Cooling flat plate design method for partition dot matrix topological optimization, cooling flat plate and medium

Abstract

The invention relates to the technical field of structural design and heat dissipation systems, in particular to a cooling flat plate design method for partition dot matrix topological optimization, a cooling flat plate and a medium. The method comprises the following steps: extracting a three-dimensional design domain of the cooling flat plate, and establishing a two-dimensional model of the three-dimensional design domain; carrying out finite element grid division processing on the two-dimensional model, and calculating to obtain a two-dimensional topological optimization result of a distribution cloud chart and a streamline diagram containing unit density; dividing the three-dimensional design domain into a plurality of regions according to a two-dimensional topological optimization result; and for each area, selecting an adaptive dot matrix unit for periodic filling, combining the filled subareas and the outer skin of the cooling flat plate into an integral entity through Boolean operation, and outputting a cooling flat plate structure which can be manufactured. According to the method, through the design of combining partition and dot matrix units, fluid channels and solid supports in the cooling flat plate can be more reasonable in spatial distribution, and the multiple performance requirements of flow guiding, heat transferring, bearing and the like are met.

Description

Technical Field

[0001] This invention relates to the field of structural design and heat dissipation system technology, and in particular to a method for designing a cooling plate with partitioned lattice topology optimization, the cooling plate and the medium. Background Technology

[0002] Under hypersonic flight conditions, scramjet engines need to withstand extremely high heat flux density and complex aerodynamic loads during operation. The engine cooling panels not only need to have efficient heat dissipation capabilities, but also need to take into account the requirements of structural load-bearing capacity and overall lightweight design.

[0003] Related technologies generally employ straight-channel or finned active cooling structures, but these designs have certain shortcomings in terms of overall performance. On the one hand, it is difficult to balance heat transfer efficiency and load-bearing capacity, resulting in an inability to simultaneously achieve optimal cooling effect and structural strength. On the other hand, the channel arrangement is relatively simple, lacking the ability to flexibly adjust according to local heat exchange needs, thus easily leading to the risk of insufficient cooling in areas with uneven heat flux distribution. Meanwhile, with the development of additive manufacturing technology, although three-period minimal curved surface structures and micro-truss lattice structures have gradually gained attention due to their high specific surface area, excellent load-bearing capacity, and design adjustability, it is difficult to fully realize their potential advantages under complex working conditions.

[0004] Therefore, the cooling wall panel structure in the relevant technology still has certain limitations in terms of heat transfer, load-bearing capacity and process adaptability, and needs further improvement. Summary of the Invention

[0005] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the purpose of this invention is to propose a cooling plate design method, a cooling plate, and a medium with partitioned lattice topology optimization, achieving optimized design with temperature and pressure drop as objectives, and improving heat transfer performance while meeting structural strength requirements by combining lattice elements.

[0006] To achieve the above objectives, a first aspect of the present invention proposes a cooling plate design method with partitioned lattice topology optimization, comprising: Extract the three-dimensional design domain of the cooling plate and establish a two-dimensional model of the three-dimensional design domain; The two-dimensional model is divided into finite element meshes, and the two-dimensional topology optimization results, including the distribution cloud map and streamline map containing the element density, are calculated. Based on the two-dimensional topology optimization results, the three-dimensional design domain is divided into multiple regions; each region corresponds to a different flow channel shape and streamline direction. For each region, suitable lattice elements are selected for periodic filling, and the filled partitioned region is merged with the outer skin of the cooling plate into a whole entity through Boolean operations, outputting a manufacturable cooling plate structure.

[0007] In addition, the method of the above embodiments of the present invention may also have the following additional technical features: According to one embodiment of the present invention, the two-dimensional model includes a solid layer and a design layer; wherein the design layer is described using the Darcy model and a fluid-structure interaction heat transfer model, and the solid layer is described using a solid heat transfer model; the design layer and the solid layer are coupled through convective heat transfer.

[0008] According to one embodiment of the present invention, the two-dimensional model is divided into finite element meshes to obtain a two-dimensional topology optimization result including a distribution cloud map and a streamline map containing element density, including: The method of moving asymptotes (MMA) is used to iteratively optimize the element density of the two-dimensional model under the condition of satisfying volume constraints. The optimization objective is to minimize the weighted result of the average temperature of the solid layer and the global pressure drop of the design layer, and the two-dimensional topology optimization result is output.

