Liquid cooling plate flow channel design method and device, storage medium and electronic equipment
By optimizing the flow channel design method, adjusting the fluid permeability and filter channel distribution, and combining topology optimization and an accurate objective function, the problem of poor heat dissipation in the flow channel design of liquid cooling plates was solved, and better actual heat dissipation effect was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2026-03-31
AI Technical Summary
Existing liquid cooling plate flow channel design methods result in heat dissipation effects that fail to meet expectations, especially when fabricating thin electronic devices.
By adjusting the fluid permeability and filtering the channel distribution, combined with topology optimization, the material density value in the channel distribution is optimized to ensure that the number of values between 0 and 1 meets the threshold. The channel shape is optimized using parameters such as the Darcy penalty function, hyperbolic tangent projection slope, and filtration radius, and an accurate heat transfer and flow objective function is established to improve design accuracy.
This reduces the deviation between the design results and the actual manufacturing results, improves the heat dissipation effect of the liquid cooling plate, and makes it closer to the expected heat dissipation performance.
Smart Images
Figure CN121765880A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of heat dissipation technology, and more specifically, to a liquid cooling plate flow channel design method, a liquid cooling plate flow channel design device, a storage medium, and an electronic device. Background Technology
[0002] As people's demands for the performance of electronic devices continue to increase, heat dissipation has gradually become a key concern. Traditional heat dissipation technology involves designing flow channels on a liquid cooling plate, where the flow of fluid carries away the heat from the heat-generating areas of the electronic device.
[0003] However, the heat dissipation effect of liquid cooling plates manufactured using the existing flow channel design methods does not meet expectations. Therefore, there is an urgent need to provide a new flow channel design method for liquid cooling plates to improve their actual heat dissipation performance. Summary of the Invention
[0004] This application provides a liquid cooling plate flow channel design method, a liquid cooling plate flow channel design device, a storage medium, and an electronic device. The liquid cooling plate designed by the method of this application provides a heat dissipation effect that is closer to the expectation.
[0005] In a first aspect, this embodiment provides a liquid cooling plate flow channel design method, applied to electronic devices, including:
[0006] Obtain the first flow channel distribution of the liquid cooling plate, wherein the first number of target values of the material density corresponding to the first flow channel distribution is greater than a threshold, and the target value is between 0 and 1;
[0007] Obtain the adjustment value of the target parameter, which includes at least one of a first parameter for adjusting the fluid permeability and a second parameter for filtering the first flow channel distribution;
[0008] Based on the adjustment value of the target parameter, the topology of the first flow channel distribution is optimized to determine the target flow channel distribution of the liquid cooling plate.
[0009] Optionally, the step of performing topology optimization on the first flow channel distribution based on the adjustment value of the target parameter to determine the target flow channel distribution of the liquid cooling plate includes:
[0010] Based on the adjustment value of the target parameter, update the first flow channel distribution to the second flow channel distribution;
[0011] Obtain a second number of target values for the material density corresponding to the second flow channel distribution;
[0012] If the second quantity is less than the threshold, the target flow channel distribution is determined based on the second flow channel distribution.
[0013] Optionally, the first parameter includes the Darcy penalty function, and the second parameter includes the hyperbolic tangent projection slope and / or the filter radius.
[0014] Optionally, the second parameter includes the hyperbolic tangent projection slope and the filter radius. The step of performing topology optimization on the first flow channel distribution based on the adjustment value of the target parameter to determine the target flow channel distribution of the liquid cooling plate includes:
[0015] Based on the adjustment value of the Darcy penalty function, the first flow channel distribution is topologically optimized to obtain the third flow channel distribution;
[0016] If the number of target values for material density corresponding to the third flow channel distribution is greater than the threshold, the fourth flow channel distribution is obtained according to the adjustment value of the hyperbolic tangent projection slope.
[0017] If the number of target values for material density corresponding to the fourth flow channel distribution is greater than the threshold, the fifth flow channel distribution is obtained based on the adjustment value of the filtration radius;
[0018] The target flow channel distribution is determined based on the fifth flow channel distribution.
