Liquid flow conduction cyclic heat management method and system

Abstract

The present invention provides a circulating heat management method and system for liquid flow conduction, which relates to the field of heat exchange technology. The specific implementation scheme is: design multiple candidate geometric structures of U-shaped heat exchange bends, and perform flow field simulation on each candidate U-shaped heat exchange bend to obtain the flow field distribution of each candidate U-shaped heat exchange bend. Based on the flow field distribution of each candidate U-shaped heat exchange bend, the correlation equation between the heat exchange bend structure and the local turbulence intensity can be determined. Then, based on the correlation equation and the actual turbulence intensity distribution of the U-shaped heat exchange bend, each candidate geometric structure is optimized to obtain a target geometric structure that can optimize the actual turbulence intensity distribution of the U-shaped heat exchange bend and achieve the optimization target. In this way, based on the target U-shaped heat exchange bend corresponding to the target geometric structure, the U-shaped heat exchange bend in the liquid flow conduction system is replaced. The use of the present invention can improve the heat transfer efficiency of the liquid flow conduction system.

Description

Technical Field

[0001] The present invention relates to the field of heat exchange technology, and in particular to a circulating heat management method and system using liquid flow conduction. Background Art

[0002] In the study of liquid flow conduction circulating thermal management, there are some technical contradictions and problems in the regulation mechanism of local turbulence intensity by the regular corrugated structure etched on the inner wall of the U-shaped bend pipe.

[0003] First, excessively high corrugations will significantly increase fluid resistance, while excessively low corrugations will make it difficult to effectively stimulate turbulence. Therefore, how to find the best balance in practical applications is a technical problem that needs to be solved urgently. Secondly, a fillet radius that is too small can easily cause premature separation of the fluid at the crest, while a fillet radius that is too large can weaken the turbulence-stimulating effect of the corrugations. It is particularly important to balance various technical conflicts and find a suitable crest fillet radius. Furthermore, the length of the trough transition zone is also a key parameter. A transition zone that is too short may cause sudden disturbances in the fluid, while a transition zone that is too long will reduce the overall efficiency of the corrugated structure. This technical contradiction in the existing technology increases the difficulty of cyclic thermal management. Finally, in actual thermal management applications, changes in the radius of curvature will also change the distribution characteristics of the corrugations on the pipe wall, thereby affecting the distribution of local turbulence intensity, which puts higher demands on achieving refined thermal management control. Summary of the Invention

[0004] The present invention provides a liquid flow-conducting circulating heat management method, device, system and storage medium, which can solve at least one of the above technical problems.

[0005] According to one aspect of the present invention, a cyclic heat management method using liquid flow conduction is provided, comprising:

[0006] For a first U-shaped heat exchange elbow in a fluid conduction system, multiple candidate geometric structures of the U-shaped heat exchange elbow are designed based on the U-shaped curvature radius and the inner wall corrugation structure, wherein the inner wall corrugation structure includes the corrugation height, the crest fillet radius, and the trough transition zone length;

[0007] Based on each of the candidate geometric structures, flow field simulations are performed to obtain flow field distributions of the candidate U-shaped heat exchange elbow corresponding to each of the candidate geometric structures, wherein the flow field distributions include velocity field distribution, pressure field distribution, and turbulence intensity distribution;

[0008] Determining a correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow;

[0009] Based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow, optimizing and selecting each of the candidate geometric structures to obtain a target geometric structure;

[0010] The first U-shaped heat exchange elbow in the fluid conducting system is replaced based on a target U-shaped heat exchange elbow corresponding to the target geometric structure.

