Liquid cooling plate flow channel optimization method and device based on topological optimization and medium

Abstract

The invention discloses a liquid cooling plate flow channel optimization method and device based on topological optimization and a medium, and relates to the technical field of battery thermal management, and the method comprises the steps: based on a manufacturing constraint data packet, carrying out constraint compliance verification through a material distribution optimization algorithm to generate a flow channel plane topological structure, and obtaining a flow channel three-dimensional entity through structure dimension raising conversion; establishing a heat-fluid-solid data exchange channel according to the flow channel three-dimensional entity, and generating a layered verification report through multi-physics field coupling verification; constructing a defect traceability mapping model, extracting defect features in the layered verification report for analysis and optimization, and generating a directional optimization instruction set; and executing a directional optimization instruction set to reconstruct a three-dimensional entity of the flow channel, and generating a performance standard-reaching authentication report through geometric process closed-loop calibration. According to the method, a defect tracing mapping model is constructed through multi-physics field coupling verification, a directional optimization instruction set is generated, and a full-closed-loop feedback optimization method is formed.

Description

Technical Field

[0001] This invention relates to the field of battery thermal management technology, and in particular to a method, device and medium for optimizing the flow channel of a liquid cooling plate based on topology optimization. Background Technology

[0002] With the widespread application of high-power battery systems in new energy vehicles and energy storage equipment, liquid cooling plates, as core heat dissipation components for battery thermal management, directly impact system heat dissipation efficiency and reliability through their flow channel design. Traditional liquid cooling plate flow channel design primarily relies on empirical biomimetic structures and parametric dimensional optimization methods. In recent years, topology optimization techniques have been gradually introduced to achieve innovative flow channel layout designs. Topology optimization generates lightweight, high-performance structural forms through material distribution algorithms, demonstrating significant potential in improving flow channel heat dissipation performance. In existing technologies, preliminary flow channel configurations are achieved by constructing optimization models with the objective function of minimizing average temperature or maximizing heat conduction. Furthermore, multiphysics simulation techniques are used to verify the reliability of optimization results, and some studies have also attempted to incorporate manufacturing process constraints into the optimization process to improve design feasibility.

[0003] However, existing technologies still have two limitations. On the one hand, the topology optimization process is disconnected from manufacturing process requirements. Most studies only treat process constraints as post-processing conditions rather than embedding them into the optimization kernel, making it difficult for the optimization results to meet actual production requirements and requiring secondary adjustments based on human experience. On the other hand, multiphysics verification and optimization design have a one-way open-loop relationship. Simulation results cannot directly drive the iterative correction of design parameters and lack a closed-loop feedback mechanism of "design-verification-re-optimization". In particular, it is difficult to quickly locate the key geometric features that affect heat dissipation performance in high-dimensional parameter spaces, which means that the method needs to be tested and verified multiple times to achieve the performance indicators, resulting in a waste of R&D resources. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a liquid cooling plate flow channel optimization method based on topology optimization to solve the problems of disconnect between topology optimization and manufacturing process and lack of closed-loop verification in multiphysics field.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a liquid cooling plate flow channel optimization method based on topology optimization, comprising: collecting liquid cooling plate process constraint data and generating a manufacturing constraint data package through preprocessing; generating a flow channel planar topology structure based on the manufacturing constraint data package by performing constraint compliance verification through a material distribution optimization algorithm, and obtaining a three-dimensional entity of the flow channel through structural dimensional transformation; establishing a thermal-fluid-solid data exchange channel based on the three-dimensional entity of the flow channel, and generating a hierarchical verification report through multi-physics field coupling verification; constructing a defect source tracing mapping model, extracting defect features from the hierarchical verification report for analysis and optimization, and generating a targeted optimization instruction set; executing the targeted optimization instruction set to reconstruct the three-dimensional entity of the flow channel, and generating a performance compliance certification report through geometric process closed-loop calibration.

[0008] As a preferred embodiment of the liquid cooling plate flow channel optimization method based on topology optimization described in this invention, the liquid cooling plate process constraint data includes thermal deformation extreme value, material stress limit and fluid turbulence critical value;

[0009] The preprocessing includes data cleaning, normalization, and geometric regularization.

[0010] As a preferred embodiment of the liquid cooling plate flow channel optimization method based on topology optimization described in this invention, the manufacturing constraint data package includes minimum forming size and maximum allowable tilt angle;

[0011] The process involves generating a flow channel planar topology structure based on manufacturing constraint data packages, performing constraint compliance verification through a material distribution optimization algorithm, and obtaining the flow channel three-dimensional entity through structural dimensional transformation.

[0012] The boundary condition matrix is ​​constructed based on the minimum forming size and the maximum allowable tilt angle. The material distribution in Euclidean space is calculated using a gradient-sensitive algorithm to generate the flow channel planar topology.

[0013] The flow channel planar topology is extended at equal intervals, and the maximum allowable tilt angle is used to smooth curvature abrupt changes through the tilt angle compensation algorithm to form a three-dimensional solid flow channel.