[0019] Optionally, the step of performing topology optimization on the first flow channel distribution based on the adjustment value of the target parameter to determine the target flow channel distribution of the liquid cooling plate includes:
[0020] Obtain an objective function, which includes any one of a heat transfer objective function, a flow objective function, and a coupling objective function. The coupling objective function is the objective function obtained by coupling the heat transfer objective function and the flow objective function. The heat transfer objective function is determined based on at least one of the ambient temperature and the heat generation coefficient of the heat source corresponding to the liquid cooling plate. The flow objective function is determined based on at least one of the first fluid flow velocity corresponding to each grid in the flow channel distribution and the fluid domain proportion corresponding to each grid. The first fluid flow velocity includes horizontal velocity and vertical velocity.
[0021] Based on the value of the objective function and the adjustment value of the objective parameter, the topology of the first flow channel distribution is optimized to determine the target flow channel distribution of the liquid cooling plate.
[0022] Optionally, obtaining the target function includes:
[0023] Based on at least one of the ambient temperature and the heat generation coefficient, the temperature field information corresponding to the flow channel distribution is determined, and the temperature field information includes the temperature at each grid in the flow channel distribution.
[0024] The objective function is determined based on the maximum and minimum temperatures in the temperature field information and the temperature of the set grid.
[0025] Alternatively, the acquisition of the target function includes:
[0026] Based on at least one of the first fluid flow velocity corresponding to each grid and the fluid domain proportion corresponding to each grid, the velocity field information corresponding to the flow channel distribution is determined, and the velocity field information includes the second fluid flow velocity of each grid in the flow channel distribution.
[0027] Based on the second fluid flow velocity, a third fluid flow velocity is determined, wherein the third fluid flow velocity characterizes the fluid flow velocity corresponding to the flow channel distribution;
[0028] The objective function is determined based on the preset maximum fluid flow velocity, the preset minimum fluid flow velocity, and the third fluid flow velocity.
[0029] Optionally, obtaining the target function includes:
[0030] Obtain the sum of the squares of the horizontal velocity and the squares of the vertical velocity;
[0031] The objective function is determined by the product of the sum of the squares of the horizontal velocity and the squares of the vertical velocity and the proportion of the fluid domain.
[0032] or,
[0033] The method for obtaining the target function includes:
[0034] The ambient temperature, the heat generation coefficient, and the temperature of the grid set in the flow channel distribution are obtained;
[0035] The objective function is determined by multiplying the difference between the ambient temperature and the temperature of the set grid with the heat generation coefficient.
[0036] Secondly, this embodiment provides a liquid-cooled plate flow channel design device, including:
[0037] The first acquisition module is used to acquire the first flow channel distribution of the liquid cooling plate, wherein the first number of the target values of the material density corresponding to the first flow channel distribution is greater than a threshold, and the target value is between 0 and 1.
[0038] The second acquisition module is used to acquire the adjustment value of the target parameter, wherein the target parameter includes at least one of a first parameter for adjusting the fluid permeability and a second parameter for filtering the first flow channel distribution.
[0039] The determination module is used to perform topology optimization on the first flow channel distribution based on the adjustment value of the target parameter, and determine the target flow channel distribution of the liquid cooling plate.
[0040] Thirdly, this embodiment provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of the first aspects of this application.
[0041] Fourthly, this embodiment provides an electronic device, including a memory and a processor, wherein the memory is used to store computer instructions, and the processor is used to invoke the computer instructions from the memory to perform the method as described in any one of the first aspects of this application.
[0042] This application embodiment achieves topology optimization for regions with material density values between 0 and 1 in the initial flow channel distribution by adjusting the fluid permeability corresponding to the initial first flow channel distribution and / or filtering the initial flow channel distribution. This ensures that the number of material density values between 0 and 1 in the optimized target flow channel distribution meets a threshold, thereby reducing the deviation between the design result and the manufacturing result. As a result, the heat dissipation effect of the liquid cooling plate obtained in actual processing is closer to the expectation, and the actual heat dissipation effect is better than that of liquid cooling plates in the prior art.
[0043] Other features and advantages of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description
[0044] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the present application and, together with their description, serve to explain the principles of the present application.
[0045] Figure 1 A schematic diagram of the design domain provided in an embodiment of this application is shown.
[0046] Figure 2 A schematic flowchart of a liquid cooling plate flow channel design method provided in an embodiment of this application is shown.
[0047] Figure 3 A schematic diagram of the flow channel distribution provided in an embodiment of this application is shown.
[0048] Figure 4 A schematic flowchart of a liquid cooling plate flow channel design method provided in another embodiment of this application is shown.
