control range, the upstream overflow contribution index is determined.

[0122] For nodes j If the total overflow amount under at least one rainfall event exceeds a preset threshold, it is identified as an overflow node. ; in, For the set of overflow nodes; This is a preset threshold. , The threshold values ​​can be determined based on engineering design standards, model output accuracy, or the statistical distribution of initial simulation results. For example, for a certain index... The threshold can be determined using the quantile method: ; in, As an indicator The corresponding preset threshold; for quantiles; The set of objects participating in the statistics.

[0123] The pipe section load rate can be obtained using the above formula. Maximum filling degree Full flow duration ratio and overflow node set These hydraulic response indicators can describe the hydraulic condition of a pipe section from its own hydraulic state and the system overflow object.

[0124] To further determine whether a particular pipe segment is worth optimizing, it is necessary to analyze the correlation between the pipe segment and the system overflow rate and the unfavorable conditions of the drainage outlet. Therefore, it is also necessary to calculate the upstream overflow contribution index and the drainage outlet correlation impact index.

[0125] First, determine the pipe section. i The set of overflow nodes within the upstream inflow range. Pipeline section. i The set of upstream control nodes is Then the pipe section i The corresponding set of upstream overflow nodes is: ; in, Indicates location within pipe section i The set of overflow nodes within the upstream control area, which describes the pipe segment. i Is there any significant overflow problem in the upstream area under control?

[0126] In determining After that, the pipe section i The upstream overflow contribution index can be expressed as: ; in, For pipe section i The upstream spillover contribution index; For the first k The weight of rainfall conditions.

[0127] The numerator in the above formula represents the pipe segment. i The weighted overflow rate of all overflow nodes within the upstream control range under multiple rainfall conditions; the denominator represents the weighted total overflow rate of all overflow nodes in the system. Therefore, It can be used to characterize pipe sections The degree to which the controlled upstream region contributes to the overall overflow problem of the system. If there are many overflow nodes and a large overflow volume within the upstream merging range of a certain pipe segment, then the upstream overflow contribution index of that pipe segment is high.

[0128] In practical applications, considering only the upstream overflow contribution index of a pipe segment cannot fully reflect the downstream boundary conditions of the drainage path in which the pipe segment is located. For areas affected by external river water levels, high water levels at drainage outlets, or restricted outflow, the hydraulic state of the drainage outlet also affects the importance of pipe segment optimization. Therefore, this embodiment of the invention also requires calculation of the pipe segment... i The impact index of drainage outlets.

[0129] Specifically, for any given pipe segment, the set of drainage outlets downstream of the drainage path to which the pipe segment belongs is first determined based on the pipe network topology; then, the hydraulic boundary parameters corresponding to each drainage outlet in the drainage outlet set are obtained, which are used to characterize the hydraulic state of the corresponding drainage outlet at the downstream boundary of the target drainage area; then, based on each hydraulic boundary parameter, the drainage outlet correlation influence index corresponding to the pipe segment is determined.

[0130] Assuming from the pipe section The collection of drainage outlets reachable along the downstream water flow direction is Then the pipe section i The correlation impact index of the drainage outlet is: ; in, For pipe section i The correlation index of drainage outlets; For drainage outlet b In the k Unfavorable hydraulic state indicators under rainfall conditions; For pipe section i The number of downstream associated drainage outlets and the weights of each rainfall condition are satisfied as follows: , .

[0131] The drainage outlet correlation impact index is used to characterize pipe sections. i The unfavorable hydraulic condition of the downstream drainage outlet along the drainage path. If A relatively large value indicates that there is a significant risk of restricted outflow, elevated boundary water level, or backwater at the downstream drainage outlet along the pipeline route. In subsequent optimization, the attention given to this pipeline segment should be appropriately increased.

[0132] In practical applications, after determining the multi-objective decision variables, the multi-objective optimization algorithm generates different combinations of candidate variables in each iteration. In order for these combinations of candidate variables to be correctly read and calculated by the hydraulic model, they need to be converted into complete model input data and subjected to consistency verification.

