Adaptive convection control in a substantially enclosed chamber

Abstract

A system for predicting the convective behavior in an enclosed chamber according to a 1st order approximation of a thermodynamic steady state solution not derived from partial differential equations and describing individual points, surfaces, and volumes, within the chamber and generating therefrom an optimal configuration of entities that maximizes convection and minimizes the activity of at least one flow generating entity

Description

[0001] ADAPTIVE CONVECTION CONTROL IN

[0002] A SUBSTANTIALLY ENCLOSED CHAMBER

[0003] FIELD OF THE INVENTION

[0004] This invention relates in general temperature regulation, and in particular to optimizing convection currents in chambers containing temperature sensitive entities.

[0005] BACKGROUND OF THE INVENTION

[0006] In modern industry, many processes are reliant on the temperature in enclosed and partially enclosed chambers. The effective operation of curing ovens essential for many manufacturing processes in ceramic and polymer engineering, so too are the chambers used for heat tempering metal and glass products. The general problem of optimizing the convection currents within substantially enclosed chambers to maintain the heat transferred to or from various temperature sensitive entities is one with significant importance in the server industry, where a computer server’s safe operation is dependent on its temperature being maintained below a threshold value. Similar problems exist in maintaining temperatures below a threshold for personnel in offices, and still too for other applications.

[0007] Many solutions have been developed and disclosed pursuant of this objective in specific industries, though none has yet been taught that can be configured to solve the general problem itself. The most pressing of these specific industries is the server industry, where many of the solutions taught in the prior art are severely limited, ensuring that running costs for cooling systems are exceptionally high.

[0008] The system and method disclosed in US202211372460 teach a method for the effective temperature maintenance of server devices in a chamber, utilizing artificial intelligence algorithms to balance the power consumption of the servers. A similar technique is developed and disclosed in US20210405727, which teaches a method of load-balancing of server systems to maintain temperature. Balancing power use is also the means by which the method taught in US20210255799 reduces the risk of overheating for data storage devices. Rather than balancing the power consumption of the servers themselves, the method disclosed in US2022369510A1 teaches a specific method of distributing a refrigerant throughout the servers.

[0009] Neural networks, a form of machine learning, appear in US20220087075, where they are used to optimize the cooling via convection of temperature sensitive entities, specifically servers and other data storage devices in a data center. Neural networks can be useful in the finding approximate solutions to the partial differential equations (PDEs) required to model the movement of heat and the dynamics of fluid flow, such as the air moving around a data center. However valuable this general principle, the knowledge taught in US20220087075 is insufficient for a person skilled in the art, for several reasons including but not limited to: the lack of sufficient disclosure for producing the means of accurately representing the geometry of the space in which the PDEs are solved; the means of measuring environmental parameters is neither specific nor necessary for the method; the flow generation function of “cooling devices” is not sufficiently captured as a necessary parameter for modelling convection. These deficiencies render the method taught in US20220087075 unclear and ineffective.

[0010] Neural networks also appear in US2021053418A1, where a method for the intelligent control of temperature in a vehicle is taught. The case for which this patent teaches a method is highly specific, the temperature sensitive entities are human passengers rather than data storage devices, and the speed of the vehicle being a significant factor. Unfortunately, for the general problem defined above, the knowledge taught in US2021053418A1 cannot provide persons skilled in the art with effective transferable methods or systems. Therefore, there remains a need in the art for a system and method for controlling the temperature in a chamber containing temperature sensitive entities.

[0011] SUMMARY OF THE INVENTION

[0012] The following embodiments and aspects thereof are described and illustrated in conjunction with systems, devices and methods which are meant to be exemplary and illustrative and not limiting in scope. In various embodiments, one or more of the abovedescribed problems have been reduced or eliminated, while other embodiments are directed to other advantages or improvements.