[0049] Figure 5 A schematic block diagram of the liquid cooling plate flow channel design device provided in an embodiment of this application is shown.
[0050] Figure 6 A schematic block diagram of an electronic device provided in an embodiment of this application is shown. Detailed Implementation
[0051] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present application.
[0052] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.
[0053] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.
[0054] In all the examples shown and discussed herein, any specific values should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.
[0055] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.
[0056] As people's demands for the performance of electronic devices continue to increase, heat dissipation has gradually become a key concern. Traditional heat dissipation technology involves designing flow channels on a liquid cooling plate, where the flow of fluid carries away the heat from the heat-generating areas of the electronic device.
[0057] However, the heat dissipation effect of liquid cooling plates manufactured using the existing flow channel design methods does not meet expectations. Therefore, there is an urgent need to provide a new flow channel design method for liquid cooling plates to improve their actual heat dissipation performance.
[0058] To facilitate understanding of the liquid cooling plate flow channel design method of this application, the process of liquid cooling plate flow channel design will be briefly introduced first.
[0059] First, define the design domain and boundary conditions of the liquid cooling plate, and assign material properties to the fluid and solid components. The design domain is the area where the liquid cooling plate flow channels are designed. The design domain can be a completely solid region of a specific size, a partially solid and partially fluid region, or a completely fluid region. The fluid domain is the area where fluids (such as coolant) can flow, and the solid domain is the area where flow channel support pillars can be installed. The design domain has specific fluid and solid domains, which can be understood as requiring further flow channel optimization design based on a specific flow channel. Material properties include material density, heat source heat generation coefficient, viscosity, specific heat capacity, etc. The density of the fluid can be set to 1, and the density of the solid can be set to 0. The heat source heat generation coefficient is a physical quantity describing the rate of heat generation per unit area; it is commonly used to evaluate the heat generation capability of electronic devices under specific conditions. Electronic devices with different power ratings have different heat source heat generation coefficients. Boundary conditions can include the velocity, pressure, and temperature of the fluid flow at the flow channel inlet and outlet.
[0060] Secondly, divide the design domain into an appropriate number of meshes to ensure that the meshes in the flow channels and critical areas are fine enough to capture details, while avoiding excessive subdivision that would waste computational resources. Figure 1 A simplified schematic diagram of a design domain provided in an embodiment of this application is shown. Figure 1 The design domain A is divided into 25 grids, and the region corresponding to each grid is configured as either a fluid domain (the region corresponding to "1" in the figure) or a solid domain (the region corresponding to "0" in the figure).
[0061] Next, set the objective function and constraints. The objective function can be determined based on the performance indicators indicated in the design requirements. For example, the objective function can be determined based on at least one of the flow channel heat exchange efficiency, flow rate, and pressure drop indicated in the design requirements. Constraints may include volume ratio. The volume ratio is used to limit the flow channel volume to a certain proportion of the design domain.
[0062] Finally, within the design domain, topology optimization is automatically performed based on the objective function, boundary conditions, and constraints to adjust the density distribution of the solid and fluid domains, resulting in an optimized flow channel distribution map. This process typically involves multiple iterations to ensure that the performance of the optimized flow channel distribution meets the design requirements.
[0063] While the performance results of the flow channel distribution simulated by the algorithm meet the design requirements, this does not necessarily mean that the performance results of the flow channels actually manufactured according to that distribution will also meet the design requirements. The applicant's analysis revealed that, compared to conventional large-size liquid cooling plates, the liquid cooling plates for electronic devices are extremely thin, for example, only about 0.4 mm thick. On such thin liquid cooling plates, the flow channel distribution simulated by the topology optimization algorithm typically has a large number of material density values between 0 and 1. In actual manufacturing, these areas with material density values between 0 and 1 will be treated as solid regions, leading to a significant difference between the actually manufactured flow channels and the simulated flow channels.
[0064] Based on this, embodiments of this application provide a liquid cooling plate flow channel design method for electronic devices. For example... Figure 2 As shown, the method may include steps S110 to S130.
[0065] Step S110: Obtain the first flow channel distribution of the liquid cooling plate, wherein the first number of target values of the material density corresponding to the first flow channel distribution is greater than a threshold, and the target value is between 0 and 1.