[0009] According to an embodiment of the present invention, when iteratively optimizing the element density of the two-dimensional model using the MMA algorithm, the method includes: The element density of the two-dimensional model is filtered and projected.

[0010] According to one embodiment of the present invention, the plurality of regions include: a left front region, a right front region, a straight low-density region, and a straight high-density region.

[0011] According to one embodiment of the present invention, the lattice unit is selected from any one or any combination of the following: body-centered cubic (BCC) unit cell, diamond unit cell, mirrored diamond unit cell, and Schwarz unit cell.

[0012] According to one embodiment of the present invention, the dimensions of the BCC unit cell and the Schwarz unit cell are consistent with the thickness of the three-dimensional design domain; The size of the Diamond unit cell is set as a multiple of the thickness of the three-dimensional design domain.

[0013] According to one embodiment of the present invention, the heat transfer coefficient of convective heat transfer between the design layer and the solid layer is obtained by interpolating the unit density between the fluid convective heat transfer coefficient and the metal contact heat transfer coefficient.

[0014] To achieve the above objectives, a second aspect of the present invention provides a cooling plate, which is designed by the above-described cooling plate design method based on partitioned lattice topology optimization.

[0015] To achieve the above objectives, a third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the steps of the above-described cooling plate design method for partitioned lattice topology optimization.

[0016] The partitioned lattice topology optimization cooling plate design method, cooling plate, and medium of this invention simplify the three-dimensional design domain of the cooling plate into a two-dimensional model, enabling rapid and efficient design of the cooling plate flow channels. By introducing a partitioned design based on topology optimization results within the three-dimensional design domain, different regions can adopt differentiated flow channel shapes and streamline directions, combined with periodic filling using suitable lattice units. This improves heat transfer performance and flow efficiency under fluid-structure interaction while ensuring overall structural strength. Furthermore, the resulting cooling plate structure possesses good manufacturability and lightweight characteristics, effectively balancing multiple objectives such as efficient heat dissipation, load-bearing capacity, and pressure drop control. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a cooling plate design method for partitioned lattice topology optimization in one embodiment. Figure 2 This is a schematic diagram of the cell density cloud map and streamline map of the two-dimensional topology optimization results in one embodiment; Figure 3 This is a schematic diagram of the division of a three-dimensional design domain in one embodiment; Figure 4 This is a schematic diagram illustrating the division of a 3D design domain into independent entities in one embodiment; Figure 5 This is a schematic diagram of the structure of different unit cells in one embodiment; Figure 6 This is a schematic diagram of the initial model of the cooling plate in one embodiment; Figure 7 This is a cross-section of the overall three-dimensional structure after merging in one embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] The implementation details of the technical solutions in the embodiments of this application are described in detail below.

[0020] In one embodiment, such as Figure 1 The diagram shows a flowchart of a cooling plate design method based on partitioned lattice topology optimization. This method may include the following steps: Step S101: Extract the three-dimensional design domain of the cooling plate and establish a two-dimensional model of the three-dimensional design domain.

[0021] The design domain refers to the potential spatial range used for arranging optimized structures while meeting geometric boundary constraints and functional requirements. The three-dimensional design domain of a cooling plate is a three-dimensional spatial region determined by the geometric boundary conditions of the cooling plate, based on comprehensive consideration of design requirements such as heat dissipation, load-bearing capacity, and lightweighting. This region covers the effective working range of the cooling plate and the space that may be used for flow channel arrangement, thus providing a complete solution range for optimization design.

[0022] After obtaining the three-dimensional design domain, in order to reduce computational complexity and highlight the key flow and heat transfer characteristics during the optimization process, the three-dimensional design domain is simplified in the thickness direction to establish a two-dimensional design domain. This two-dimensional design domain can be regarded as an equivalent simplified model of the three-dimensional design domain, which can maintain the main geometric features and functional areas of the cooling plate while reducing the degrees of freedom in the optimization calculation and improving computational efficiency.

[0023] In one embodiment, the established two-dimensional model consists of two parts: a design layer and a solid layer. The solid layer and design layer of the two-dimensional model are described in detail below.