[0014] As a preferred embodiment of the liquid cooling plate flow channel optimization method based on topology optimization described in this invention, the specific steps for establishing a thermal-fluid-solid data exchange channel based on the three-dimensional entity of the flow channel are as follows:

[0015] Extract the surface curvature features of the three-dimensional solid of the flow channel, and obtain the topological carrier nodes through geometric feature topology mapping;

[0016] A thermal-fluid-solid data link is established between the topological carrier nodes, and a thermal-fluid-solid data exchange channel is established through a vector fusion algorithm.

[0017] As a preferred embodiment of the liquid-cooled plate flow channel optimization method based on topology optimization described in this invention, the specific steps for generating a hierarchical verification report through multiphysics coupling verification are as follows:

[0018] The temperature gradient extreme region, fluid vortex region and stress concentration region in the thermal-fluid-solid data exchange channel are analyzed to form a physical field feature vector set.

[0019] The coefficient matrix of the thermo-fluid-structure interaction equation is constructed based on the feature vector set, and a structured hierarchical verification report is generated by separating the inter-field interaction terms.

[0020] As a preferred embodiment of the liquid cooling plate flow channel optimization method based on topology optimization described in this invention, the specific steps for constructing the defect source tracing mapping model are as follows:

[0021] A cross-field coupling feature separation method is used to simultaneously extract the three-dimensional coordinates of the temperature gradient extreme value region, the fluid vortex region, and the stress concentration region to generate the spatial coordinates of the defect features.

[0022] Based on the three-dimensional solid of the flow channel, the spatial coordinates of the defect features are mapped to the flow channel design parameters to obtain the defect design parameter correlation matrix;

[0023] Temperature gradient, pressure drop, and stress amplitude are extracted from the defect design parameter correlation matrix. The physical field coupling strength is calculated using a field coupling strength algorithm, and finally a defect source tracing mapping model is constructed.

[0024] As a preferred embodiment of the liquid cooling plate flow channel optimization method based on topology optimization described in this invention, the generation of the directional optimization instruction set refers to extracting defect features from the hierarchical verification report, inputting them into the defect source mapping model, and fusing the coefficient matrix of the thermal-fluid-structure interaction equation to generate the directional optimization instruction set.

[0025] As a preferred embodiment of the liquid cooling plate flow channel optimization method based on topology optimization described in this invention, the specific steps of reconstructing the three-dimensional solid of the flow channel by executing the directional optimization instruction set and generating a performance compliance certification report through geometric process closed-loop calibration are as follows.

[0026] The spatial location and operation parameters in the directional optimization instruction set are analyzed to drive the geometric structure adjustment of the three-dimensional entity of the flow channel and generate the reconstructed three-dimensional entity of the flow channel.

[0027] Based on the manufacturing constraint data package, the reconstructed three-dimensional solid of the flow channel is used to verify structural compliance, and the data is input into the thermal-fluid-solid data exchange channel to perform lightweight coupling analysis and output calibration performance data.

[0028] By combining calibration performance data with stratified verification reports, a performance compliance certification report is generated through differential comparison.

[0029] In a second aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the liquid cooling plate flow channel optimization method based on topology optimization as described in the first aspect of the present invention.

[0030] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the liquid cooling plate flow channel optimization method based on topology optimization as described in the first aspect of the present invention.

[0031] The beneficial effects of this invention are as follows: by embedding manufacturing constraints deep into the topology optimization process, secondary rework caused by disconnection is avoided, and the first-pass yield of the design is improved; at the same time, a defect source tracing mapping model is constructed based on multi-physics field coupling verification, and a directional optimization instruction set is generated, forming a fully closed-loop feedback optimization method. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart of a liquid cooling plate flow channel optimization method based on topology optimization.

[0034] Figure 2 A flowchart for generating a three-dimensional solid flow channel.

[0035] Figure 3 A flowchart for generating a tiered validation report.

[0036] Figure 4 A flowchart for generating a targeted optimization instruction set. Detailed Implementation

[0037] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0038] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0039] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0040] Reference Figures 1-4 This is one embodiment of the present invention, which provides a liquid cooling plate flow channel optimization method based on topology optimization, including the following steps:

[0041] S1: Collect process constraint data for liquid cooling plates and generate manufacturing constraint data packages through preprocessing.

[0042] S1.1: Process limitation data for liquid cooling plates include extreme values ​​of thermal deformation, material stress limits, and critical values ​​for fluid turbulence;

[0043] It should be noted that the extreme value of thermal deformation is generated by directly measuring the deformation behavior of the material during the continuous heating process using a thermomechanical analyzer to generate a deformation curve. The extreme value of thermal deformation is generated by real-time monitoring of the deformation curve and identifying the critical temperature at which the deformation cannot be recovered as the judgment value.