[0066] In this embodiment, the first flow channel distribution can be obtained by topology optimization based on an all-solid initial design domain, or by topology optimization based on an all-fluid initial design domain, or by topology optimization based on a specific initial design domain, or it can be directly obtained from an existing flow channel distribution library. The method of obtaining the first flow channel distribution is not specifically limited here.
[0067] The first channel distribution characterizes the path of fluid flow. As an example, Figure 3 A partial schematic diagram of the flow channel distribution is shown. In this distribution, region B, with a material density value of 1, is the fluid region, forming the flow channel. Regions with a material density value of 0 are solid regions. Regions with material density values between 0 and 1 are porous media regions. Since the porous media regions will be processed into solid regions during actual processing, it is necessary to identify the number of material density values between 0 and 1. In this embodiment, material density values between 0 and 1 are used as target values. First, the number of target values is identified. If the number of target values exceeds a threshold, it indicates that the current flow channel distribution needs further optimization to adjust the number of target values to below the threshold.
[0068] The threshold value can be determined based on the proportion of the area corresponding to the pre-set target value within the design domain. This embodiment does not limit the specific value of this proportion; it can be determined based on the performance differences between the actual processed flow channel and the simulated flow channel. A lower proportion can be set when the required performance difference is small.
[0069] Step S120: Obtain the adjustment value of the target parameter, wherein the target parameter includes at least one of a first parameter for adjusting the fluid permeability and a second parameter for filtering the first flow channel distribution.
[0070] Step S130: Based on the adjustment value of the target parameter, perform topology optimization on the first flow channel distribution to determine the target flow channel distribution of the liquid cooling plate.
[0071] Fluid permeability is an important parameter describing the ease with which a fluid flows in a porous medium. When the number of identified target values exceeds a threshold, the fluid permeability can be adjusted by changing the value of the first parameter, thereby updating the first flow channel distribution to a second flow channel distribution.
[0072] After obtaining the updated second flow channel distribution, the second flow channel distribution can be further updated by adjusting the second parameter to filter it.
[0073] Filtering the flow channel distribution typically involves applying mathematical or physical rules to smooth and simplify its shape, causing the material density value corresponding to the flow channel distribution to approach 0 or 1. This results in a clear boundary between the fluid and solid domains, improving processing efficiency. As an example, the second parameter can be a flow channel length filtering parameter. By limiting the length or width of the flow channel, flow channels that are difficult to process are avoided. The second parameter can also be a shape filtering parameter. Shape rules are used to optimize the geometry of the flow channel, for example, avoiding sharp angles and corners, making the flow channel smoother and more continuous. The second parameter can also be a topology filtering parameter, such as the slope of the hyperbolic tangent projection, or the filtering radius.
[0074] In this embodiment, the first parameter may include the Darcy penalty function, and the second parameter may include the hyperbolic tangent projection slope and / or the filtering radius. The Darcy penalty function is adjusted from 0 to 10. When the material density value is between 0 and 1, the intermediate density value is penalized, causing the intermediate density value to gradually converge towards either 0 or 1. This allows the topology optimization model of continuous variables to better approximate the optimization model of discrete variables of 0 or 1. The smaller the value of this parameter, the closer the intermediate density is to 0 or 1. The hyperbolic tangent projection slope is used to filter the overall design domain, and its adjustment range is 1 to 32. The larger the value of this parameter, the better the filtering effect. The filtering radius is adjusted from 0 to 1 m. By adjusting the value of this parameter, a checkerboard pattern in the flow channel distribution can be avoided, i.e., more complete solid walls are presented, leading to discontinuous flow channels.
[0075] If the number of target values exceeds the threshold, the value of the target parameter is adjusted. Based on the value of the target parameter, the topology of the first flow channel distribution is optimized. Through continuous iteration, the target flow channel distribution is obtained.
[0076] In this embodiment, step S130 may include steps S131 to S133.
[0077] Step S131: Update the first flow channel distribution to the second flow channel distribution according to the adjustment value of the target parameter.
[0078] Step S132: Obtain the second quantity of the target value of the material density corresponding to the second flow channel distribution.
[0079] Step S133: If the second quantity of the target value of the material density is less than the threshold, determine the target flow channel distribution based on the second flow channel distribution.
[0080] In this embodiment, the step of determining the target flow channel distribution based on the second flow channel distribution in step S133 can be further optimized using any flow channel distribution optimization method to determine the target flow channel distribution. For example, the topology optimization method can be used to obtain the target flow channel distribution.