[0011] According to another aspect of the present invention, a circulating heat management device using liquid flow conduction is provided, comprising:

[0012] a candidate structure determination module for designing, for a first U-shaped heat exchange elbow in a fluid conduction system, multiple candidate geometric structures of the U-shaped heat exchange elbow based on the U-shaped curvature radius and the inner wall corrugation structure, wherein the inner wall corrugation structure includes corrugation height, crest fillet radius, and trough transition zone length;

[0013] A flow field simulation module is used to perform flow field simulation based on each of the candidate geometric structures to obtain the flow field distribution of the candidate U-shaped heat exchange elbow corresponding to each of the candidate geometric structures, wherein the flow field distribution includes velocity field distribution, pressure field distribution and turbulence intensity distribution;

[0014] A correlation equation determination module, configured to determine a correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow;

[0015] a target structure determination module, configured to optimize and select each of the candidate geometric structures based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow to obtain a target geometric structure;

[0016] The elbow replacement module is used to replace the first U-shaped heat exchange elbow in the liquid flow conduction system based on the target U-shaped heat exchange elbow corresponding to the target geometric structure.

[0017] According to another aspect of the present invention, there is provided an electronic device, comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to execute any liquid flow conduction cyclic thermal management method in the embodiments of the present invention.

[0021] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any liquid flow-conducting cyclic thermal management method according to the embodiments of the present invention.

[0022] By adopting the technical solution of the present invention, multiple candidate geometric structures of the U-shaped heat exchange bend are designed for the first U-shaped heat exchange bend in the liquid flow conduction system, and flow field simulations are performed respectively to obtain the flow field distribution of the candidate U-shaped heat exchange bend corresponding to each candidate geometric structure. Based on the flow field distribution of each candidate U-shaped heat exchange bend, the correlation equation between the heat exchange bend structure and the local turbulence intensity can be determined. Then, based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange bend, each candidate geometric structure is optimized and selected to obtain a target geometric structure that can optimize the actual turbulence intensity distribution of the first U-shaped heat exchange bend and achieve the optimization target. In this way, based on the target U-shaped heat exchange bend corresponding to the target geometric structure, the first U-shaped heat exchange bend in the liquid flow conduction system is replaced, which can reduce the turbulence intensity of the liquid flow conduction system and improve the heat transfer efficiency of the liquid flow conduction system.

[0023] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are provided for a better understanding of the present invention and do not constitute a limitation of the present invention.

[0025] Figure 1 This is a flow chart of a cyclic heat management method using liquid flow conduction according to an embodiment of the present invention;

[0026] Figure 2 This is a structural block diagram of a liquid flow conduction circulating heat management device according to an embodiment of the present invention;

[0027] Figure 3 is a block diagram of an electronic device for implementing the method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, and various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0029] Figure 1FIG. 1 is a flow chart of a cyclic heat management method using liquid flow conduction according to an embodiment of the present invention.

[0030] like Figure 1 As shown, the liquid flow conduction cyclic heat management method may include:

[0031] S110, for a first U-shaped heat exchange elbow in the fluid conduction system, design multiple candidate geometric structures of the U-shaped heat exchange elbow based on the U-shaped curvature radius and the inner wall corrugation structure, wherein the inner wall corrugation structure includes corrugation height, crest fillet radius, and trough transition length;

[0032] S120, performing flow field simulations based on each candidate geometric structure to obtain flow field distributions of the candidate U-shaped heat exchange elbow corresponding to each candidate geometric structure, wherein the flow field distributions include velocity field distribution, pressure field distribution, and turbulence intensity distribution;

[0033] S130, determining a correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow;

[0034] S140, optimizing and selecting each candidate geometric structure based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow to obtain a target geometric structure;

[0035] S150: Replace the first U-shaped heat exchange elbow in the fluid conduction system based on the target U-shaped heat exchange elbow corresponding to the target geometric structure.

[0036] It is understood that the fluid conduction system may include one or more U-shaped heat exchange elbows to perform heat exchange, for example, heating or cooling a space or equipment.

[0037] It can be understood that the first U-shaped heat exchange elbow is any U-shaped heat exchange elbow in the liquid flow conducting system.

[0038] It is understandable that for different candidate geometric structures, the U-shaped curvature radius and / or the inner wall corrugation structure are different. For different inner wall corrugation structures, at least one of the corrugation height, the crest fillet radius and the trough transition zone length may be different.

[0039] For example, for the candidate geometric structure, the corrugation height, peak fillet radius, trough transition zone length and U-shaped curvature radius with values ​​within the corresponding deviation range can be selected for the actual structure of the first U-shaped heat exchange elbow to obtain the candidate geometric structure.