[0044] The material stress limit is determined by directly performing tensile tests on the liquid-cooled plate substrate using a universal testing machine. The stress-strain curve of the material under stress is recorded in real time, and the inflection point of the stress-strain curve when plastic deformation first occurs is taken as the yield strength. The peak value of the highest point of the stress-strain curve is taken as the tensile strength. The yield strength and tensile strength in the stress-strain curve are used as limit values ​​to generate the material stress limit.

[0045] The critical value of fluid turbulence is obtained by directly monitoring the changes in the flow state of the fluid in the flow channel through a flow velocity sensor, observing the critical point of transition from laminar to turbulent flow, and recording the corresponding flow velocity value as the critical value of fluid turbulence.

[0046] S1.2: Preprocessing includes data cleaning, normalization, and geometric regularization.

[0047] It should be noted that the extreme values ​​of thermal deformation, material stress limits, and critical values ​​of fluid turbulence are obtained by cleaning up abnormal data points caused by sensor vibration; at the same time, moving average filtering is used to smooth data fluctuations and eliminate measurement noise.

[0048] After data cleaning, the minimum and maximum values ​​of the thermal deformation extreme value, material stress limit, and fluid turbulence critical value were statistically analyzed for the liquid cooling plate process constraints. Normalization was then applied to linearly map each data point to the [0,1] interval. This operation eliminated the dimensional differences between the thermal deformation extreme value, material stress limit, and fluid turbulence critical value.

[0049] Based on the normalized liquid cooling plate process constraint data, the material stress limit value is transformed into a manufacturable geometric constraint, and the minimum forming size (such as minimum wall thickness) is derived.

[0050] Based on the normalized extreme values ​​of thermal deformation and critical values ​​of fluid turbulence, and using the geometric regularization steps of the liquid-cooled plate flow channel optimization method, this paper analyzes the flow separation critical point on an inclined wall (i.e., the specific angle at which flow separation begins to form vortices, identified through computational fluid dynamics simulation). It correlates the extreme values ​​of thermal deformation (e.g., the critical temperature of material thermal deformation) in the manufacturing constraint data package with the material's thermal expansion characteristics (e.g., the coefficient of linear expansion) to assess the risk of dimensional changes under thermal load. Simultaneously, it correlates the critical values ​​of fluid turbulence (e.g., the critical Reynolds number) with flow stability (e.g., laminar flow maintenance capability) to predict the flow deterioration threshold. Finally, through multiphysics coupling analysis, it integrates thermal expansion constraints (to avoid overheating leading to structural interference) and flow stability constraints (to avoid separation or turbulence intensification). An iterative optimization algorithm (e.g., gradient search) is used to balance these requirements, outputting the maximum allowable angle value that simultaneously satisfies thermal reliability and flow efficiency.

[0051] By analyzing the flow separation critical point of fluid on an inclined wall, the extreme value of thermal deformation is correlated with the thermal expansion characteristics of the material to assess the risk of dimensional changes under thermal load; the critical value of fluid turbulence is correlated with flow stability to predict the inflection point of flow deterioration; by integrating the thermal expansion characteristics of the material and the flow stability, and by using gradient search to balance the combined effects of the thermal expansion characteristics of the material and the flow stability, the maximum inclination angle of the flow channel wall is determined, thereby obtaining the maximum allowable inclination angle.

[0052] S2: Based on the manufacturing constraint data package, the constraint compliance is verified by the material distribution optimization algorithm to generate the flow channel planar topology, and the three-dimensional entity of the flow channel is obtained through structural dimensional transformation.

[0053] S2.1: The manufacturing constraint data package includes the minimum forming size and the maximum allowable tilt angle;

[0054] Specifically, the minimum forming size in the manufacturing constraint data package ensures that the channel wall thickness meets the minimum requirements, avoiding cracks or deformations caused by insufficient structural strength, thereby guaranteeing the mechanical reliability of the channel. The maximum permissible tilt angle controls the maximum tilt angle of the channel wall, preventing overhangs or collapses during manufacturing and ensuring the manufacturability of the channel geometry. The minimum forming size and the maximum permissible tilt angle work together to transform process constraints into specific design constraints, providing executable boundary conditions for topology optimization and ensuring that the channel design meets both performance requirements and manufacturing process compatibility.

[0055] S2.2: Construct a boundary condition matrix based on the minimum forming size and the maximum allowable tilt angle, and generate the flow channel planar topology by calculating the material distribution in Euclidean space using a gradient-sensitive algorithm;

[0056] It should be noted that, based on the minimum forming size and maximum allowable tilt angle in the manufacturing constraint data package, the material is mapped to a planar mesh with a unit mesh spacing to obtain the flow channel planar mesh. The minimum forming size is used as the minimum material density of a single flow channel planar mesh; the maximum allowable tilt angle is used as the maximum allowable density gradient of a single flow channel planar mesh; and the ratio of the maximum allowable tilt angle to the flow channel planar mesh spacing is used as the upper limit of the density gradient. The boundary condition matrix stores the minimum material density and the maximum allowable density gradient, with rows corresponding to the coordinates of flow channel planar mesh points and columns corresponding to the minimum material density and the maximum allowable density gradient, thus constructing the boundary condition matrix.