[0013] According to a first aspect of the invention, a system for the adaptive control of temperature as a result of fluid convection in a substantially enclosed chamber comprises: (a) fluid undergoing passive ambient convection; (b) at least one temperature sensitive entity; (c) at least one linear temperature sensing entity with a plurality of loci at which temperature is sensed located within the substantially enclosed chamber; (d) at least one flow-generating entity capable of generating a flow of the fluid within the substantially enclosed chamber and thereby facilitating active convection additional to the ambient convection undergone by the fluid; (e) a geometrically accurate digital model of the substantially enclosed chamber containing all entities located therein; (f) a control unit with access to the geometrically accurate digital model and in communication with the at least one linear temperature sensor and least one flow-generating entity, wherein a control unit accesses a geometrically accurate digital model of substantially enclosed chamber and all entities located therein and predicts the convective behavior therein according to a 1storder approximation of a thermodynamic steady state solution not derived from partial differential equations and describing individual points, surfaces, and volumes, within the chamber and generates therefrom an optimal configuration of entities that maximizes convection and minimizes the activity of the at least one flow generating entity. The control unit may employ a machine learning, neural network, or artificial intelligent algorithm in order to operate the said 1storder approximation of a thermodynamic steady state solution not derived from partial differential equations. By generating a first order approximation of the thermodynamic steady state solution without operating partial differential equations as conventionally associated with the fluid mechanics and heat transfer, the present invention can optimize the convection within the limited context of the substantially enclosed chamber without demanding high computational effort, and thereby allowing for multiple iterations that more closely approximate the real situation with limited computational resources.

[0014] According to another aspect of the invention, the system further comprises a fluid flow actuating entity capable of redirecting the flow of the fluid within the substantially enclosed chamber and thus of the convective behavior of said fluid. Persons skilled in the art will appreciate that the term “redirecting” in this context can be interpreted to mean “actuating”, “controlling”, “influencing”, or “maneuvering”.

[0015] According to another aspect of the invention, the system further comprises a flowsensing entity capable of measuring the direction and velocity of flow over a particular area.

[0016] According to another aspect of the invention, the entities within the geometrically accurate digital model are generated from the images captured within the substantially enclosed chamber.

[0017] According to another aspect of the invention, the temperature sensitive entities themselves generate higher temperatures, and wherein the optimal configuration of entities generated by the control unit sets a reference range of tolerance temperatures within which said temperature sensitive entities are maintained. For cooling applications, the upper limit of said range of temperatures indicates a maximum temperature for whatever process is undertaken by or on the temperature-sensitive entities, and the lower limit of said temperature range indicates a temperature below which the use of additional convection is a waste of energy for the maintenance of said process. For heating applications, the lower limit of said range of temperatures indicates a minimum temperature for whatever process is undertaken by or on the temperature-sensitive entities, and the upper limit of said temperature range indicates a temperature below which the use of additional convection is a waste of energy for the maintenance of said process.

[0018] According to another aspect of the invention, the temperature sensitive entities are server modules, and wherein the fluid in the substantially enclosed chamber is air.

[0019] According to another aspect of the invention, the temperatures sensitive entities are workspaces for human workers.

[0020] According to another aspect of the invention, the temperature sensitive entities themselves absorb ambient temperatures, and wherein the optimal configuration of entities generated by the control unit sets a reference temperature range within which said temperature sensitive entities are maintained. When the control unit is configured to operate a neural network, machine learning, or artificial intelligence algorithm, said algorithm can be configured to factor for the thermal transition of the interface between said temperature sensitive entities and said fluid.

[0021] According to another aspect of the invention, the temperature sensitive entities are items undergoing a curing, heat treating, or tempering process.

[0022] According to another aspect of the invention, a method of adaptively controlling the temperature in a substantially enclosed chamber as a result of fluid convection comprises the steps: (a) generating a geometrically accurate digital model of the substantially enclosed chamber containing at least one temperature sensitive entity, at least one temperature sensing entity, and at least one flow-generating entity, located therein; (b) accessing said geometrically accurate digital model with a control unit and predicting therewith the convection behavior of the fluid utilizing non-differential equations resolving point, surface, and volume temperature changes; (c) setting a threshold temperature above or below which the temperature sensitive entity cannot be allowed to pass; (d) holding the configuration of at least one entity in the geometrically accurate digital model as fixed; and (e) determining the optimal configurations of all remaining entities in the geometrically accurate digital model for the maximal convection with minimal activity of the at least one flow-generating entity, whereby a control unit accesses a geometrically accurate digital model of a substantially enclosed chamber and the at least one temperature sensitive entity and the at least one temperature-sensing entity and the at least one flow-generating entity contained therein and predicts the convection behavior therein according to temperatures changes at individual points, surfaces, and volumes, and wherein optimal configurations of entities are thereby determined.