[0081] This application embodiment achieves topology optimization for regions with material density values between 0 and 1 in the initial flow channel distribution by adjusting the fluid permeability corresponding to the initial first flow channel distribution and / or filtering the initial flow channel distribution. This ensures that the number of material density values between 0 and 1 in the optimized target flow channel distribution meets a threshold, thereby reducing the deviation between the design result and the manufacturing result. As a result, the heat dissipation effect of the liquid cooling plate obtained in actual processing is closer to the expectation, and the actual heat dissipation effect is better than that of liquid cooling plates in the prior art.
[0082] In some embodiments, the order of adjusting the target parameters can be set according to the degree of influence of the target parameters on the channel topology optimization results. In this embodiment, the first parameter can be adjusted first, and the first channel distribution can be topologically optimized based on the adjusted value of the first parameter to obtain the updated channel distribution. If the number of target values for material density corresponding to the updated channel distribution is greater than a threshold, the second parameter can be adjusted further.
[0083] Specifically, step S130 may include steps S135 to S138.
[0084] Step S135: Based on the adjustment value of the Darcy penalty function, perform topology optimization on the first flow channel distribution to obtain the third flow channel distribution.
[0085] Step S136: If the number of target values of material density corresponding to the third flow channel distribution is greater than the threshold, the fourth flow channel distribution is obtained according to the adjustment value of the hyperbolic tangent projection slope.
[0086] Step S137: If the number of target values of material density corresponding to the fourth flow channel distribution is greater than the threshold, the fifth flow channel distribution is obtained according to the adjustment value of the filter radius.
[0087] Step S138: Determine the target flow channel distribution based on the fifth flow channel distribution.
[0088] In this embodiment, step S138 may include: if the number of target values of material density corresponding to the fifth flow channel distribution is greater than a threshold, adjusting the size of the grid corresponding to the fifth flow channel distribution to obtain the sixth flow channel distribution; if the number of target values of material density corresponding to the sixth flow channel distribution is less than a threshold, determining the target flow channel distribution based on the sixth flow channel distribution.
[0089] This application embodiment sets the adjustment order priority for the target parameter. If the flow channel distribution updated according to the adjustment value of the first parameter meets the requirements, there is no need to continue adjusting the target parameter, which can reduce the waste of resources.
[0090] In some embodiments, simply adjusting the values of the target parameters is insufficient to obtain a flow channel distribution that meets the design requirements. This is because the accuracy of the objective function used in the relevant flow channel design scheme is insufficient to reflect the true performance. Therefore, this embodiment establishes a new objective function based on the design requirements. Typically, design requirements include the heat transfer efficiency of the flow channel, fluid velocity, etc. This embodiment establishes new heat transfer objective functions and flow objective functions based on the design requirements of the heat transfer efficiency and fluid velocity of the flow channel, respectively, to improve the accuracy of the objective function values.
[0091] For the heat transfer objective function, related technologies first use finite element method (FEM) to simulate the temperature field information corresponding to the flow channel distribution. This temperature field information includes the temperature at each grid point in the flow channel distribution. The temperature corresponding to this simulated physical field information is directly used to calculate the heat transfer objective function. However, in practical applications of liquid-cooled plate flow channels, the temperature of the liquid-cooled plate is also affected by the ambient temperature and the heat generation coefficient of the heat source. Therefore, the value of the heat transfer objective function calculated directly using the simulated temperature is obviously not accurate enough. Thus, in this embodiment, the heat transfer objective function is determined based on at least one of the ambient temperature and the heat generation coefficient of the heat source corresponding to the liquid-cooled plate, in order to improve the accuracy of the heat transfer objective function value.
[0092] For the flow objective function, related technologies also directly utilize finite element analysis to obtain the velocity field information corresponding to the flow channel distribution to calculate the flow objective function. This velocity field information includes the horizontal velocity at each grid in the flow channel distribution. However, in the simulation calculation of liquid-cooled plate flow channels, fluid velocity is a two-dimensional variable, including not only horizontal velocity but also vertical velocity. The value of the flow objective function calculated directly using the horizontal velocity is obviously not accurate enough. In addition, in the simulation calculation, each grid in the flow channel distribution is not necessarily entirely a solid region or a fluid region, but includes a portion of solid regions and a portion of fluid regions. Therefore, using the flow velocity calculated using the entire fluid region as the flow velocity corresponding to the grid that only includes a portion of the fluid region will also result in inaccurate calculation results. Therefore, in this embodiment, the flow objective function is determined based on at least one of the first fluid flow velocity corresponding to each grid in the flow channel distribution, which includes both horizontal and vertical velocities, and the fluid domain proportion corresponding to each grid, in order to improve the accuracy of the flow objective function value.