[0133] In this embodiment of the invention, a multi-objective optimization algorithm is first invoked to process the multi-objective decision variables, resulting in multiple candidate pipe network structures. For any candidate pipe network structure, a hydraulic model file corresponding to the candidate pipe network structure is generated based on the attribute parameters of the key pipe segment to be optimized. Then, the hydraulic model file is run to obtain the hydraulic response evaluation results corresponding to each candidate pipe network structure. Next, based on the hydraulic response evaluation results corresponding to each candidate pipe network structure, the target pipe network structure corresponding to the target drainage area is determined from the multiple candidate pipe network structures.

[0134] Specifically, after the multi-objective optimization algorithm generates multiple candidate pipe network structures, the electronic device updates the parameters such as pipe diameter, slope and overburden depth of the corresponding key pipe segments according to the attribute parameter variables of the key pipe segments in the candidate pipe network structures, and generates the hydraulic model file corresponding to the candidate pipe network structure.

[0135] It is worth noting that although this embodiment only sets multi-objective decision variables for the key pipe sections to be optimized, when generating the hydraulic model file corresponding to the candidate pipe network structure, the electronic device still performs consistency checks on the pipe elevation, manhole depth, pipe section offset, soil cover depth and model input parameters of the entire pipe network to ensure that the model file meets the calculation requirements of the drainage pipe network hydraulic model.

[0136] For the key pipe sections to be optimized The downstream pipe bottom elevation can be determined based on the upstream pipe bottom elevation, slope, and pipe section length: ; in, For pipe section i Upstream end pipe bottom elevation; For pipe section i Downstream end pipe bottom elevation; For the slope of the pipe section; This refers to the length of the pipe section.

[0137] After obtaining the elevations of the pipe bottoms at the upstream and downstream ends of the pipe section, the overburden depth at the upstream and downstream ends of the pipe section can be further calculated: ; ; in, and These are the ground elevations at the upstream and downstream nodes of the pipeline segment, respectively. The pipe diameter or equivalent height of the pipe section.

[0138] To ensure that the candidate pipeline structure meets the engineering installation requirements, the soil cover depth of the pipe section should meet the minimum soil cover constraint: , ,in, For pipe sectioni The minimum allowable soil cover depth.

[0139] For inspection well nodes v j The bottom elevation of the well can be uniformly determined based on the bottom elevation of all pipe segments connected to that node at that node. Let the node be... v j The connected pipe segments are E(j) Then the elevation of the bottom of the well at the node can be expressed as: ; in, Indicates pipe section i At the node j The elevation of the bottom of the pipe at the location. After determining the elevation of the bottom of the node well, the depth of the inspection well is: ; in, For nodes j Ground elevation.

[0140] If the SWMM model is used, when generating the hydraulic model file corresponding to the candidate pipe network structure, the electronic equipment can recalculate and write the node bottom elevation, node maximum depth, pipe segment inlet offset, pipe segment outlet offset and pipe segment cross-sectional parameters based on the updated pipe segment diameter, pipe segment length, slope, node well bottom elevation and pipe segment inlet and outlet elevation.

[0141] For the pipe section i The inlet offset at the upstream node and the outlet offset at the downstream node can be expressed as follows: ; ; in, For pipe section i The import offset; For pipe section i The exit offset; and These are the bottom elevations of the upstream and downstream nodes of the pipeline segment, respectively.

[0142] In practical applications, for other pipe sections that are not identified as key pipe sections to be optimized, their pipe diameter, slope, and overburden depth are not changed as optimization variables; however, when writing to the hydraulic model file, the electronic equipment can still recalculate the offset and maximum depth of the node related to the bottom elevation of the node well according to the consistency check rules of the whole pipeline network, so as to ensure the correctness of the model connection relationship.

[0143] Through the above implementation method, each candidate pipeline structure can meet the calculation requirements of the hydraulic model after being written into the hydraulic model file, avoiding model operation errors caused by inconsistencies in node well depth, pipe segment offset, soil cover depth, or pipe bottom elevation.

[0144] After completing the selection of key pipe sections to be optimized, the construction of multi-objective decision variables, and the setting of model parameter consistency verification rules, the electronic equipment constructs a multi-objective optimization design model corresponding to the target drainage area. Since this model is only for... The optimization variables are set for the pipe segments in the model, so the number of decision variables is significantly reduced compared to the model that optimizes all pipe segments.