[0023] According to another aspect of the invention, the entities in the geometrically accurate digital model include a fluid flow actuating entity capable of redirecting the flow of the fluid within the substantially enclosed chamber and thus of the convective behavior of said fluid. Persons skilled in the art will appreciate that the term “redirecting” in this context can be interpreted to mean “actuating”, “controlling”, “influencing”, or “maneuvering”.

[0024] According to another aspect of the invention, the entities in the geometrically accurate digital model include a flow-sensing entity capable of measuring the direction and velocity of flow over a particular area.

[0025] According to another aspect of the invention, the control module is in direct communication with entities other than the temperature sensitive entities, and continually updates the geometrically accurate digital model to reflect the real-time convective behavior of the fluid in the substantially enclosed chamber.

[0026] According to another aspect of the invention, the method further comprises a step after step (e): directly controlling the non-sensing entities to adjust the configuration according to the determination of optimal configurations.

[0027] According to another aspect of the invention, the method further comprises the steps prior to step (a): (a) capturing images of the substantially enclosed chamber; and (b) generating from said images locations of the entities contained therein. A person skilled in the art will recognize that the said locations are within a substantially enclosed chamber, and thus that they constitute locations within a three dimensional space. A person skilled in the art will also recognize that due to the said entities having a non-zero volume, the said locations refer to subvolumes within the substantially enclosed chamber. A person skilled in the art will yet still recognize that due to features of the said entities being functional, for example the outlet of a fluid flow generating entity, that the functional features and geometric configuration thereof will also be represented in the sub-volumes located within the substantially enclosed chamber. When the control unit is configured to operate a neural network, machine learning, or artificial intelligence algorithm, said algorithm can be configured to operate step (b) “generating from said images locations of the entities contained therein”, thereby accurately generating a digital model of the substantially enclosed chamber and all entities contained therein from said images, including the operating parameters of said entities from a database containing product information wherein the product information is captured in the said images.

[0028] BRIEF DESCRIPTION OF THE FIGURES Some embodiments of the invention are described herein with reference to the accompanying figures. The description, together with the figures, makes apparent to a person having ordinary skill in the art how some embodiments may be practiced. The figures are for the purpose of illustrative description and no attempt is made to show structural details of an embodiment in more detail than is necessary for a fundamental understanding of the invention.

[0029] In the Figures:

[0030] FIG. 1 constitutes a “simple” model heat dissipation based on a series of thermal conductors, according to some embodiments.

[0031] FIG. 2 constitutes a demonstration of the boundary effect and its influence on laminar and turbulent fluid flows, according to some embodiments.

[0032] FIG. 3 constitutes an overview of the zones of propelled fluid from a fluid flow actuating entity and its effect on surrounding fluid, according to some embodiments.

[0033] FIG. 4 constitutes an overview of a substantially enclosed chamber containing temperature-sensitive entities in which convection is generated in a conventional manner, according to some embodiments.

[0034] FIG. 5 constitutes an overview of a substantially enclosed chamber containing temperature-sensitive entities of FIG. 4 further comprising temperature sensors and a thermal controller feeding a digital model of said chamber, according to some embodiments.

[0035] FIG. 6 constitutes an overview of a substantially enclosed chamber containing temperature-sensitive entities of FIG. 5 further comprising the control unit of the present invention, according to some embodiments. FIG. 7A-B constitute overviews of the control unit of the present invention in FIG. 6 embodied with a machine learning algorithm, according to some embodiments.

[0036] FIG. 8 constitutes a flow of logic for the control unit of the present invention through a range of temperatures, according to some embodiments.

[0037] FIG. 9A-B constitutes configurations for generating a digital model of the substantially enclosed chamber and entities therein, according to some embodiments of the invention

[0038] DETAILED DESCRIPTION OF SOME EMBODIMENTS:

[0039] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components, modules, units and / or circuits have not been described in detail so as not to obscure the invention. Some features or elements described with respect to one embodiment may be combined with features or elements described with respect to other embodiments. For the sake of clarity, discussion of same or similar features or elements may not be repeated.