[0024] The design layer characterizes the fluid regions that may exist within the cooling plate. Its internal flow state is described using the Darcy model, and combined with a fluid-structure interaction heat transfer model to characterize the heat transfer process between the fluid and the surrounding solid. This allows the optimization calculations to simultaneously reflect the thermal conduction behavior of the structural region and the convective heat transfer behavior of the flow channel region. The governing equations for the design layer are:

[0025] In the above formula, For vector differentiation (Nabla) operators; The permeability of the unit cell is obtained by interpolation using the Solid Isotropic Material with Penalization (SIMP) model. The unit viscosity obtained using SIMP interpolation; For fluid pressure; The cell density obtained using SIMP interpolation, For the unit specific heat capacity obtained using SIMP interpolation, The unit thermal conductivity is obtained using SIMP interpolation. For designing the layer unit temperature, For heat exchange from the solid layer, The thickness of the design layer.

[0026] The solid layer characterizes the solid structural region of the cooling plate, and a solid heat transfer model is used to describe its thermal conductivity and heat distribution within the solid material. The governing equations of the solid heat transfer model are as follows:

[0027] In the above formula, Thermal conductivity of solid materials The temperature of the solid layer. As a heat source, The thickness of the solid layer.

[0028] To achieve energy transfer between the design layer and the solid layer, a convective heat transfer boundary condition is established at the interface, with coupled heat transfer... Defined as:

[0029] In the above formula, This model represents the heat transfer coefficient for convective heat transfer between the design layer and the solid layer. This modeling approach accurately represents the energy exchange relationship between the fluid and the solid, while balancing computational efficiency and physical plausibility, providing a reliable foundation for subsequent topology optimization.

[0030] In one embodiment, the convective heat transfer coefficient between the design layer and the solid layer is expressed as a function of the unit density in the fluid convective heat transfer coefficient. Heat transfer coefficient in contact with metal Interpolation is used to obtain the values. In topology optimization, element density is used to distinguish the physical properties of different regions: when the element density approaches 1, the region is closer to a solid structure; when the element density approaches 0, the region is closer to a fluid channel. In the solid region of the design layer, i.e., when the element density is close to a solid state, the thermal resistance between the solid layer and the design layer is small, and the corresponding heat transfer coefficient tends to be a larger metal-to-metal contact heat transfer coefficient. For example, 2*10 can be taken. 5 W / (m2·K); In the fluid region of the design layer, i.e., when the unit density is close to the fluid state, the thermal resistance between the solid layer and the fluid layer is relatively large, and the corresponding heat transfer coefficient tends to be a smaller fluid convection heat transfer coefficient, for example, 1*10. 4 W / (m2·K).

[0031] This interpolation method enables a smooth transition of heat transfer capacity between the solid and fluid regions in topology optimization calculations, thereby ensuring the physical rationality of the fluid-structure interaction heat transfer process.

[0032] Step S102: Divide the two-dimensional model into finite element meshes and calculate the two-dimensional topology optimization results, which include the distribution cloud map and streamline map of element density.

[0033] The design domain of the two-dimensional model and the combined structure of the solid layer are divided into several finite element elements according to a preset mesh density. Each element has corresponding node coordinates and geometric properties.

[0034] After the mesh is generated, the density of each cell is solved by topology optimization through numerical iteration. The density value of each cell is updated by the topology optimization algorithm, so that the solid region gradually concentrates in the position with better heat transfer performance, while the fluid region gradually forms a continuous flow channel.

[0035] After optimization, the output element density distribution cloud map is used to characterize the distribution of solid or fluid properties in each region of the design domain. Simultaneously, streamline diagrams generated from calculating the velocity and pressure fields in the fluid region are used to reflect the flow path and velocity distribution characteristics of the fluid within the design domain. Combining the element density distribution cloud map and the streamline diagram provides a visual representation of the final results of the two-dimensional topology optimization.

[0036] In one embodiment, the MMA algorithm is used to iteratively update the element density during the solution process. Volume constraints are applied during the iteration process to limit the volume percentage of the fluid domain within the entire three-dimensional design domain, thereby ensuring that the optimized structure meets the design requirements.