[0057] Based on the minimum material density and the maximum allowable density gradient in the boundary condition matrix, the density gradient value in Euclidean space (two-dimensional space) is calculated. The flow channel planar meshes with density gradient values ​​less than the maximum allowable density gradient and density values ​​less than the minimum material density are integrated to generate the flow channel planar topology. The expression for calculating the density gradient value is:

[0058] ;

[0059] in, This represents the density gradient value. This represents the mesh density value of the flow channel plane. This is the index value of the flow channel plane grid row. This is the index value of the flow channel plane grid column. Indicates that it is located at the th line, number The grid density value of the flow channel plane in the column. Indicates that it is located at the th line, number The grid density value of the flow channel plane in the column. Indicates that it is located at the th line, number The grid density value of the flow channel plane in the column. Indicates that it is located at the th line, number The grid density value of the flow channel plane in the column.

[0060] S2.3: Extend the flow channel planar topology at equal intervals, and use the maximum allowable tilt angle to smooth curvature abrupt changes through the tilt angle compensation algorithm to form a three-dimensional solid flow channel.

[0061] It should be noted that the flow channel planar topology is used as input, and a fixed distance is extended along the normal direction. The extension distance is directly adopted from the minimum forming size value (e.g., minimum wall thickness value) in the manufacturing constraint data package to generate a preliminary three-dimensional solid frame.

[0062] The angle between the normal vector of each point on the surface of the preliminary three-dimensional solid frame and the vertical direction is used as the tilt angle value. The excess area where the tilt angle value exceeds the maximum allowable tilt angle is identified. Local geometric adjustments are applied to the excess area. The curvature is optimized by inserting transition surfaces or adjusting the vertex coordinates of the flow channel plane mesh, so that the tilt angle value is reduced to the maximum allowable tilt angle range, thus forming a three-dimensional solid flow channel.

[0063] S3: Establish a thermal-fluid-solid data exchange channel based on the three-dimensional entity of the flow channel, and generate a hierarchical verification report through multi-physics field coupling verification.

[0064] S3.1: Extract the surface curvature features of the three-dimensional solid of the flow channel, and obtain the topological carrier nodes through geometric feature topological mapping;

[0065] It should be noted that, based on the three-dimensional solid of the flow channel, the normal vectors of the surface flow channel planar mesh are extracted, and the ratio of the difference between the normal vectors of the preceding and subsequent surface patches to the normal vector of the preceding surface patch is used as the rate of change between the normal vectors of adjacent surface patches.

[0066] Based on the rate of change between the normal vectors of adjacent facets, regions where the rate of change exceeds the material stress limit and the fluid turbulence critical value are identified as curvature change regions. Combining the material stress limit and the fluid turbulence critical value in the manufacturing constraint data package as the basis for judging curvature abrupt changes, regions where the curvature change exceeds the material stress limit and the fluid turbulence critical value are marked as feature points. The marked feature points are associated with the flow channel plane grid coordinates on the three-dimensional solid surface of the flow channel to form a set of feature points containing spatial location and curvature attributes.

[0067] Based on a set of feature points containing spatial location and curvature attributes (such as curvature amplitude, rate of curvature change, and associated manufacturing constraint parameters), each feature point in the set is mapped to a topological carrier node. Each node inherits the spatial coordinates and curvature attribute values ​​of the feature points, thus forming a set of topological carrier nodes.

[0068] S3.2: Establish thermal-fluid-solid data links between topological carrier nodes and establish thermal-fluid-solid data exchange channels through vector fusion algorithms;

[0069] It should be noted that bidirectional transmission paths between nodes are configured based on the topological carrier node set, and the node spacing is obtained based on spatial coordinates. At the same time, a data channel frame is declared; the temperature field channel frame transmits the temperature gradient vector; the flow field channel frame transmits the fluid velocity vector and pressure scalar; and the solid field channel frame transmits the stress tensor. The temperature field channel frame, the flow field channel frame, and the solid field channel frame are used as data channel frames.

[0070] Subsequently, based on the process constraint parameters (thermal deformation extreme value, fluid turbulence critical value, and material stress limit) in the manufacturing constraint data package, the thermal deformation extreme value is mapped to the temperature gradient warning value of the temperature field channel; the fluid turbulence critical value is mapped to the velocity vortex identification standard of the flow field channel; the material stress limit is mapped to the stress concentration judgment benchmark of the solid field channel; and the timestamp is synchronously bound to the data channel framework to ensure the time sequence alignment of multi-physics data, thereby generating a thermal-fluid-solid data exchange channel.