[0040] For example, flow field simulation software may be used to execute step S110 to obtain the flow field distribution of each candidate U-shaped heat exchange elbow.

[0041] For example, a genetic algorithm or a particle swarm optimization algorithm may be used to optimize and select various candidate geometric structures based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow to obtain a target geometric structure.

[0042] For example, the mechanical device may be controlled to replace the first U-shaped heat exchange elbow with the target U-shaped heat exchange elbow in the fluid conduction system, thereby achieving cyclic thermal management.

[0043] According to the above embodiment, for the first U-shaped heat exchange bend in the liquid flow conduction system, multiple candidate geometric structures of the U-shaped heat exchange bend are designed, and flow field simulations are performed respectively to obtain the flow field distribution of the candidate U-shaped heat exchange bend corresponding to each candidate geometric structure. Based on the flow field distribution of each candidate U-shaped heat exchange bend, the correlation equation between the heat exchange bend structure and the local turbulence intensity can be determined. Then, based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange bend, each candidate geometric structure is optimized and selected to obtain a target geometric structure that can optimize the actual turbulence intensity distribution of the first U-shaped heat exchange bend and achieve the optimization target. In this way, based on the target U-shaped heat exchange bend corresponding to the target geometric structure, replacing the first U-shaped heat exchange bend in the liquid flow conduction system can reduce the turbulence intensity of the liquid flow conduction system and improve the heat transfer efficiency of the liquid flow conduction system.

[0044] In one embodiment, based on each candidate geometric structure, flow field simulation is performed respectively to obtain the flow field distribution of the U-shaped heat exchange bend corresponding to each candidate geometric structure, including: constructing a corresponding U-shaped bend model based on the candidate geometric structure; simulating the U-shaped bend model based on the preset calculation domain boundary conditions and the standard k-epsilon turbulence closed control equation group to obtain the velocity field distribution and pressure field distribution of the candidate U-shaped heat exchange bend corresponding to the candidate geometric structure; determining the velocity gradient tensor based on the velocity field distribution; calculating the velocity gradient tensor based on the turbulent kinetic energy transport equation to obtain the turbulence intensity distribution of the candidate U-shaped heat exchange bend; and determining the flow field distribution of the candidate U-shaped heat exchange bend based on the velocity field distribution, the pressure field distribution and the turbulence intensity distribution.

[0045] It can be understood that the velocity field distribution is the liquid flow velocity at each position in the U-shaped heat exchange elbow. The pressure field distribution is the pressure of the liquid flow on the elbow wall at each position in the U-shaped heat exchange elbow. The turbulence intensity distribution is the turbulence intensity at each position in the U-shaped heat exchange elbow.

[0046] For example, a candidate geometric structure is imported into the simulation software, so that a U-shaped bend pipe model can be constructed.

[0047] For example, a mesh is applied to the inner cavity of a U-bend pipe model. For example, the mesh size is gradually increased from 0.1 mm on the corrugated surface to 0.5 mm in the center, with the mesh quality factor kept above 0.85. A 12-layer structured mesh is generated from the corrugated surface toward the center of the pipe.

[0048] For example, the preset computational domain boundary conditions are input into the gridded U-shaped bend pipe model, and then the standard k-epsilon turbulence closed control equation group is selected in the simulation software, and the U-shaped bend pipe model is simulated, and the simulation results are the velocity field distribution and the pressure field distribution.

[0049] For example, the computational domain boundary conditions may include the inlet flow rate, outlet pressure, and corrugated wall friction factor of the elbow model. For example, the inlet flow rate is 5 to 20 liters per minute, the outlet pressure is 101 kPa, and the corrugated wall friction factor is 0.02.

[0050] Exemplarily, after the velocity field distribution is obtained, a gradient calculation is performed on the velocity field distribution to obtain a velocity gradient tensor.

[0051] For example, in simulation software, the turbulent kinetic energy transport equation is used to calculate the velocity gradient tensor and solve for the Reynolds stress tensor. The Reynolds stress tensor can be used to determine the turbulence intensity distribution of the candidate U-shaped heat exchange elbow.