[0037] In each iteration, the average temperature of the solid layer and the global pressure drop of the design layer are calculated based on the current unit density. These two values ​​are then weighted to form the objective function, with the goal of minimizing this weighted result. The average temperature of the solid layer characterizes the heat transfer performance of the cooling plate, while the global pressure drop of the design layer characterizes the flow resistance. Weighting these values ​​allows for a balance between heat transfer and flow performance during the optimization process. This method yields a two-dimensional topology optimization result that achieves an optimal balance between heat transfer and flow performance for the cooling plate structure while maintaining volume constraints.

[0038] Based on the above iterative process, the following optimization model can be established:

[0039] in, For the density of finite elements, Indicates the first The density of finite element elements; the optimization objective is to minimize the weighting function. , The average temperature of the solid layer. For global voltage drop at the design layer; The weighting is the average temperature of the solid layer. This is the weight for the global voltage drop at the design layer.

[0040] In the above formula To optimize the volume constraints applied during the iteration process, where, For a two-dimensional design domain, Due to volume constraints, The volume percentage of the fluid domain within the entire two-dimensional design domain.

[0041] Among the above optimization objectives, the average temperature of the solid layer is... Defined as:

[0042] In the above formula, For solid layer region, The unit temperature.

[0043] Among the above optimization objectives, the global voltage drop at the design layer is... Defined as:

[0044] In the above formula, and These represent the velocity components of the fluid in the horizontal and vertical directions, respectively; The inlet Reynolds number; and This is a velocity gradient-related term used to calculate the contribution of local pressure drop.

[0045] This optimization model enables a reasonable distribution of element density between the solid and fluid regions, thereby achieving a two-dimensional topology optimization result that balances heat transfer and flow performance.

[0046] In one embodiment, when solving the topology optimization problem for a two-dimensional model, element density filtering and projection processing are used to ensure the physical rationality and manufacturability of the optimization results.

[0047] In one implementation, Helmholtz filtering is used to smooth the cell density, eliminating checkerboard patterns and high-frequency numerical noise. Specifically, the filtered density of each cell is calculated by weighted averaging of its neighboring cells, thus achieving continuous spatial variation of the cell density and ensuring the numerical stability of the optimization results. The cell density update formula is as follows:

[0048] in, For the filter radius, The density of a finite element, i.e., the original density of the element. This represents the unit density after filtration.

[0049] After filtering, the element density is projected. In one implementation, Heaviside projection can be used to binarize the element density to eliminate grayscale elements, making the optimization results closer to the actual manufacturable solid or fluid state. During the projection process, a set decomposition threshold is used... and projection intensity This maps continuous element density to values ​​close to 0 or 1, achieving a clear division between solid and fluid regions. The calculation formula is as follows:

[0050] In the above formula, This represents the projected element density.

[0051] Through the above filtering and projection processing, a smooth transition and rationalization of unit density can be achieved during the MMA iterative optimization process, while enhancing the manufacturability and structural stability of the final two-dimensional topology optimization results.

[0052] Step S103: Based on the two-dimensional topology optimization results, the three-dimensional design domain is divided into multiple regions.

[0053] After outputting the 2D topology optimization results, a comprehensive analysis of the element density distribution cloud map and streamline diagram is performed to extract the main streamline directions and corresponding geometric distributions of the fluid channels, which are then used as a reference for region division. Based on these features, the 2D topology optimization results are mapped to the 3D design domain and extended along the thickness direction to ensure that the spatial distribution characteristics within the 3D design domain are consistent with the 2D topology optimization results. In this way, both the solid-dominant region and the fluid channel region can be identified simultaneously within the 3D design domain. Furthermore, by combining this with the main streamline directions of the fluid, the entire 3D design domain is divided into several independent regions, each corresponding to a specific channel shape and streamline direction.

[0054] In one embodiment, when dividing the three-dimensional design domain into regions based on the cell density distribution cloud map and streamline map output by the two-dimensional topology optimization results, it can be divided into a left front region, a right front region, a straight low-density region, and a straight high-density region.