[0040] Reference is made to FIG. 1, which constitutes a “simple” model heat dissipation based on a series of thermal conductors, according to some embodiments. Three temperature areas are shown: the ambient temperature 101 outside the substantially enclosed chamber 110; the case temperature 102 of the border of the substantially enclosed chamber 110; the junction temperature 103 within the substantially enclosed chamber 110. This model, simply defined with only three temperatures, indicates the difference in temperatures within the and outside of the substantially enclosed chamber 110 as a result of convection, either active or passive. By configuring a resistance chain 104 containing two temperature-sensitive resistors: case-to- ambient 105 between the case temperature 102 and the ambient temperature 101; andjunction- to-case 106 between the junction temperature 103 and the case temperature 102, the resistance chain 104 can determine relative temperatures therebetween which can be used to determine the effect of convection, active or passive, within and around the substantially enclosed chamber 110.

[0041] Reference is made to FIG. 2, which constitutes a demonstration of the boundary effect and its influence on laminar and turbulent fluid flows, according to some embodiments. Initial flow 201 along a boundary produces in an initial distance 202 a laminar boundary layer zone 203 in which the flow at the interface produces a laminar boundary layer. Within the laminar boundary layer zone 203 the flow distribution follows a laminar boundary layer zone flow distribution 231, wherein the flow further away from the boundary layer is at faster velocity than the flow at the boundary, due to friction between the stationary surface and the initial fluid flow 201. As the flow progresses along the surface, the laminar flow breaks down into a series of turbulent eddies in the transition zone 204, before becoming turbulent boundary layer zone 205 in which a majority of the flow is turbulent. Within the turbulent boundary layer zone 205 the flow distribution follows a laminar boundary layer zone flow distribution 231, wherein the flow further away from the boundary layer is at faster velocity than the flow at the boundary, due to friction between the stationary surface and the initial fluid flow 201. Within the turbulent boundary layer zone 203 four specific layers define distinct patterns of flow that produce the flow distribution 231: the turbulent layer 207; the overlap layer 208; the buffer layer 209; and the viscous sub layer 210. The present invention determines the first order approximation of thermodynamic steady solution according to an understanding of this behaviour, wherein:

[0042] For Laminar flow: h = 3.86 0.8

[0043] For Turbulent flow:

[0044] For Heat Transfer: h = 2.51

[0045] In the above three equations, h = convective heat coefficient, V= velocity, L = distance from the source of fluid flow, C = shape coefficient, and AT = temperature difference. Using the above three equations, and resolving for three dimensions with known values relating to the shape coefficient and set values relating to the temperature range values, the present invention presents a means of determining the effective temperature difference as a result of fluid flow within a substantially enclosed chamber.

[0046] Reference is made to FIG. 3, which constitutes an overview of the zones of propelled fluid from a fluid flow actuating entity and its effect on surrounding fluid, according to some embodiments. In the case illustrated by FIG. 3, the fluid is air, however different compressible and non-compressible fluids can be modelled in a system similar to FIG. 3 for the purposes of the present invention. A flow of air 311 emanating from a fluid flow actuating entity 310 at an angle of 312 and through a four distinct zones which define the effect of said flow of air 311 on the surrounding air 315. During the short zone 301 air from the surrounding air 315 is drawn into the stream at a high velocity, and the interface between the induced flow form the surrounding air 315 and the flow of air 311 is highly distinct. In the transition zone 302 this interface is reduced, as more of the surrounding air 315 is drawn into the flow of air 311, and is drawn in at an angle closer to the direction of the flow of air 311. In the long zone 303, the air being drawn in 315 to the flow of air 311 begins to induce gentle movement 313 of the surrounding air further away from the initial flow of air 311. In the interface of the long zone 303 and the terminal zone 304, the induced air movement from the surrounding air 315 joins the initial flow of air 311 in flow direction, producing a net air flow 314 in the surrounding air 315 away from the initial flow 311. By modelling the fluid emanating from a fluid flow actuating entity with the model illustrated in FIG. 3, the present invention can calculate the extent and direction of fluid velocity as function of its position in relation to a fluid flow actuating entity , using the below equations.