[0052] Exemplarily, the flow field distribution of the candidate U-shaped heat exchange elbow includes velocity field distribution, pressure field distribution, and turbulence intensity distribution.

[0053] According to the above embodiment, the flow field distribution of each candidate U-shaped heat exchange elbow can be accurately simulated in the simulation software.

[0054] In one embodiment, based on the flow field distribution of each candidate U-shaped heat exchange bend, a correlation equation between the heat exchange bend structure and the local turbulence intensity is determined, including: for each candidate U-shaped heat exchange bend, the following operations are performed: the turbulence intensity distribution of the candidate U-shaped heat exchange bend is extracted from the flow field distribution of the candidate U-shaped heat exchange bend; a polynomial kernel function is used to map the candidate geometric structure of the candidate U-shaped heat exchange bend and the turbulence intensity distribution of the candidate U-shaped heat exchange bend to obtain a mapping relationship between each candidate U-shaped heat exchange bend and its turbulence intensity distribution; and a least squares method is used to fit the mapping relationship between each candidate U-shaped heat exchange bend and its turbulence intensity distribution to obtain a correlation equation between the heat exchange bend structure and the local turbulence intensity.

[0055] For example, the polynomial kernel function may adopt a corresponding kernel function order and penalty factor, and then perform the above fitting. For example, the kernel function order may be 4 or 5, and the penalty factor may be 0.001 or 0.004.

[0056] According to the above embodiment, a polynomial kernel function can be first used to fit the mapping relationship between each candidate U-shaped heat exchange elbow and its turbulence intensity distribution. Then, a least squares method can be used to fit the mapping relationship between each candidate U-shaped heat exchange elbow and its turbulence intensity distribution to obtain the correlation equation between the heat exchange elbow structure and the local turbulence intensity. In this way, the correlation equation between the heat exchange elbow structure and the local turbulence intensity can be accurately fitted.

[0057] In one embodiment, based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange bend, each candidate geometric structure is optimized and selected to obtain a target geometric structure, including: determining an initial population based on each candidate geometric structure, wherein the initial population includes multiple individuals, and each individual corresponds to a candidate U-shaped heat exchange bend corresponding to a candidate geometric structure; performing the following population iteration operation starting from the initial population: calculating the candidate geometric structure corresponding to each individual in this iterative population based on the correlation equation to obtain the predicted turbulence intensity distribution corresponding to each individual; determining the optimization degree of the candidate U-shaped heat exchange bend corresponding to each individual relative to the first U-shaped heat exchange bend based on the predicted turbulence intensity distribution corresponding to each individual and the actual turbulence intensity distribution of the first U-shaped heat exchange bend; when the optimization degree corresponding to each individual meets the preset conditions, determining the target geometric structure among the candidate geometric structures corresponding to each individual in this iterative population based on the optimization degree corresponding to each individual.

[0058] In one embodiment, the population iteration operation further includes: when the optimization degree corresponding to each individual does not meet the preset conditions, performing crossover mutation on the candidate geometric structures corresponding to each individual in the current iterative population to obtain the next iterative population.

[0059] For example, the candidate geometric structures corresponding to each individual in the sub-iteration population are input into the correlation equation respectively, and the predicted turbulence intensity distribution corresponding to each individual can be calculated.

[0060] Exemplarily, for each individual, the correspondence between each first position in the predicted turbulence intensity distribution corresponding to that individual and each second position in the actual turbulence intensity distribution of the first U-shaped heat exchange elbow is determined. For example, the distance between each first position and each second position is calculated to determine the correspondence between the first position and the second position with the closest distance. Then, for that individual, the degree of reduction in the predicted turbulence intensity at each first position relative to the actual predicted turbulence intensity at the corresponding second position is calculated. The calculated reduction degrees are averaged to determine the degree of optimization of the candidate U-shaped heat exchange elbow for that individual relative to the first U-shaped heat exchange elbow.