[0071] S3.3: Analyze the extreme temperature gradient region, fluid vortex region, and stress concentration region in the thermal-fluid-solid data exchange channel to form a set of physical field feature vectors;

[0072] It should be noted that the temperature gradient vector in the temperature field channel frame is extracted, and the temperature gradient warning value mapped by the manufacturing constraint data package is used as the judgment criterion to identify the region where the temperature gradient exceeds the extreme value of thermal deformation as the temperature gradient extreme value region; the fluid velocity vector in the flow field channel frame is extracted simultaneously, and the vortex identification standard mapped by the manufacturing constraint data package is used as the judgment criterion to identify the region where the vortex intensity exceeds the critical value of fluid turbulence as the fluid vortex region; the stress tensor in the solid field channel frame is extracted, and the stress concentration judgment criterion mapped by the manufacturing constraint data package is used as the judgment criterion to identify the region where the stress exceeds the material stress limit as the stress concentration region.

[0073] The physical properties (temperature gradient amplitude, vortex intensity, and stress concentration factor) of the temperature gradient extremum region, fluid vortex region, and stress concentration region are extracted and combined into a multi-dimensional vector to form a physical field feature vector set. Finally, the temporal consistency of the physical field feature vector set is verified to ensure that all vectors reflect the multi-physics state at the same time, and a temporally aligned physical field feature vector set is output.

[0074] S3.4: Construct the coefficient matrix of the thermo-fluid-structure interaction equation based on the feature vector set, and generate a structured hierarchical verification report by separating the inter-field interaction terms.

[0075] It should be noted that the temperature gradient magnitude is obtained from the physical field eigenvector set as the temperature field input of the heat conduction equation to generate the temperature field coefficient matrix; the vortex intensity is used as the flow field velocity input of the Navier-Stokes equation to obtain the flow field coefficient matrix; the stress concentration factor is used as the stress field input of the solid elasticity equation to obtain the solid field coefficient matrix; and the node distribution of the discretized equation is determined based on the spatial coordinates of the topological carrier node set.

[0076] The extreme value parameter of thermal deformation is used as the coupling strength between the temperature field and the solid field; the critical value parameter of fluid turbulence is used as the coupling strength between the flow field and the temperature field; and the material stress limit parameter is used as the coupling strength between the solid field and the flow field. The temperature field coefficient matrix, flow field coefficient matrix, and solid field coefficient matrix are integrated according to the coupling strength between the temperature field and the solid field, the coupling strength between the flow field and the temperature field, and the coupling strength between the solid field and the flow field. The time synchronization of the data is confirmed through the thermal-fluid-solid data exchange channel, and a structured layered verification report is generated.

[0077] Furthermore, the heat conduction equation, based on Fourier's law, obtains the spatial distribution and temporal variation of the temperature field, quantifies the thermal conductivity of the flow channel wall, and accurately locates the high-temperature region (hot spot) caused by thermal resistance, providing core temperature data for evaluating heat dissipation performance.

[0078] The Navier-Stokes equations are used to characterize the fluid dynamics of coolant within flow channels. By applying the principles of mass and momentum conservation, they simulate the pressure field, velocity field, and turbulence effects of the fluid, analyzing flow resistance distribution, vortex generation, and flow separation phenomena. This provides a fluid-side basis for optimizing flow channel morphology to reduce pressure drop and improve cooling efficiency.

[0079] The equations of solid elasticity are used to calculate the mechanical response of flow channel structures under thermal-fluid loads. Based on the constitutive relationship of stress and strain, the stress and strain fields of the solid domain are obtained, stress concentration regions caused by pressure or thermal deformation are identified, structural reliability is assessed, and mechanical criteria are provided to prevent fatigue failure.

[0080] S4: Construct a defect source mapping model, extract defect features from the hierarchical verification report for analysis and optimization, and generate a targeted optimization instruction set.

[0081] S4.1: Employing the cross-field coupling feature separation method, the three-dimensional coordinates of the temperature gradient extreme region, fluid vortex region, and stress concentration region are simultaneously extracted to generate the spatial coordinates of the defect features;

[0082] It should be noted that the index of entries whose temperature gradient amplitude exceeds the extreme value of thermal deformation is used as the identifier of the extreme value region of temperature gradient, the index of entries whose vortex intensity exceeds the critical value of fluid turbulence is used as the identifier of the fluid vortex region, and the index of entries whose stress concentration factor exceeds the stress limit of the material is used as the identifier of the stress concentration region.

[0083] Based on the topological carrier node set, temperature gradient extreme region identifier, fluid vortex region identifier, and stress concentration region identifier, the spatial coordinates of the corresponding index nodes in the topological carrier node set are mapped to the coordinates of the temperature gradient extreme region, fluid vortex region, and stress concentration region, respectively, forming a three-field defect region spatial coordinate set. The temporal consistency between the three-field defect region spatial coordinate set and the original physical field data is verified, and the coordinates are unified to the spatial reference system of the topological carrier node set to ensure temporal alignment and spatial consistency. Finally, the three-field defect region spatial coordinate sets are integrated, and each record is associated with the physical attribute values ​​(temperature gradient amplitude, vortex intensity, and stress concentration coefficient) in the physical field feature vector set to generate defect feature spatial coordinates.