[0145] If the total number of pipe segments is The number of key pipe sections to be optimized is Then the variable compression ratio can be expressed as: ; in, k This represents the compression ratio of the optimized variables. The smaller the ratio, the higher the degree of dimensionality reduction of the optimized variable space.

[0146] In some alternative implementations, the objective function in the multi-objective optimization model includes at least two of the following: minimizing engineering cost, minimizing system overflow, minimizing the proportion of continuous full flow in the pipe section, and minimizing the unfavorable hydraulic state of the drainage outlet.

[0147] The first objective function is to minimize the project cost, which can be calculated using the following formula: ; in, Indicates optimization of pipeline network structure X The total cost of constructing or renovating the corresponding rainwater pipe network.

[0148] The second objective function is to minimize the total system overflow, which can be calculated using the following formula: ; in, Indicating in candidate pipeline structure X Next, node j In the k Total overflow under rainfall conditions.

[0149] The third objective function is to minimize the proportion of the system's full-flow duration, which can be calculated using the following formula: ; in, Indicating in candidate pipeline structure Below, pipe section i In the k Rainfall conditions tThe fullness of time.

[0150] The fourth objective function is to minimize the unfavorable hydraulic state at the drainage outlet, which can be calculated using the following formula: ; in, Indicating in candidate pipeline structure X Below, drain outlet b In the k Unfavorable hydraulic state indicators under rainfall conditions.

[0151] In practical applications, two or more objective functions can be selected to construct a multi-objective optimization model based on the engineering objectives. For example, in areas where the main objective is to control urban flooding overflow, the objective functions of engineering cost and total system overflow can be used as the primary focus; in areas where drainage outlets are significantly affected by the water level of external rivers, the objective function of unfavorable hydraulic conditions of the drainage outlets can be further incorporated.

[0152] The constraints of a multi-objective optimization model may include at least one of the following: pipe diameter constraint, soil cover depth constraint, slope constraint, flow velocity constraint, pipe bottom elevation connection constraint, and model consistency check constraint.

[0153] Pipe diameter constraints can be expressed as: ; The soil cover depth constraint can be expressed as: ; Slope constraints can be expressed as: ; The flow velocity constraint can be expressed as: ; The pipe bottom elevation connection constraint can be expressed as: ; In this embodiment of the invention, the electronic device can construct a dimensionality-reduced multi-objective optimization model based on the set of key pipe segments to be optimized, so that the multi-objective optimization algorithm only searches for multi-objective decision variables on the key pipe segments, thereby improving the generation efficiency of candidate pipe network structures and the evaluation efficiency of hydraulic models.

[0154] After constructing a dimensionality-reduced multi-objective optimization model based on multi-objective decision variables, objective functions, and constraints, electronic devices can also use multi-objective optimization algorithms to solve the above multi-objective optimization model.

[0155] For the n The decision variables for a candidate pipeline network structure can be expressed as follows: ; Alternatively, the adjustment amount can be expressed as follows: ; During each evaluation of candidate pipeline structures, electronic equipment can... Update the pipe diameter, slope, and cover depth of key pipe sections, and generate hydraulic model files corresponding to candidate pipe network structures according to the above consistency verification rules. Subsequently, the electronic equipment runs the corresponding rainfall conditions to obtain the objective function values ​​corresponding to the candidate pipe network structures. ; in, n This indicates the number of objective functions.

[0156] Through iterative search using a multi-objective optimization algorithm, a set of Pareto optimal solutions that balance different objective functions can be obtained.

[0157] ; in, This is the Pareto optimal solution set; The number of Pareto solutions.

[0158] In some alternative implementations, to improve model solving efficiency, hydraulic model files can be generated in batches for multiple candidate pipe network structures, and a parallel computing approach can be used to complete the hydraulic simulation evaluation.

[0159] Through the above steps, the electronic equipment can obtain multiple pipe network structures. Since these pipe network structures have different trade-offs among objective functions such as engineering cost, overflow control, full flow duration ratio and drainage outlet hydraulic state, it is necessary to further adopt a comprehensive evaluation method to screen out a better pipe network structure from the Pareto solution set.