[0047] Short Zone Velocity:

[0048] Transition Zone Velocity:

[0049] Long Zone Velocity:

[0050] Vx

[0051] Terminal Zone Velocity: — ^0

[0052] Where Vxis the velocity at a point, Vo is the initial velocity, Ao is the effective outlet area, X is the throw distance, and K2; K3; and K4, are the transition zone constant; long zone constant; and terminal zone constant, respectively. The distance from the fluid flow actuating entity at which the terminal velocity of the fluid flow is measured is also known in the art as the “throw”, and its cross sectional area perpendicular to the flow is also known in the art as the “spread”.

[0053] Reference is made to FIG. 4, which constitutes an overview of a substantially enclosed chamber containing temperature-sensitive entities in which convection is generated in a conventional manner, according to some embodiments. A substantially enclosed chamber 401 containing a fluid contains three temperature sensitive entities 421, 422, and 423. A conventional fluid flow actuating entity produces a conventional fluid flow in the substantially enclosed chamber 401. Under these conventional conditions, the energy used for the fluid flow actuating entity to produce the conventional fluid flow is non-optimized, such that it is not adaptive for the convective dynamics of the substantially enclosed chamber 401.

[0054] Reference is made to FIG. 5, which constitutes an overview of a substantially enclosed chamber containing temperature-sensitive entities of FIG. 4 further comprising temperature sensors and a thermal controller feeding a digital model of said chamber, according to some embodiments. A substantially enclosed chamber 401 contains a fluid and three temperature sensitive entities 421, 422, and 423. Unlike the conventional case illustrated in FIG. 4, in the case illustrated by FIG. 5A a control unit 500 is in communication with a series of temperature sensors 501 configured as a linear temperature sensor 502, and is in further communication and control of the fluid flow actuating entity 503. The control unit 500 calculates the optimal configuration of the fluid flow actuating entity 503 according to the temperature sensed by the linear temperature sensor 502, and according to a digital model illustrated in FIG. 5B, wherein digital models 521, 522, and 523 are rendered of the three temperature sensitive entities 421, 422, and 423, as is a digital model of the fluid flow actuating entity 531 of the fluid flow actuating entity 503. The overlapping flows of fluid generated by the fluid flow actuating entity 503 are also modelled, and the effect on convection in the substantially enclosed chamber is modelled using the model illustrated in FIG 3. Using the digital model illustrated in FIG. 5B and the control unit 501 in communication with , the present invention can adaptively facilitate for optimal convective control of the substantially enclosed chamber illustrated in FIG. 5A.

[0055] A person skilled in the art will appreciate that the shape of the substantially enclosed chamber, the number of temperatures sensitive entities, and the number, power, and geometric configuration of the fluid flow actuating entity / ies may be altered from the case illustrated in

[0056] FIG. 5 Reference is made to FIG. 6, which constitutes an overview of a substantially enclosed chamber containing temperature-sensitive entities of FIG. 5 further comprising the control unit of the present invention, according to some embodiments. In the case illustrated by the FIG. 6, the present invention allows not only for the adaptive control of the power of the fluid flow actuating entity , but also the optimal vectorization of said fluid flow actuating entity . A substantially enclosed chamber 401 contains a fluid and three temperature sensitive entities

[0057] 421, 422, and 423, a control unit 600 is in communication with a series of temperature sensors 501 configured as a linear temperature sensor 502, and is in further communication and control of the fluid flow actuating entity 603 and is capable of adaptively controlling the vectorization and power of the fluid flow actuating entity 603. Using the models illustrated in FIG. 2 and FIG. 3, and calculating said models within a digital model such as that illustrated in FIG. 5B, the embodiment of present invention illustrated in FIG. 6 can optimize the convection in the substantially enclosed chamber 401 in order to maintain the temperature sensitive entities 421,

[0058] 422, and 423 within an ideal temperature range.