[0093] In this embodiment, step S130 may further include steps S210 to S220.
[0094] Step S210: Obtain the objective function, which includes any one of the heat transfer objective function, the flow objective function, and the coupling objective function. The coupling objective function is the objective function obtained by coupling the heat transfer objective function and the flow objective function.
[0095] The coupling objective function can be obtained by weighted summation of the heat transfer objective function and the flow objective function. The formula for the coupling objective function F can be:
[0096] F = a*A + b*B
[0097] Where A is the heat transfer objective function, a is the weight of the heat transfer objective function, B is the flow objective function, and b is the weight of the flow objective function.
[0098] Optionally, based on experience, specific weights can be pre-set for the heat transfer objective function and the flow objective function to obtain a coupled objective function.
[0099] Optionally, during the topology optimization iteration process, the weights can be updated based on the quality of the current objective function value after each iteration. For example, if the heat transfer objective function value has reached a good level in the current iteration, the weight of that heat transfer objective function can be reduced, while the weight of the flow objective function can be increased. This approach allows the algorithm to explore the solution space more flexibly, avoiding premature focus on a specific objective, thus helping to find a flow channel distribution that is closer to the design requirements.
[0100] Step S220: Based on the value of the objective function and the adjustment value of the objective parameter, perform topology optimization on the first flow channel distribution to determine the target flow channel distribution of the liquid cooling plate.
[0101] In this embodiment, based on the adjusted value of the target parameter, the value of the first objective function corresponding to the first flow channel distribution is calculated. When the value of the first objective function does not meet the preset target, the flow channel distribution is updated in the next iteration. Then, based on the adjusted value of the target parameter, the value of the second objective function corresponding to the updated flow channel distribution is calculated. When the value of the second objective function does not meet the preset target or the change in the value of the second objective function compared to the value of the objective function corresponding to the previous iteration is greater than a threshold, the next iteration is continued until the value of the objective function meets the preset target or the change in the value of the objective function compared to the value of the objective function corresponding to the previous iteration is less than a threshold. The flow channel distribution at this time is taken as the target flow channel distribution.
[0102] The objective function established by the method in the embodiments of this application has a more accurate objective function value when performing topology optimization, and can obtain a flow channel distribution that is closer to the design requirements.
[0103] In some embodiments, step S210 may include steps S211 to S212.
[0104] Step S211: Determine the temperature field information corresponding to the flow channel distribution based on at least one of the ambient temperature and the heat generation coefficient of the heat source. The temperature field information includes the temperature at each grid in the flow channel distribution.
[0105] In this embodiment, optionally, new temperature field information corresponding to the flow channel distribution can be determined based on at least one of the ambient temperature and the heat generation coefficient of the heat source. The new temperature field information replaces the temperature field information directly obtained through finite element simulation in the existing objective function, thereby determining the objective function.
[0106] Optionally, in step S212, the objective function is determined based on the maximum temperature, minimum temperature, and set grid temperature in the temperature field information obtained in step S211.
[0107] In some embodiments, step S210 may include steps S213 to S214.
[0108] Step S213: Obtain the ambient temperature, the heat generation coefficient of the heat source, and the temperature of the grid set in the flow channel distribution.
[0109] Step S214: Determine the objective function based on the product of the difference between the ambient temperature and the set grid temperature and the heat generation coefficient of the heat source.
[0110] In this embodiment, step S214 can use the product of the difference between the ambient temperature and the temperature of the set grid and the heat generation coefficient of the heat source as the temperature corresponding to each grid, and determine the objective function based on the temperature.
[0111] As an example, the formula for the heat transfer objective function A can be:
[0112]
[0113] Where Ta = theta*(TQ-T), theta is the heat generation coefficient of the heat source, TQ is the ambient temperature, and T is the temperature obtained by finite element calculation for each grid.
[0114] In some embodiments, step S210 may include steps S215 to S217.
[0115] Step S215: Determine the velocity field information corresponding to the flow channel distribution based on at least one of the first fluid flow velocity corresponding to each grid and the fluid domain proportion corresponding to each grid. The velocity field information includes the second fluid flow velocity of each grid in the flow channel distribution.