[0084] S4.2: Based on the three-dimensional solid of the flow channel, map the spatial coordinates of the defect features to the flow channel design parameters and obtain the defect design parameter correlation matrix;

[0085] It should be noted that each coordinate point in the defect feature space coordinates is matched with the nearest neighbor of the flow channel plane mesh node on the surface of the flow channel three-dimensional entity to find the corresponding node index; the flow channel design parameters corresponding to the node index are extracted from the flow channel three-dimensional entity, including topology density, flow channel width and wall inclination angle.

[0086] Based on the manufacturing constraint data package (thermal deformation extreme value parameters, fluid turbulence critical value parameters, and material stress limit parameters) and the physical property values ​​of defects (temperature gradient amplitude, vortex intensity, and stress concentration factor), the direction of design parameter adjustment is determined (e.g., exceeding the temperature gradient limit increases the topology density, exceeding the vortex intensity limit expands the flow channel width, and exceeding the stress concentration limit reduces the wall inclination angle) to obtain the adjusted flow channel design parameters;

[0087] Integrate the flow channel design parameters and design parameter adjustment directions of all coordinate points to generate a defect design parameter correlation matrix. The rows of the defect design parameter correlation matrix correspond to the coordinate points, and the columns contain spatial coordinates, design parameter adjustment directions, and adjusted design parameters.

[0088] S4.3: Extract the temperature gradient, pressure drop and stress amplitude from the defect design parameter correlation matrix, calculate the physical field coupling strength through the field coupling strength algorithm, and finally construct the defect source tracing mapping model;

[0089] It should be noted that the pressure drop is obtained from the flow field channel data in the statistical design parameter correlation matrix, the stress amplitude is obtained from the statistical design parameter correlation matrix, and the temperature gradient is obtained from the temperature gradient amplitude in the statistical extraction defect design parameter correlation matrix, thus generating a physical field parameter set.

[0090] Based on the physical field parameter set, the extreme values ​​of thermal deformation in the manufacturing constraint data package are used as temperature field weights, the critical values ​​of fluid turbulence as flow field weights, and the material stress limit parameters as solid field weights. The temperature field weights, flow field weights, and solid field weights are nonlinearly fused to generate inter-field coupling coefficients. The coupling strength value at each point is calculated using the single-point coupling strength formula, and the coupling strength values ​​at all points are statistically analyzed to obtain the global coupling strength. The expression for calculating the coupling strength value is:

[0091] ;

[0092] in, This represents the coupling strength value. This represents the temperature gradient value. For pressure reduction, The stress amplitude, This represents the extreme value of thermal deformation. This is the critical value for fluid turbulence. The material stress limit The inter-field coupling coefficient;

[0093] The inter-field coupling coefficient was determined through thermo-fluid-solid coupled simulation. The simulation results were compared with high-fidelity measurement data (such as PIV flow field data, infrared thermal imager temperature data, and strain gauge stress data). The inter-field coupling coefficient that minimizes the error between the simulated value and the high-fidelity measurement data was selected as the final value. The range of values ​​is as follows: .

[0094] Based on the coupling strength value and the spatial coordinate set of defect features, the defect source tracing mapping model includes spatial coordinates, temperature gradient values, pressure drop values, stress amplitudes, and coupling strength values ​​for each coordinate point in the corresponding defect feature spatial coordinate set. The spatial coordinates are read from the defect feature spatial coordinate set. The temperature gradient values, pressure drop values, and stress amplitudes of the corresponding coordinate points are read based on the defect design parameter correlation matrix. The inter-field coupling coefficient is calibrated by gradually reducing the error between the simulation results and the high-fidelity measurement data. At the same time, the matching degree between the spatial coordinates and the high-fidelity measurement data is verified, and the defect source tracing mapping model is generated.

[0095] S4.4: Extract defect features from the hierarchical verification report and input them into the defect source mapping model. Then, fuse the coefficient matrix of the thermal-fluid-structure interaction equation to generate a directional optimization instruction set.

[0096] It should be noted that, based on the hierarchical verification report, the spatial coordinate set of defect features is extracted; the spatial coordinate set of defect features is input into the defect tracing mapping model. When the temperature gradient value exceeds the thermal deformation extreme value parameter in the manufacturing constraint data package, the topology density needs to be increased; when the stress amplitude exceeds the material stress limit parameter, the wall inclination angle needs to be reduced, and parameter adjustment instructions are generated.

[0097] Each adjustment value in the parameter adjustment command is mapped to a corresponding position in the coefficient matrix of the thermo-fluid-structure interaction equation. For example, the topology density adjustment value is mapped to the coefficient region related to the temperature field in the matrix, the channel width adjustment value is mapped to the coefficient region related to the flow field, and the wall inclination angle adjustment value is mapped to the coefficient region related to the solid field.