[0059] Reference is made to FIG. 7, which constitutes an overview of the control unit of the present invention in FIG. 6 embodied with a machine learning algorithm, according to some embodiments. In the operating logic of the control unit operated by the control unit illustrated in FIG. 7B the control unit and is considered the agent 700, and the conditions of the substantially enclosed chamber are considered as the environment 701. Through decisions regarding the configurations of the fluid flow actuating entity the agent 700 effects changes to the surrounding 701 through actions 702, and through the at least one linear temperature sensor the agent 700 receives observations 703 regarding the conditions of the surrounding 701 in order to define the current state 705. A feature in the operating logic demonstrated in FIG. 7A is the reward 704 derived from information gleaned in the surrounding 701 that feeds the machine learning decision making process 706 the agent operates to generate actions 702 on the surroundings 701 from the state 705 defined form the observations 703 of the surroundings

[0060] 702. A person skilled in the art will appreciate the definition of “reward” in this context, that it is a mathematical mechanism for a neural network, artificial intelligence, or other machine learning algorithm to “learn” the optimal configuration of a system during training and apply the algorithm “learned” from the maximum accumulated reward during training to an application. A simplified model of the flow of processes 702, 703, and 704 between the logical entities 700 and 701 is further illustrated in FIG. 7B.

[0061] Reference is made to FIG. 8, which constitutes a flow of logic for the control unit of the present invention through a range of temperatures, according to some embodiments. The class of embodiments illustrated by the FIG. 8 refers to cases in which the temperature sensitive entities are required to be operated below a threshold temperature, and wherein said temperature sensitive entities themselves produce heat. Along a temperature scale 800 and along the progression of time 810, a range of temperatures constituting three regions is defined: a dangerous region 811; an optimal region 812; and an energy waste region 813. A target temperature 801 defines the boundary between the dangerous region 811 and the optimal region 812. The recorded ambient temperature 802 defines the boundary between the optimal region 812 and the energy waste region 813.

[0062] A 0-reward temperature 803 is defined above the target temperature and within the dangerous region 811, and it is the distance from this 0-reward temperature 803 that a reward value 830, as illustrated as 704 in FIG. 7, is derived. A temperature observed in in the in the dangerous region 811 will thus be awarded a large negative reward 831, temperature observed closer to the 0 -value reward temperature 803 will be awarded a less negative reward 832, a temperature observed at the 0 -value reward temperature 803 will be awarded a reward of 0 833. A temperature observed at the target temperature 801 will be awarded the maximum reward 833, as temperatures decrease down to the ambient temperatures the rewards awarded 834 and 835 similarly approach 0. At the ambient temperature 802 and below, a 0-value reward 836 is awarded, and an identical 0-value reward 837 is awarded at significantly lower temperatures.

[0063] With the embodiment of the control unit illustrated in FIG. 8, the reward system ensures that the surrounding is maintained within a target range 820, above which the temperaturesensitive entities are susceptible to damage, and below which the system is in danger of applying more energy than is required. According to another embodiment of the invention, the reward can be further modified according to the time taken for temperatures to change or stabilize.

[0064] Persons skilled in the art that the directionality of the temperature scale illustrated in FIG. 8 is particular to a class of cases in which the objective is to cool the temperature-sensitive entities, but that a similar technique can be employed with a reversed temperature scale for heating applications, and in particular for heating applications when the temperature-sensitive entities absorb heat, such as in curing or tempering applications.

[0065] Reference is made to FIG. 9A , which constitutes a configuration for generating a digital model of the substantially enclosed chamber and entities therein, according to some embodiments of the invention. Images 901 captured from image capture devices, such as dedicated camera devices or cameras installed in other devices, are communicated to a control system apparatus 910, which uploads 915 said images 901 to a cloud computing network 920. According to some embodiments of the invention, the upload process 915 of the images 901 to the cloud computing network 920 includes an additional processing step operated by the control unit apparatus 910. The cloud computing network utilizes this information to generate a digital model file 930, which can be viewed in a user interface as a three dimensional rendering 940 of a substantially enclosed chamber.

[0066] Reference is made to FIG. 9B, which constitutes a configuration for the generation and processing of a digital model of the substantially enclosed chamber and entities therein utilizing neural network, machine learning, or artificial intelligence (Al) algorithms, according to some embodiments of the invention. Images 901 are captured and communicated to a control unit apparatus 910 and further communicated 915 to a cloud computing network 920 wherein a digital model file 930 is generated. The three dimensional rendering 940 is then processed using an Al algorithm 950 to generate an optimized configuration of entities 960 which is communicated 965 to the cloud computing network 920 before being communicated 966 to a user interface 970 configured to manage the optimization of the real substantially enclosed chamber and entities therein.