[0116] Step S216: Determine the third fluid flow velocity based on the second fluid flow velocity, wherein the third fluid flow velocity characterizes the fluid flow velocity corresponding to the flow channel distribution.
[0117] In this embodiment, the second fluid flow velocity is the fluid flow velocity corresponding to each grid in the channel distribution, and the third fluid flow velocity characterizes the global fluid flow velocity corresponding to the channel distribution. As an example, the third fluid flow velocity can be obtained by summing the second fluid flow velocities. As another example, the third fluid flow velocity can be obtained by integrating the second fluid flow velocities.
[0118] Step S217: Determine the objective function based on the preset maximum fluid flow velocity, the preset minimum fluid flow velocity, and the third fluid flow velocity.
[0119] In this embodiment, the maximum fluid flow velocity and the minimum fluid flow velocity can be preset based on experience, and used to determine the objective function in step S216.
[0120] In some embodiments, step S210 may include steps S218 to S219.
[0121] Step S218: Obtain the sum of the squares of the horizontal velocity and the squares of the vertical velocity corresponding to each grid.
[0122] Step S219: Determine the objective function based on the product of the sum of the squares of the horizontal and vertical velocities and the proportion of the fluid domain.
[0123] In this embodiment, in step S219, the product of the square of the horizontal velocity and the square of the vertical velocity, and the proportion of the fluid domain, can be used as the second fluid flow velocity corresponding to each grid. Based on this second fluid flow velocity, the objective function is determined.
[0124] As an example, the formula for the flow objective function B can be:
[0125]
[0126] Where Fa=∑(1-r)*(u2+v2), r is the proportion of solid volume in the mesh to the mesh volume, (1-r) is the proportion of fluid volume in the mesh to the mesh volume, i.e. fluid domain proportion, u is horizontal velocity, and v is vertical velocity.
[0127] This application also provides a liquid cooling plate flow channel design device. For example... Figure 5 As shown, the device 100 includes a first acquisition module, a second acquisition module, and a determination module.
[0128] The first acquisition module is used to acquire the first flow channel distribution of the liquid cooling plate, wherein the first number of target values of the material density corresponding to the first flow channel distribution is greater than a threshold, and the target value is between 0 and 1.
[0129] The second acquisition module is used to acquire the adjustment value of the target parameter, which includes at least one of a first parameter for adjusting the fluid permeability and a second parameter for filtering the first flow channel distribution.
[0130] The determination module is used to perform topology optimization on the first flow channel distribution based on the adjustment value of the target parameter, and determine the target flow channel distribution of the liquid cooling plate.
[0131] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the method as described in any of the above method embodiments.
[0132] This application also provides an electronic device, such as... Figure 6 As shown, the electronic device 200 includes a memory 210 and a processor 220.
[0133] The memory 210 is used to store computer instructions, and the processor 220 is used to retrieve the computer instructions from the memory 210 to execute the method as described in any of the above method embodiments.
[0134] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device and apparatus embodiments are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.
[0135] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0136] This application may be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this application.
[0137] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.
[0138] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.
[0139] The computer program instructions used to perform the operations of this application may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of this application.
[0140] Various aspects of this application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.
[0141] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.
[0142] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.
[0143] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It will be well known to those skilled in the art that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are equivalent.
[0144] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of this application is defined by the appended claims.
Claims
1. A liquid-cooled plate flow channel design method, characterized in that, Applied to electronic devices, including: Obtain the first flow channel distribution of the liquid cooling plate, wherein the first number of target values of the material density corresponding to the first flow channel distribution is greater than a threshold, and the target value is between 0 and 1; Obtain the adjustment value of the target parameter, which includes at least one of a first parameter for adjusting the fluid permeability and a second parameter for filtering the first flow channel distribution; Based on the adjustment value of the target parameter, the topology of the first flow channel distribution is optimized to determine the target flow channel distribution of the liquid cooling plate.
2. The method according to claim 1, characterized in that, The step of performing topology optimization on the first flow channel distribution based on the adjustment value of the target parameter to determine the target flow channel distribution of the liquid cooling plate includes: Based on the adjustment value of the target parameter, update the first flow channel distribution to the second flow channel distribution; Obtain a second number of target values for the material density corresponding to the second flow channel distribution; If the second quantity is less than the threshold, the target flow channel distribution is determined based on the second flow channel distribution.