[0160] Specifically, after obtaining the Pareto optimal solution set, the electronic equipment uses a comprehensive evaluation method to rank the Pareto optimal solution set and select recommended optimized pipeline structures. The comprehensive evaluation method can be TOPSIS, grey relational analysis, entropy weighting, analytic hierarchy process (AHP), or a combination thereof.

[0161] First, the objective function values ​​are standardized to obtain the standardized objective matrix: ; in, Z n,m Indicates the first n The Pareto network structure in the first m Standardized values ​​for each target.

[0162] Based on the standardized objective matrix, the positive and negative ideal solutions are determined: ; ; Among them, the positive ideal solution represents the pipeline structure in which all objectives reach the optimal state, while the negative ideal solution represents the pipeline structure in which all objectives are in a poor state.

[0163] Further, calculate the first n The distance between the network structure and the ideal solution: ; Calculate the first n The distance between the network structure and the negative ideal solution: ; in, M f Indicates the number of objective functions; w m Indicates the first m The comprehensive evaluation weight of each objective function.

[0164] To simultaneously reflect the degree to which the pipeline network structure approaches and deviates from the positive ideal solution, the calculation of the first... n The proximity of the pipeline structure.

[0165] ; The greater the proximity, the closer the pipeline structure is to the positive ideal solution and the farther away it is from the negative ideal solution. For example, the pipeline structure with the greatest proximity can be identified as the recommended optimized pipeline structure.

[0166] ; Among them, the comprehensive evaluation weight The objective function can be determined based on project objectives, investment constraints, drainage safety requirements, or expert evaluation, or it can be automatically determined using the entropy weight method based on the degree of dispersion of each objective function value.

[0167] In some optional implementations, the electronic device can also output recommended optimized pipe network structures and their corresponding pipe network design parameters, hydraulic evaluation results, engineering cost results, and model construction results. The output may include: recommended optimized pipe network structure numbers, changes in pipe diameter, slope, cover depth, and bottom elevation of key pipe sections before and after optimization, pipe section optimization priority index, set of key pipe sections to be optimized, optimization variable compression ratio, Pareto optimal solution set, comprehensive evaluation results, changes in system overflow, full-flow duration ratio, and unfavorable hydraulic state at drainage outlets before and after optimization, and model consistency verification results corresponding to candidate pipe network structures, etc.

[0168] The model construction result can be represented as follows: ; in, This is the set of key pipe segments to be optimized. To optimize the variable compression ratio; P is the Pareto optimal solution set; To recommend optimizing the pipeline network structure.

[0169] By outputting the above results, it can be explained how the key pipe segments are selected from the initial hydraulic simulation results, and how the variable space of the multi-objective optimization model is directly constructed from the set of key pipe segments to be optimized, thereby improving the engineering interpretability and verifiability of the optimization design model.

[0170] This invention also provides a device for determining the structure of a hydraulic pipeline network, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0171] This invention provides a device for determining the structure of a hydraulic pipeline network, such as... Figure 4 As shown, it includes: The acquisition module 401 is used to acquire the pipe network topology and water catchment parameters corresponding to the target drainage area; the pipe network topology includes multiple nodes, and each node is connected by a pipe segment.

[0172] The simulation module 402 is used to perform hydraulic simulation of the pipe network in the target drainage area based on the pipe network topology and water catchment parameters, and obtain the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions.

[0173] The first determination module 403 is used to determine the key pipe segment to be optimized from multiple pipe segments based on the hydraulic response results.

[0174] The second determination module 404 is used to determine multi-objective decision variables based on the attribute parameters of the key pipe segment to be optimized.

[0175] The third determining module 405 is used to determine the pipe network structure corresponding to the target drainage area based on multi-objective decision variables.

[0176] In one optional implementation, the first determining module includes: The first determining unit is used to determine the hydraulic response index corresponding to each pipe segment based on the hydraulic response results; the hydraulic response index is used to characterize the hydraulic load of the corresponding pipe segment.

[0177] The second determining unit is used to determine the priority of each pipe section based on the hydraulic response index.

[0178] The third determining unit is used to determine the key pipe segment to be optimized from multiple pipe segments based on the priority corresponding to each pipe segment.