[0061] For example, if the optimization degree of each individual meets the preset optimization degree requirement, then the optimization degree corresponding to each individual is determined to meet the preset condition. Alternatively, if the minimum optimization degree among the optimization degrees of each individual is greater than a preset optimization degree threshold, then the optimization degree corresponding to each individual is determined to meet the preset condition.

[0062] Exemplarily, when the optimization degree corresponding to each individual meets the preset conditions, the candidate geometric structure corresponding to the individual with the maximum optimization degree in this iterative population is determined, and the candidate geometric structure is used as the target geometric structure.

[0063] For example, each structural parameter in the candidate geometric structure corresponding to each individual after crossover mutation needs to be within a preset range.

[0064] According to the above embodiment, the candidate geometric structures may be optimized through multiple iterations to obtain the target geometric result.

[0065] In one embodiment, the method further includes: monitoring the turbulence intensity of the liquid flow conduction system in which the first U-shaped heat exchange bend has been replaced with the target U-shaped heat exchange bend to obtain the actual turbulence intensity distribution of the target U-shaped heat exchange bend; if the actual turbulence intensity distribution of the target U-shaped heat exchange bend does not meet the preset conditions, returning to continue executing the above steps S140 and S150 to achieve cyclic thermal management.

[0066] According to the above embodiment, the turbulence intensity of the liquid flow conduction system can be monitored. When the actual turbulence intensity distribution of the target U-shaped heat exchange elbow does not meet the preset conditions, the U-shaped heat exchange elbow can be optimized to achieve cyclic thermal management and ensure the heat transfer efficiency of the liquid flow conduction system.

[0067] Figure 2 4 is a structural block diagram of a circulating thermal management device according to an embodiment of the present invention.

[0068] like Figure 2 As shown, the circulating thermal management device includes:

[0069] A candidate structure determination module 210 is configured to design, for a first U-shaped heat exchange elbow in a fluid conduction system, multiple candidate geometric structures of the U-shaped heat exchange elbow based on the U-shaped curvature radius and the inner wall corrugation structure, wherein the inner wall corrugation structure includes corrugation height, crest fillet radius, and trough transition zone length;

[0070] A flow field simulation module 220 is configured to perform flow field simulations based on each of the candidate geometric structures to obtain flow field distributions of the candidate U-shaped heat exchange elbow corresponding to each of the candidate geometric structures, wherein the flow field distributions include velocity field distribution, pressure field distribution, and turbulence intensity distribution;

[0071] A correlation equation determination module 230 is configured to determine a correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow;

[0072] a target structure determination module 240 for optimizing and selecting each of the candidate geometric structures based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow to obtain a target geometric structure;

[0073] The elbow replacement module 250 is configured to replace the first U-shaped heat exchange elbow in the fluid conduction system based on a target U-shaped heat exchange elbow corresponding to the target geometric structure.

[0074] In one embodiment, the flow field simulation module 220 includes:

[0075] A model building unit, configured to build a corresponding U-bend model based on the candidate geometric structure;

[0076] a first distribution determination unit, configured to perform simulation calculations on the U-shaped bend model based on preset computational domain boundary conditions and a standard k-epsilon turbulence closed control equation group, to obtain velocity field distribution and pressure field distribution of the candidate U-shaped heat exchange bend corresponding to the candidate geometric structure;

[0077] a gradient tensor determining unit, configured to determine a velocity gradient tensor based on the velocity field distribution;

[0078] a second distribution determining unit, configured to calculate the velocity gradient tensor based on a turbulent kinetic energy transport equation to obtain a turbulence intensity distribution of the candidate U-shaped heat exchange elbow;

[0079] The third distribution determination unit is configured to determine the flow field distribution of the candidate U-shaped heat exchange elbow based on the velocity field distribution, the pressure field distribution, and the turbulence intensity distribution.

[0080] In one embodiment, the correlation equation determination module 230 includes:

[0081] a mapping processing unit, configured to perform the following operations for each candidate U-shaped heat exchange bend: extracting the turbulence intensity distribution of the candidate U-shaped heat exchange bend from the flow field distribution of the candidate U-shaped heat exchange bend; and mapping the candidate geometric structure of the candidate U-shaped heat exchange bend and the turbulence intensity distribution of the candidate U-shaped heat exchange bend using a polynomial kernel function to obtain a mapping relationship between each candidate U-shaped heat exchange bend and its turbulence intensity distribution;

[0082] The fitting unit is used to fit the mapping relationship between each candidate U-shaped heat exchange elbow and its turbulence intensity distribution using the least square method to obtain a correlation equation between the heat exchange elbow structure and the local turbulence intensity.