[0067] Although the present invention has been described with reference to specific embodiments, this description is not meant to be construed in a limited sense. Various modifications of the disclosed embodiments, as well as alternative embodiments of the invention will become apparent to persons skilled in the art upon reference to the description of the invention. It is, therefore, contemplated that the appended claims will cover such modifications that fall within the scope of the invention.

Claims

CLAIMS1. A system for the adaptive control of temperature as a result of fluid convection in a enclosed chamber comprising: a. fluid undergoing passive ambient convection; b. at least one temperature sensitive entity; c. at least one linear temperature sensing entity with a plurality of loci at which temperature is sensed located within the enclosed chamber; d. at least one flow-generating entity capable of generating a flow of the fluid within the enclosed chamber and thereby facilitating active convection additional to the ambient convection undergone by the fluid; e. a geometrically accurate digital model of the enclosed chamber containing all entities located therein; f. a control unit with access to the geometrically accurate digital model and in communication with the at least one linear temperature sensor and least one flow-generating entity, wherein a control unit accesses a geometrically accurate digital model of enclosed chamber and all entities located therein and predicts the convective behavior therein according to a 1 st order approximation of a thermodynamic steady state solution not derived from partial differential equations and describing individual points, surfaces, and volumes, within the chamber and generates therefrom an optimal configuration of entities that maximizes convection and minimizes the activity of the at least one flow generating entity.

2. The system of claim 1, further comprising a fluid flow actuating entity capable of redirecting the flow of the fluid within the enclosed chamber and thus of the convective behavior of said fluid.

3. The system of claim 1, wherein the entities within the geometrically accurate digital model are generated from the images captured within the enclosed chamber.

4. The system of claim 1 , wherein the temperature sensitive entities themselves generate higher temperatures, and wherein the optimal configuration of entities generated by the control unit sets a reference range of tolerance temperatures within which said temperature sensitive entities are maintained.

5. The system of claim 4, wherein the temperature sensitive entities are server modules or components contained within server modules, and wherein the fluid in the enclosed chamber is air.

6. The system of claim 4, wherein the temperatures sensitive entities are workspaces for human workers.

7. The system of claim 1 , wherein the temperature sensitive entities are items undergoing a curing, heat treating, or tempering process.

8. A method of adaptively controlling the temperature in a enclosed chamber as a result of fluid convection comprises the steps: a. generating a geometrically accurate digital model of the enclosed chamber containing at least one temperature sensitive entity, at least one temperature sensing entity, and at least one flow-generating entity, located therein; b. accessing said geometrically accurate digital model with a control unit and predicting therewith the convection behavior of the fluid utilizing non- differential equations resolving point, surface, and volume temperature changes; c. setting a threshold temperature above or below which the temperature sensitive entity cannot be allowed to pass; d. holding the configuration of at least one entity in the geometrically accurate digital model as fixed; and e. determining the optimal configurations of all remaining entities in the geometrically accurate digital model for the maximal convection with minimal activity of the at least one flow-generating entity, whereby a control unit accesses a geometrically accurate digital model of a enclosed chamber and the at least one temperature sensitive entity and the at least one temperature - sensing entity and the at least one flow-generating entity contained therein and predicts the convection behavior therein according to temperatures changes at individual points, surfaces, and volumes, and wherein optimal configurations of entities are thereby determined.

9. The method of claim 8, wherein the entities in the geometrically accurate digital model include a fluid flow actuating entity capable of redirecting the flow of the fluid within the enclosed chamber and thus of the convective behavior of said fluid.

10. The method of claim 8, the control module is in direct communication with entities other than the temperature sensitive entities, and continually updates the geometrically accurate digital model to reflect the real-time convective behavior of the fluid in the enclosed chamber.

11. The method of claim 8, further comprising a step after step (e): directly controlling the non-sensing entities to adjust the configuration according to the determination of optimal configurations.

12. The method of claim 8, further comprising the steps prior to step (a): (a) capturing images of the enclosed chamber; and (b) generating from said images locations of the entities contained therein.

Images