[0098] Based on the existing inter-field coupling relationships (such as the interaction coefficients between the temperature field and the flow field) in the coefficient matrix of the thermo-fluid-structure interaction equation, the specific values ​​of the parameter adjustment commands are adjusted. For example, if there is a strong coupling between the temperature field and the flow field, the relevant flow field parameters need to be adjusted simultaneously when adjusting the temperature gradient. The adjusted parameter adjustment commands are then categorized according to the spatial coordinates of the defect features to generate a set of directional optimization commands.

[0099] S5: Executes the directional optimization instruction set to reconstruct the three-dimensional solid of the flow channel, and generates a performance compliance certification report through geometric process closed-loop calibration.

[0100] S5.1: Analyze the spatial location and operation parameters in the directional optimization instruction set, drive the three-dimensional entity of the flow channel to adjust the geometric structure, and generate the reconstructed three-dimensional entity of the flow channel;

[0101] It should be noted that, based on the directional optimization instruction set, the spatial location (x, y, z coordinates) of each instruction is parsed to obtain the instruction coordinates and operation parameters (such as topology density change, width change, and wall tilt angle change).

[0102] Locate the flow channel plane mesh node in the three-dimensional entity corresponding to the spatial position of the command, and then adjust the material density value at the node according to the change in topology density. For example, expand the material distribution range when the topology density is increased, and shrink the material distribution range when the topology density is decreased, to ensure that the density change meets the minimum forming size requirement in the manufacturing constraint data package.

[0103] The system identifies the spatial location of the instruction and the corresponding flow channel cross-section location. Then, it modifies the cross-section dimensions based on the width change. For example, when the width is increased, the cross-section profile is offset outward, and when the width is decreased, the cross-section profile is offset inward. At the same time, the flow channel wall thickness meets the minimum forming size limit in the manufacturing constraint data package.

[0104] The system locates the surface region corresponding to the spatial position of the positioning command, and then adjusts the surface curvature according to the change in wall inclination angle. For example, it increases the smoothness of the transition surface when the inclination angle decreases, and reduces the curvature change gradient when the inclination angle increases, ensuring that the final inclination angle value does not exceed the maximum allowable inclination angle parameter in the manufacturing constraint data package. The reconstructed 3D solid of the flow channel is then generated.

[0105] S5.2: Based on the manufacturing constraint data package, the reconstructed three-dimensional solid of the flow channel is subjected to structural compliance verification, and the data is input into the thermal fluid-solid data exchange channel to perform lightweight coupling analysis and output calibration performance data;

[0106] It should be noted that the structural compliance of the reconstructed flow channel 3D entity is verified based on the manufacturing constraint data package. The geometric features of the flow channel 3D entity are checked, and the minimum wall thickness is measured to ensure that it meets the minimum forming size and the surface tilt angle meets the maximum allowable tilt angle requirements in the manufacturing constraint data package.

[0107] The verified three-dimensional solid flow channel is input into the thermal fluid-solid data exchange channel to extract performance data of temperature field, flow field, and solid field (such as temperature gradient, pressure drop, and stress amplitude). By comparing the minimum forming size requirement and maximum allowable tilt angle in the manufacturing constraint data package, the calibration performance data is finally output.

[0108] S5.3: Combine calibration performance data with stratified verification reports to generate a performance compliance certification report through differential comparison.

[0109] It should be noted that the temperature gradient benchmark in the extreme temperature gradient region, the flow velocity benchmark in the fluid vortex region, and the stress benchmark in the stress concentration region of the stratified verification report are extracted and combined with the calibration performance data to form a data pair set.

[0110] For each data pair in the data pair set, the temperature gradient difference is the difference between the measured temperature gradient value and the reference temperature gradient value in the calibration performance data, the pressure drop difference is the difference between the measured pressure drop value and the reference pressure drop value in the calibration performance data, and the stress amplitude difference is the difference between the measured stress amplitude value and the reference stress amplitude value in the calibration performance data.

[0111] The compliance status is evaluated based on the process limitation parameters in the manufacturing constraint data package. If the temperature gradient difference is not greater than the extreme value of thermal deformation, the pressure drop difference is not greater than the critical value of fluid turbulence, and the stress amplitude difference is not greater than the material stress limit, then the data is marked as compliant; otherwise, it is marked as non-compliant and the difference exceeding the limit is recorded.

[0112] Finally, generate a report containing calibration performance data, stratified verification report, differential comparison results, and overall performance compliance conclusion (such as "fully compliant" or "partially compliant" with a note of parameters that did not meet the standard).

[0113] This embodiment also provides a computer device applicable to the liquid cooling plate flow channel optimization method based on topology optimization, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the liquid cooling plate flow channel optimization method based on topology optimization as proposed in the above embodiment.

[0114] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0115] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the topology-optimized liquid cooling plate flow channel optimization method proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0116] In summary, this invention avoids secondary rework caused by disconnection in traditional methods by deeply embedding manufacturing constraints into the topology optimization process, thereby improving the first-pass yield of designs. At the same time, it constructs a defect source tracing mapping model based on multi-physics field coupling verification and generates a directional optimization instruction set, forming a fully closed-loop feedback optimization method.