[0179] In one optional implementation, the second determining unit includes: The first processing subunit is used to normalize each index in the hydraulic response index to obtain the normalized index corresponding to each index. The hydraulic response index includes at least one of the following: pipe section load rate, maximum filling degree, full flow duration ratio, upstream overflow contribution index, and drainage outlet correlation influence index.

[0180] The second processing subunit is used to perform weighted processing on each normalized index to obtain the hydraulic response index; the hydraulic response index represents the priority of the pipe section.

[0181] In one optional embodiment, the apparatus further includes: The first acquisition module is used to acquire the total overflow of any given node under preset rainfall conditions.

[0182] The fourth determination module is used to determine a node as an overflow node if the total overflow amount is greater than a preset threshold.

[0183] The fifth determination module is used to determine the set of upstream control nodes of a pipeline segment based on the pipeline network topology.

[0184] The second acquisition module is used to determine the set of overflow nodes within the upstream control range corresponding to the pipe segment based on the overflow nodes and the set of upstream control nodes; and to determine the upstream overflow contribution index based on the set of overflow nodes within the upstream control range.

[0185] In one optional embodiment, the device further includes: The sixth determination module is used to determine the set of drainage outlets downstream of the drainage path to which any given pipe segment belongs, based on the pipe network topology.

[0186] The third acquisition module is used to acquire the hydraulic boundary parameters corresponding to each drainage outlet in the drainage outlet set; the hydraulic boundary parameters are used to characterize the hydraulic state of the corresponding drainage outlet at the downstream boundary of the target drainage area.

[0187] The seventh determination module is used to determine the correlation influence index of the drainage outlet corresponding to each pipe segment based on various hydraulic boundary parameters.

[0188] In one optional implementation, the third determining module includes: The first processing unit is used to call a multi-objective optimization algorithm to process multi-objective decision variables and obtain multiple candidate pipeline structures.

[0189] The generation unit is used to generate a hydraulic model file corresponding to any candidate pipe network structure based on the attribute parameters of the key pipe segments to be optimized.

[0190] The second processing unit is used to run the hydraulic model file and obtain the hydraulic response evaluation results corresponding to each candidate pipe network structure.

[0191] The fourth determining unit is used to determine the target pipe network structure corresponding to the target drainage area from multiple candidate pipe network structures based on the hydraulic response evaluation results corresponding to each candidate pipe network structure.

[0192] In one optional embodiment, the device further includes: The fourth acquisition module is used to acquire drainage system data for the design area.

[0193] The partitioning module is used to divide the design area into drainage boundaries based on drainage system data, resulting in multiple drainage zones and corresponding runoff generation and confluence parameters for each drainage zone.

[0194] The construction module is used to build the pipe network topology for each drainage zone based on the runoff and drainage system data; the drainage zone includes the target drainage area.

[0195] The hydraulic pipeline network structure determination device provided in this embodiment of the invention can execute the hydraulic pipeline network structure determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0196] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0197] The following is a detailed reference. Figure 5 This diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory 502 or a program loaded from memory 508 into random access memory 503. Random access memory 503 also stores various programs and data required for the operation of the electronic device. The processor 501, read-only memory 502, and random access memory 503 are interconnected via bus 504. Input / output interface 505 is also connected to bus 504.

[0198] Typically, the following devices can be connected to the input / output interface 505: input devices 506 including, for example, a touchscreen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; memory devices 508 including, for example, magnetic tape, hard disk, etc.; and communication devices 509. Communication devices 509 allow electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0199] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a read-only memory 502. When the computer program is executed by the processor 501, it performs the functions defined in the method for determining the hydraulic network structure according to embodiments of the present invention.

[0200] Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0201] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the method for determining the hydraulic pipeline network structure shown in the above embodiments is implemented.

[0202] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0203] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for determining the structure of a hydraulic pipeline network, characterized in that, The method includes: Obtain the pipe network topology and water catchment parameters corresponding to the target drainage area; the pipe network topology includes multiple nodes, and each node is connected by a pipe segment. Based on the pipeline network topology and the water catchment parameters, a hydraulic simulation of the pipeline network is performed on the target drainage area to obtain the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions. Based on the hydraulic response results, the key pipe segments to be optimized are determined from among the multiple pipe segments; Based on the attribute parameters of the key pipe segment to be optimized, multi-objective decision variables are determined; Based on the multi-objective decision variables, the pipe network structure corresponding to the target drainage area is determined.