[0055] The left-forward region is the area where the flow channel shape faces left and forward, and the right-forward region is the area where the flow channel shape faces right and forward. The left-forward and right-forward regions correspond to fluid channels with a certain slope in the streamline direction in the two-dimensional topology optimization results. In the three-dimensional design domain, they extend along the thickness direction to form a flow channel structure with forward guiding characteristics.

[0056] The vertical low-density region is mainly composed of low-density units, representing a spatial distribution dominated by fluid channels. This region is identified as the main flow channel portion in 3D modeling. In contrast, the vertical high-density region is mainly composed of high-density units, representing a spatial distribution dominated by solid structures. This region corresponds to the solid support portion of the cooling plate in 3D modeling.

[0057] Figure 2 The cell density contour plot and streamline plot of the two-dimensional topology optimization results are shown, based on... Figure 2 As a result, partitioning the entire 3D design domain yields the following results: Figure 3 The diagram illustrates four regions: left front, right front, vertical low density, and vertical high density. In practical applications, the entire 3D design domain can be divided into several independent entities according to these four regions, such as... Figure 4 As shown, this provides a clear zoning basis for the subsequent arrangement of the lattice structure and the manufacturing of the cooling plate.

[0058] Step S104: For each region, select suitable lattice units for periodic filling, and merge the filled partitioned region with the outer skin of the cooling plate into a whole entity through Boolean operation, outputting a manufacturable cooling plate structure.

[0059] Lattice units are repeatable microstructural units that form a continuous three-dimensional network structure through periodic combination. These lattice units can not only be uniformly distributed in space, but also have good load-bearing capacity and thermal conductivity, providing stable support and effective heat transfer channels for fluid channels.

[0060] After partitioning the 3D design domain, suitable lattice elements are selected and periodically filled into each partition according to the flow channel shape and streamline direction of each region. The filled lattice structure maintains the connectivity and flow direction of the fluid channels, while also providing a solid foundation for subsequent integration with the external skin, and achieving an optimized balance between lightweight design and heat transfer performance.

[0061] After infilling, the lattice units of each zone are merged with the outer skin of the cooling plate through Boolean operations. The outer skin serves as the overall surface or load-bearing frame of the cooling plate, providing structural support and protecting the internal lattice flow channels, thus forming a unified solid. During the Boolean operation, the lattice units and the outer skin are tightly integrated, while preserving the independent features and flow channel orientation of each zone. The resulting overall 3D solid can be directly exported as a manufacturable model file (such as a stereolithography (STL) file), providing a data foundation for additive manufacturing or other processing techniques, thereby achieving high-precision manufacturability of the cooling plate.

[0062] In one embodiment, the array elements may be selected from several microstructural elements, including BCC cells, Diamond cells, mirrored Diamond cells, and Schwarz cells. Figure 5 The diagrams show the structural schematics of different unit cells. Among them, the BCC unit cell is a cubic body-centered structure with good uniform load-bearing capacity; the Diamond unit cell has a rhombic network structure with high specific surface area and excellent heat transfer performance; the mirrored Diamond unit cell is a mirror arrangement of Diamond unit cells, which can improve local mechanical properties through symmetrical combination; and the Schwarz unit cell is a continuous minimal surface structure that can provide stable three-dimensional support while ensuring unobstructed fluid channels.

[0063] In one embodiment, to ensure the adaptability and uniform distribution of lattice units in the three-dimensional design domain, the dimensions of various unit cells are set separately. The geometric dimensions of BCC and Schwarz unit cells are consistent with the thickness of the three-dimensional design domain, enabling them to completely fill the partitioned areas in the thickness direction and match the external skin, ensuring structural continuity and overall support performance. The size of Diamond unit cells can be set as a multiple of the thickness of the three-dimensional design domain (e.g., twice) to accommodate the larger space requirements of the design layer and flow channel region. At the same time, through periodic arrangement to form a continuous microstructure network, higher specific surface area and effective heat transfer paths are achieved.

[0064] In practical applications, the volume fraction of lattice cells can be selected based on the flow channel shape and streamline direction of each zone to further optimize fluid-structure interaction performance. For example, a 20% volume fraction BCC cell can be used in the left forward region, a 30% volume fraction Diamond cell in the right forward region, a 30% volume fraction mirrored Diamond cell in the vertical low-density region, and a 40% volume fraction Schwarz cell in the vertical high-density region. Through reasonable configuration of size and volume fraction, comprehensive optimization of fluid channel connectivity, structural support, and heat transfer performance can be achieved, thereby obtaining a manufacturable monolithic cooling plate structure.