[0117] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing a flow channel of a liquid cooling plate based on topology optimization, characterized in that: The method comprises the following steps: Collecting liquid cooling plate process limit data and generating manufacturing constraint data packet through preprocessing; Based on the manufacturing constraint data packet, the material distribution optimization algorithm is used to perform constraint compliance verification to generate a flow channel plane topology structure, and a flow channel three-dimensional entity is obtained through structure dimension upgrading conversion; According to the flow channel three-dimensional entity, a heat-fluid-solid data exchange channel is established, and a layered verification report is generated through multi-physical field coupling verification; A defect trace mapping model is constructed, defect features in the layered verification report are extracted for analysis and optimization, and a directional optimization instruction set is generated; The directional optimization instruction set is executed to reconstruct the flow channel three-dimensional entity, and a performance standard certification report is generated through geometric process closed-loop calibration.

2. The topology optimization based liquid cold plate runner optimization method of claim 1, wherein: The liquid cooling plate process limit data includes thermal deformation extreme value, material stress limit and fluid turbulent critical value; The preprocessing includes data cleaning, normalization processing and geometric regularization processing.

3. The topology optimization based liquid cold plate runner optimization method of claim 2, wherein: The manufacturing constraint data packet includes minimum forming size and maximum allowable inclination angle; Based on the manufacturing constraint data packet, the material distribution optimization algorithm is used to perform constraint compliance verification to generate a flow channel plane topology structure, and a flow channel three-dimensional entity is obtained through structure dimension upgrading conversion, the specific steps are as follows Based on the minimum forming size and the maximum allowable inclination angle, a boundary condition matrix is constructed, and the material distribution in the Euclidean space is calculated through a gradient sensitive algorithm to generate a flow channel plane topology structure; The flow channel plane topology structure is extended equidistantly, and the maximum allowable inclination angle is called to smooth the curvature mutation through an inclination compensation algorithm to form a flow channel three-dimensional entity.

4. The topology optimization based liquid cold plate runner optimization method of claim 3, wherein: According to the flow channel three-dimensional entity, a heat-fluid-solid data exchange channel is established, and a layered verification report is generated through multi-physical field coupling verification, The surface curvature features of the flow channel three-dimensional entity are extracted, and a topological carrier node is obtained through geometric feature topology mapping; A heat-fluid-solid data link is established between the topological carrier nodes, and a heat-fluid-solid data exchange channel is established through a vector fusion algorithm.

5. The topology optimization based liquid cold plate runner optimization method of claim 4, wherein: The layered verification report is generated through multi-physical field coupling verification, and the specific steps are as follows The temperature gradient extreme value area, fluid vortex area and stress concentration area in the heat-fluid-solid data exchange channel are analyzed to form a physical field feature vector set; Based on the feature vector set, a heat-fluid-solid coupling equation coefficient matrix is constructed, and a structured layered verification report is generated by separating the interaction items between fields.

6. The topology optimization based liquid cold plate runner optimization method of claim 5, wherein: The specific steps of constructing the defect trace mapping model are as follows The three-dimensional coordinates of the temperature gradient extreme value area, fluid vortex area and stress concentration area are extracted synchronously by using the cross-field coupling feature separation method to generate a defect feature space coordinate; Based on the flow channel three-dimensional entity, the defect feature space coordinate is mapped to the flow channel design parameter to obtain a defect design parameter correlation matrix; The temperature gradient, pressure drop and stress amplitude in the defect design parameter correlation matrix are extracted, the physical field coupling strength is calculated through a field coupling strength algorithm, and finally the defect trace mapping model is constructed.

7. The topology optimization based liquid cold plate runner optimization method of claim 6, wherein: The directional optimization instruction set is generated by inputting the defect features in the layered verification report into the defect trace mapping model and fusing the heat-fluid-solid coupling equation coefficient matrix.

8. The topology optimization based liquid cold plate runner optimization method of claim 7, wherein: The directional optimization instruction set is executed to reconstruct the flow channel three-dimensional entity, and a performance standard certification report is generated through geometric process closed-loop calibration, the specific steps are as follows, The spatial position and operation parameters in the directional optimization instruction set are analyzed, a geometric structure adjustment of the flow channel three-dimensional entity is driven, and a reconstructed flow channel three-dimensional entity is generated; Based on the manufacturing constraint data packet, the structure compliance of the reconstructed flow channel three-dimensional entity is verified, and the heat flow solid data exchange channel is input to perform lightweight coupling analysis to output calibration performance data; Combined with the calibration performance data and the layered verification report, a performance standard authentication report is generated by differential comparison. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the liquid cooling plate flow channel optimization method based on topological optimization in any one of claims 1-8.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the liquid cooling plate flow channel optimization method based on topological optimization in any one of claims 1-8.

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