[0083] In one embodiment, the target structure determination module 240 includes:

[0084] An initial population determining unit, configured to determine an initial population based on each of the candidate geometric structures, wherein the initial population includes a plurality of individuals, each of which corresponds to a candidate U-shaped heat exchange elbow corresponding to the candidate geometric structure;

[0085] The population iteration operation unit performs the following population iteration operations starting from the initial population:

[0086] Based on the correlation equation, the candidate geometric structures corresponding to each individual in the iterative population are calculated to obtain the predicted turbulence intensity distribution corresponding to each individual;

[0087] Determining the degree of optimization of the candidate U-shaped heat exchange bend corresponding to each of the individuals relative to the first U-shaped heat exchange bend based on the predicted turbulence intensity distribution corresponding to each of the individuals and the actual turbulence intensity distribution of the first U-shaped heat exchange bend;

[0088] When the degree of optimization corresponding to each of the individuals meets the preset conditions, a target geometric structure is determined among the candidate U-shaped heat exchange elbows corresponding to each of the individuals in this iterative population based on the degree of optimization corresponding to each of the individuals.

[0089] In one embodiment, the population iteration operation further includes:

[0090] When the optimization degree corresponding to each of the individuals does not meet the preset conditions, crossover mutation is performed on the candidate geometric structures corresponding to each individual in the current iterative population to obtain the next iterative population.

[0091] In one embodiment, the above device further comprises:

[0092] a turbulence monitoring module, configured to monitor turbulence intensity of the liquid flow conducting system in which the first U-shaped heat exchange elbow has been replaced with the target U-shaped heat exchange elbow, and obtain an actual turbulence intensity distribution of the target U-shaped heat exchange elbow;

[0093] The cyclic processing module is used to return to the following steps to implement cyclic thermal management when the actual turbulence intensity distribution of the target U-shaped heat exchange elbow does not meet the preset conditions:

[0094] Based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow, optimizing and selecting each of the candidate geometric structures to obtain a target geometric structure; and

[0095] The target U-shaped heat exchange elbow corresponding to the target geometric structure is used to replace the first U-shaped heat exchange elbow in the liquid flow conduction system.

[0096] For the description of specific functions and examples of each module and submodule of the device according to the embodiment of the present invention, reference can be made to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0097] In the technical solution of the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0098] According to an embodiment of the present invention, the present invention further provides a system and a readable storage medium.

[0099] Figure 3 A schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0100] like Figure 3As shown, device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. RAM 803 may also store various programs and data required for the operation of device 800. Computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to bus 804.

[0101] Various components in device 800 are connected to I / O interface 805, including an input unit 806, such as a keyboard, mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0102] The computing unit 801 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above, such as the fluid-conducting cyclical thermal management method. For example, in some embodiments, the fluid-conducting cyclical thermal management method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the fluid-conducting cyclical thermal management method described above can be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to execute the fluid-conducting cyclic thermal management method in any other appropriate manner (eg, by means of firmware).

[0103] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0104] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0105] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0106] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0107] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0108] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0109] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved. This is not limited herein.