[0065] To further illustrate the specific application of the partitioned lattice topology optimization cooling plate design method of the present invention, an application embodiment is proposed to provide a clearer understanding of the operation and effects of each step. The cooling plate design shown in this application embodiment achieves both fluid channel optimization and improved heat transfer performance, while also considering structural manufacturability and mechanical support requirements.

[0066] Figure 6This is a schematic diagram of the initial model of the cooling plate. The cooling plate has a rectangular structure with a length, width, and height of L=176mm, W=46mm, and H=7mm, respectively. The design layer thickness is Δzd=5mm, and the solid layer thickness is Δzb=1mm. The outermost layer of the cooling plate is a solid skin, and the middle core is the flow channel design domain for fluid cooling.

[0067] First, based on the design requirements of the cooling plate, the design domain is extracted and its thickness is ignored, simplifying it into a two-dimensional model with dimensions of 176mm × 46mm. The two-dimensional model is divided into two parts: a design layer and a solid layer. The design layer is used to characterize the region where the fluid may be distributed, while taking into account both the Darcy fluid model and the fluid-structure interaction heat transfer model. The solid layer is used to characterize the solid structural region of the cooling plate, and only the solid heat transfer model is considered. The two layers are coupled through convection heat transfer to achieve fluid-solid energy exchange.

[0068] In this application embodiment, the solid material is silicon nitride ceramic with a density of 1970. Thermal conductivity 33.699 W / (m·K), specific heat capacity 556 J / kg·K; fluid is water, density 1000 W / (m·K). Thermal conductivity 0.6 W / (m·K), specific heat capacity 4200 J / kg·K, viscosity 0.001 Pa·s. Boundary conditions are set as follows: inlet flow rate 10 g / s, inlet temperature 20℃, outlet pressure 3 MPa, and heat source 100000. .

[0069] Subsequently, the two-dimensional design model was meshed using the finite element method (FEM), and a topology optimization model was established and solved. During the optimization process, the MMA algorithm was used for iterative optimization of the element density, with the volume constraint set to ensure that the solid content of the entire design domain is greater than 50%. The optimization objective was primarily to reduce the average temperature of the solid layer, while also considering the flow pressure drop of the design layer. In the topology optimization process, Helmholtz filtering with a filter radius of 2 mm was used to eliminate numerical noise and checkerboard patterns. Furthermore, to enhance manufacturability, Heaviside projection was employed with a projection intensity of 16 and a boundary threshold of 0.5.

[0070] After the two-dimensional topology optimization is completed, the following is obtained: Figure 2 The unit density distribution cloud map and streamline diagram shown divide the entire three-dimensional design domain into several regions based on the flow channel shape and streamline direction, forming a pattern as follows: Figure 3 and Figure 4 The diagram shows independent partitions. These partitions represent different flow channel characteristic regions, providing a basis for subsequent lattice filling.

[0071] During the lattice filling stage, several candidate lattice units are selected, including BCC cells, Diamond cells, mirrored Diamond cells, and Schwarz cells (e.g., ...). Figure 5 (As shown). Among them, the dimensions of BCC unit cells and Schwarz unit cells are consistent with the design domain thickness, which is 5mm×5mm×5mm; the dimensions of Diamond unit cells are twice the design domain thickness, i.e., 10mm×10mm×10mm, to accommodate larger space requirements.

[0072] Based on the flow channel shape and streamline direction of each partition, suitable lattice units are selected to periodically fill the partition area, forming a continuous and uniform microstructure network to ensure the connectivity of the fluid channels, while optimizing heat conduction and structural support performance.

[0073] After infilling, the lattice regions of each partition are merged with the outer skin of the cooling plate using Boolean operations to form a unified solid. The outer skin serves as the overall surface or load-bearing frame of the cooling plate, providing structural support and protecting the internal flow channels. The cross-section of the merged overall 3D structure is shown below. Figure 7 As shown, the final output is a manufacturable model file (e.g., an STL file), which can be used to create a physical object through processes such as additive manufacturing.