2. The method according to claim 1, characterized in that, The process of identifying key pipe segments to be optimized from multiple pipe segments based on the hydraulic response results includes: Based on the hydraulic response results, the hydraulic response indicators corresponding to each of the pipe sections are determined. Based on the hydraulic response index, the priority of each pipe segment is determined. Based on the priority of each pipe segment, the key pipe segments to be optimized are determined from the multiple pipe segments.

3. The method according to claim 2, characterized in that, The step of determining the priority of each pipe segment based on the hydraulic response index includes: Each of the hydraulic response indices is normalized to obtain the normalized index corresponding to each index; the hydraulic response indices include at least one of the following: pipe section load rate, maximum filling degree, full flow duration ratio, upstream overflow contribution index, and drainage outlet correlation influence index. The normalized indices are weighted to obtain the hydraulic response index; the hydraulic response index represents the priority of the pipe section.

4. The method according to claim 3, characterized in that, The method further includes: For any given node, obtain the total overflow of that node under a preset rainfall condition; If the total overflow amount is determined to be greater than a preset threshold, then the node is determined to be an overflow node; Based on the pipeline network topology, determine the set of upstream control nodes for the pipeline segment; Based on the overflow node and the upstream control node set, determine the overflow node set within the upstream control range corresponding to the pipe segment; The upstream overflow contribution index is determined based on the set of overflow nodes within the upstream control range.

5. The method according to claim 3, characterized in that, The method further includes: For any given pipe segment, determine the set of drainage outlets downstream of the drainage path to which the pipe segment belongs based on the pipe network topology; Obtain the hydraulic boundary parameters corresponding to each drainage outlet in the set of drainage outlets; the hydraulic boundary parameters are used to characterize the hydraulic state of the corresponding drainage outlet at the downstream boundary of the target drainage area. Based on the hydraulic boundary parameters, the associated influence index of the drainage outlet corresponding to the pipe segment is determined.

6. The method according to claim 1, characterized in that, The step of determining the pipe network structure corresponding to the target drainage area based on the multi-objective decision variables includes: A multi-objective optimization algorithm is invoked to process the multi-objective decision variables, resulting in multiple candidate pipeline structures; For any candidate pipe network structure, a hydraulic model file corresponding to the candidate pipe network structure is generated based on the attribute parameters of the key pipe segment to be optimized; Run the hydraulic model file to obtain the hydraulic response evaluation results corresponding to each of the candidate pipe network structures; Based on the hydraulic response evaluation results corresponding to each of the candidate pipe network structures, the target pipe network structure corresponding to the target drainage area is determined from the multiple candidate pipe network structures.

7. The method according to claim 1, characterized in that, The method further includes: Obtain drainage system data for the design area; Based on the drainage system data, the design area is divided into drainage boundaries to obtain multiple drainage zones, and the corresponding flow generation and confluence parameters for each drainage zone. Based on the runoff and runoff parameters and the drainage system data, a pipe network topology corresponding to each drainage zone is constructed; the drainage zone includes the target drainage area.

8. A device for determining the structure of a hydraulic pipeline network, characterized in that, The device includes: The acquisition module is used to acquire the pipe network topology and water catchment parameters corresponding to the target drainage area; the pipe network topology includes multiple nodes, and each node is connected by a pipe segment. The simulation module is used to perform hydraulic simulation of the pipe network in the target drainage area based on the pipe network topology and the water catchment parameters, and to obtain the hydraulic response results of each pipe segment and its associated nodes under preset rainfall conditions. The first determining module is used to determine the key pipe segment to be optimized from multiple pipe segments based on the hydraulic response results; The second determining module is used to determine multi-objective decision variables based on the attribute parameters of the key pipe segment to be optimized; The third determining module is used to determine the pipe network structure corresponding to the target drainage area based on the multi-objective decision variables.

9. An electronic device, characterized in that, include: A memory and a processor are interconnected, the memory stores computer instructions, and the processor executes the computer instructions to perform the method for determining the hydraulic pipeline network structure as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the method for determining the hydraulic network structure as described in any one of claims 1 to 7.

Images