[0110] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A circulating heat management method using liquid flow conduction, characterized in that: include: For a first U-shaped heat exchange elbow in a fluid conduction system, multiple candidate geometric structures of the U-shaped heat exchange elbow are designed based on the U-shaped curvature radius and the inner wall corrugation structure, wherein the inner wall corrugation structure includes the corrugation height, the crest fillet radius, and the trough transition zone length; Based on each of the candidate geometric structures, flow field simulations are performed to obtain flow field distributions of the candidate U-shaped heat exchange elbow corresponding to each of the candidate geometric structures, wherein the flow field distributions include velocity field distribution, pressure field distribution, and turbulence intensity distribution; Determining a correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow; Based on the association equation and the actual turbulence intensity distribution of the first U-shaped heat exchange bend, each of the candidate geometric structures is optimized and selected to obtain a target geometric structure, including: determining an initial population based on each of the candidate geometric structures, wherein the initial population includes multiple individuals, each of which corresponds to a candidate U-shaped heat exchange bend corresponding to the candidate geometric structure; performing the following population iteration operation starting from the initial population: based on the association equation, calculating the candidate geometric structure corresponding to each individual in this iterative population to obtain the predicted turbulence intensity distribution corresponding to each individual; determining the corresponding turbulence intensity distribution of each individual based on the predicted turbulence intensity distribution corresponding to each individual and the actual turbulence intensity distribution of the first U-shaped heat exchange bend. The degree of optimization of the candidate U-shaped heat exchange bend relative to the first U-shaped heat exchange bend includes: determining, for each individual, a correspondence between each first position in the predicted turbulence intensity distribution corresponding to the individual and each second position in the actual turbulence intensity distribution of the first U-shaped heat exchange bend, and calculating the degree of reduction of the predicted turbulence intensity at each first position relative to the actual predicted turbulence intensity at the corresponding second position; averaging the calculated reduction degrees to obtain the degree of optimization of the candidate U-shaped heat exchange bend of the individual relative to the first U-shaped heat exchange bend; and determining, based on the degree of optimization corresponding to each individual, a target geometric structure among the candidate U-shaped heat exchange bends corresponding to each individual in this iterative population when the degree of optimization corresponding to each individual meets a preset condition; The first U-shaped heat exchange elbow in the fluid conducting system is replaced based on a target U-shaped heat exchange elbow corresponding to the target geometric structure.

2. The method according to claim 1, characterized in that The flow field simulation is performed based on each of the candidate geometric structures to obtain the flow field distribution of the U-shaped heat exchange elbow corresponding to each of the candidate geometric structures, including: Based on the candidate geometric structure, construct a corresponding U-shaped bend pipe model; Based on the preset computational domain boundary conditions and the standard k-epsilon turbulence closed control equations, the U-shaped elbow model is simulated and calculated to obtain the velocity field distribution and pressure field distribution of the candidate U-shaped heat exchange elbow corresponding to the candidate geometric structure; determining a velocity gradient tensor based on the velocity field distribution; Calculating the velocity gradient tensor based on the turbulent kinetic energy transport equation to obtain the turbulence intensity distribution of the candidate U-shaped heat exchange elbow; Based on the velocity field distribution, the pressure field distribution, and the turbulence intensity distribution, the flow field distribution of the candidate U-shaped heat exchange elbow is determined.

3. The method according to claim 1, characterized in that Determining the correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow comprises: For each candidate U-shaped heat exchange elbow, the following operations are performed: extracting the turbulence intensity distribution of the candidate U-shaped heat exchange elbow from the flow field distribution of the candidate U-shaped heat exchange elbow; using a polynomial kernel function, mapping the candidate geometric structure of the candidate U-shaped heat exchange elbow and the turbulence intensity distribution of the candidate U-shaped heat exchange elbow to obtain a mapping relationship between each candidate U-shaped heat exchange elbow and its turbulence intensity distribution; The least square method is used to fit the mapping relationship between each candidate U-shaped heat exchange elbow and its turbulence intensity distribution, and a correlation equation between the heat exchange elbow structure and the local turbulence intensity is obtained.

4. The method according to claim 1, wherein The population iteration operation further includes: When the optimization degree corresponding to each of the individuals does not meet the preset conditions, crossover mutation is performed on the candidate geometric structures corresponding to each individual in the current iterative population to obtain the next iterative population.

5. The method according to any one of claims 1 to 4, characterized in that Also includes: performing turbulence intensity monitoring on the liquid flow conducting system in which the first U-shaped heat exchange elbow has been replaced with the target U-shaped heat exchange elbow to obtain an actual turbulence intensity distribution of the target U-shaped heat exchange elbow; When the actual turbulence intensity distribution of the target U-shaped heat exchange elbow does not meet the preset conditions, return to the following steps to achieve cyclic thermal management: Based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow, optimizing and selecting each of the candidate geometric structures to obtain a target geometric structure; and The target U-shaped heat exchange elbow corresponding to the target geometric structure is used to replace the first U-shaped heat exchange elbow in the liquid flow conduction system.