[0074] In the above embodiments, a modeling approach based on partitioned lattice topology optimization was introduced into the design of the cooling plate. Two-dimensional topology optimization yielded a distribution cloud map and streamline map containing the unit density. This result was then combined with the flow channel shape and streamline direction to partition and fill the three-dimensional design domain, ensuring that the lattice units matched the fluid flow characteristics and heat transfer requirements. This improved overall heat transfer efficiency while maintaining flow channel connectivity. Furthermore, by setting different unit cell sizes and volume fractions, a comprehensive balance was achieved between structural load-bearing capacity, thermal conductivity, and fluid flow resistance. The resulting cooling plate not only significantly reduced the temperature of the solid layer and improved heat dissipation performance but also maintained a low flow pressure drop, balancing lightweight design and manufacturability.

[0075] In one embodiment, a cooling plate is provided, which is designed by a cooling plate design method based on partitioned lattice topology optimization.

[0076] In one embodiment, a computer storage medium is provided on which a computer program is stored, which, when executed by a processor, implements a cooling plate design method with partitioned lattice topology optimization.

[0077] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0078] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0079] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0080] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0081] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for designing a cooling plate with partitioned lattice topology optimization, characterized in that, include: Extract the three-dimensional design domain of the cooling plate and establish a two-dimensional model of the three-dimensional design domain; The two-dimensional model is divided into finite element meshes, and the two-dimensional topology optimization results, including the distribution cloud map and streamline map containing the element density, are calculated. Based on the two-dimensional topology optimization results, the three-dimensional design domain is divided into multiple regions; each region corresponds to a different flow channel shape and streamline direction. For each region, suitable lattice elements are selected for periodic filling, and the filled partitioned region is merged with the outer skin of the cooling plate into a whole entity through Boolean operations, outputting a manufacturable cooling plate structure.

2. The cooling plate design method for partitioned lattice topology optimization according to claim 1, characterized in that, The two-dimensional model includes a solid layer and a design layer; wherein, the design layer is described using the Darcy model and a fluid-structure interaction heat transfer model, and the solid layer is described using a solid heat transfer model; the design layer and the solid layer are coupled through convective heat transfer.

3. The cooling plate design method for partitioned lattice topology optimization according to claim 2, characterized in that, The two-dimensional model is meshed using finite element methods to obtain two-dimensional topology optimization results, including distribution cloud maps and streamline maps containing element density. The MMA algorithm is used to iteratively optimize the element density of the two-dimensional model under the condition of satisfying the volume constraint. The optimization objective is to minimize the weighted result of the average temperature of the solid layer and the global pressure drop of the design layer, and the two-dimensional topology optimization result is output.

4. The cooling plate design method for partitioned lattice topology optimization according to claim 3, characterized in that, When iteratively optimizing the cell density of the two-dimensional model using the MMA algorithm, the following steps are included: The element density of the two-dimensional model is filtered and projected.

5. The cooling plate design method for partitioned lattice topology optimization according to claim 1, characterized in that, Multiple regions include: left anterior region, right anterior region, vertical low-density region, and vertical high-density region.

6. The cooling plate design method for partitioned lattice topology optimization according to claim 1, characterized in that, The lattice units are selected from any one or any combination of the following: BCC unit cell, Diamond unit cell, mirrored Diamond unit cell, and Schwarz unit cell.

7. The cooling plate design method for partitioned lattice topology optimization according to claim 6, characterized in that, The dimensions of the BCC unit cell and the Schwarz unit cell are consistent with the thickness of the three-dimensional design domain. The size of the Diamond unit cell is set as a multiple of the thickness of the three-dimensional design domain.

8. The cooling plate design method for partitioned lattice topology optimization according to claim 2, characterized in that, The heat transfer coefficient of convective heat transfer between the design layer and the solid layer is obtained by interpolating between the fluid convective heat transfer coefficient and the metal contact heat transfer coefficient using the unit density.

9. A cooling plate, characterized in that, The cooling plate is designed by the cooling plate design method of partitioned lattice topology optimization as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the cooling plate design method for partitioned lattice topology optimization as described in any one of claims 1 to 8.

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