3. The method according to claim 1, characterized in that, The first parameter includes the Darcy penalty function, and the second parameter includes the hyperbolic tangent projection slope and / or the filter radius.
4. The method according to claim 3, characterized in that, The second parameter includes the hyperbolic tangent projection slope and the filter radius. The step of performing topology optimization on the first flow channel distribution based on the adjustment value of the target parameter to determine the target flow channel distribution of the liquid cooling plate includes: Based on the adjustment value of the Darcy penalty function, the first flow channel distribution is topologically optimized to obtain the third flow channel distribution; If the number of target values for material density corresponding to the third flow channel distribution is greater than the threshold, the fourth flow channel distribution is obtained according to the adjustment value of the hyperbolic tangent projection slope. If the number of target values for material density corresponding to the fourth flow channel distribution is greater than the threshold, the fifth flow channel distribution is obtained based on the adjustment value of the filtration radius; The target flow channel distribution is determined based on the fifth flow channel distribution.
5. The method according to any one of claims 1 to 4, characterized in that, The step of performing topology optimization on the first flow channel distribution based on the adjustment value of the target parameter to determine the target flow channel distribution of the liquid cooling plate includes: Obtain an objective function, which includes any one of a heat transfer objective function, a flow objective function, and a coupling objective function. The coupling objective function is the objective function obtained by coupling the heat transfer objective function and the flow objective function. The heat transfer objective function is determined based on at least one of the ambient temperature and the heat generation coefficient of the heat source corresponding to the liquid cooling plate. The flow objective function is determined based on at least one of the first fluid flow velocity corresponding to each grid in the flow channel distribution and the fluid domain proportion corresponding to each grid. The first fluid flow velocity includes horizontal velocity and vertical velocity. Based on the value of the objective function and the adjustment value of the objective parameter, the topology of the first flow channel distribution is optimized to determine the target flow channel distribution of the liquid cooling plate.
6. The method according to claim 5, characterized in that, The method for obtaining the target function includes: Based on at least one of the ambient temperature and the heat generation coefficient, the temperature field information corresponding to the flow channel distribution is determined, and the temperature field information includes the temperature at each grid in the flow channel distribution. The objective function is determined based on the maximum and minimum temperatures in the temperature field information and the temperature of the set grid. Alternatively, the acquisition of the target function includes: Based on at least one of the first fluid flow velocity corresponding to each grid and the fluid domain proportion corresponding to each grid, the velocity field information corresponding to the flow channel distribution is determined, and the velocity field information includes the second fluid flow velocity of each grid in the flow channel distribution. Based on the second fluid flow velocity, a third fluid flow velocity is determined, wherein the third fluid flow velocity characterizes the fluid flow velocity corresponding to the flow channel distribution; The objective function is determined based on the preset maximum fluid flow velocity, the preset minimum fluid flow velocity, and the third fluid flow velocity.
7. The method according to claim 5, characterized in that, The method for obtaining the target function includes: Obtain the sum of the squares of the horizontal velocity and the squares of the vertical velocity; The objective function is determined by the product of the sum of the squares of the horizontal velocity and the squares of the vertical velocity and the proportion of the fluid domain. or, The method for obtaining the target function includes: The ambient temperature, the heat generation coefficient, and the temperature of the grid set in the flow channel distribution are obtained; The objective function is determined by multiplying the difference between the ambient temperature and the temperature of the set grid with the heat generation coefficient.
8. A liquid-cooled plate flow channel design device, characterized in that, include: The first acquisition module is used to acquire the first flow channel distribution of the liquid cooling plate, wherein the first number of the target values of the material density corresponding to the first flow channel distribution is greater than a threshold, and the target value is between 0 and 1. The second acquisition module is used to acquire the adjustment value of the target parameter, wherein the target parameter includes at least one of a first parameter for adjusting the fluid permeability and a second parameter for filtering the first flow channel distribution. The determination module is used to perform topology optimization on the first flow channel distribution based on the adjustment value of the target parameter, and determine the target flow channel distribution of the liquid cooling plate.
9. A storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.
10. An electronic device, characterized in that, Including memory and processor, The memory is used to store computer instructions, and the processor is used to retrieve the computer instructions from the memory to perform the method as described in any one of claims 1 to 7.