6. A liquid flow conduction circulating heat management device, characterized in that: include: a candidate structure determination module for designing, for a first U-shaped heat exchange elbow in a fluid conduction system, multiple candidate geometric structures of the U-shaped heat exchange elbow based on the U-shaped curvature radius and the inner wall corrugation structure, wherein the inner wall corrugation structure includes corrugation height, crest fillet radius, and trough transition zone length; A flow field simulation module is used to perform flow field simulation based on each of the candidate geometric structures to obtain the flow field distribution of the candidate U-shaped heat exchange elbow corresponding to each of the candidate geometric structures, wherein the flow field distribution includes velocity field distribution, pressure field distribution and turbulence intensity distribution; A correlation equation determination module, configured to determine a correlation equation between the heat exchange elbow structure and the local turbulence intensity based on the flow field distribution of each candidate U-shaped heat exchange elbow; a target structure determination module, configured to optimize and select each of the candidate geometric structures based on the correlation equation and the actual turbulence intensity distribution of the first U-shaped heat exchange elbow to obtain a target geometric structure; a pipe elbow replacement module, configured to replace the first U-shaped heat exchange pipe elbow in the fluid conduction system based on a target U-shaped heat exchange pipe elbow corresponding to the target geometric structure; The target structure determination module 240 includes: An initial population determining unit, configured to determine an initial population based on each of the candidate geometric structures, wherein the initial population includes a plurality of individuals, each of which corresponds to a candidate U-shaped heat exchange elbow corresponding to the candidate geometric structure; The population iteration operation unit performs the following population iteration operations starting from the initial population: Based on the correlation equation, the candidate geometric structures corresponding to each individual in the iterative population are calculated to obtain the predicted turbulence intensity distribution corresponding to each individual; Based on the predicted turbulence intensity distribution corresponding to each of the individuals and the actual turbulence intensity distribution of the first U-shaped heat exchange bend, determining the degree of optimization of the candidate U-shaped heat exchange bend corresponding to each of the individuals relative to the first U-shaped heat exchange bend, including: for each individual, determining the corresponding relationship between each first position in the predicted turbulence intensity distribution corresponding to the individual and each second position in the actual turbulence intensity distribution of the first U-shaped heat exchange bend, calculating the degree of reduction of the predicted turbulence intensity at each first position relative to the actual predicted turbulence intensity at the corresponding second position; averaging the calculated respective reduction degrees to obtain the degree of optimization of the candidate U-shaped heat exchange bend of the individual relative to the first U-shaped heat exchange bend; When the degree of optimization corresponding to each of the individuals meets the preset conditions, a target geometric structure is determined among the candidate U-shaped heat exchange elbows corresponding to each of the individuals in this iterative population based on the degree of optimization corresponding to each of the individuals.

7. The device according to claim 6, characterized in that The flow field simulation module includes: A model building unit, configured to build a corresponding U-bend model based on the candidate geometric structure; a first distribution determination unit, configured to perform simulation calculations on the U-shaped bend model based on preset computational domain boundary conditions and a standard k-epsilon turbulence closed control equation group, to obtain velocity field distribution and pressure field distribution of the candidate U-shaped heat exchange bend corresponding to the candidate geometric structure; a gradient tensor determining unit, configured to determine a velocity gradient tensor based on the velocity field distribution; a second distribution determining unit, configured to calculate the velocity gradient tensor based on a turbulent kinetic energy transport equation to obtain a turbulence intensity distribution of the candidate U-shaped heat exchange elbow; The third distribution determination unit is configured to determine the flow field distribution of the candidate U-shaped heat exchange elbow based on the velocity field distribution, the pressure field distribution, and the turbulence intensity distribution.

8. A liquid flow conduction circulating heat management system comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

9. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 5.

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