Multi-scale heatproof structure optimization design method based on heterogeneous dot matrix fusion

Abstract

The invention relates to a multi-scale heat-proof structure optimization design method based on heterogeneous dot matrix fusion. The method comprises the following steps: constructing different types of dot matrix structures, and establishing a topological optimization mathematical model of a heat insulation structure to obtain a structure density field and a node temperature value; performing bilinear interpolation on the node temperature value to obtain a structure normalized temperature field; carrying out pooling treatment to obtain a pooled unit density field and a normalized temperature field; establishing a cell element type selection mechanism based on the unit normalization temperature field after pooling; according to a cell type selection mechanism, correlating cell configurations of the units, pooled unit density fields and space coordinates; and carrying out heterogeneous dot matrix fusion filling design on the design domain, and carrying out performance verification comparative analysis to complete the multi-scale optimization design of the heat-proof structure. According to the method, topological optimization design and lattice structure design are creatively combined, the advantages of the two design methods are brought into full play, macro-micro multi-scale optimization design of the heat protection structure is achieved, and the heat insulation performance and continuity of the whole structure are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of structural lightweight design and structural optimization, and particularly to a multi-scale thermal protection structure optimization design method based on heterogeneous lattice fusion. Background Technique

[0002] The Triply Periodic Minimal Surfaces (TPMS) lattice structure has many excellent thermal properties such as a high specific surface area and good fluid flow characteristics, and is easy to realize parametrically autonomous and controllable design. The structural parameters can be flexibly adjusted according to performance requirements, and it has a wide application prospect in active cooling structures. Topological optimization can find the best material distribution that meets various performance requirements through iteration within a fixed design domain, and obtain an excellent macroscopic material distribution.

[0003] However, the existing lattice design methods are mainly homogeneous or gradient lattice filling designs, and the best material distribution cannot be obtained macroscopically. Topological optimization is mostly a 0-1 material distribution, focusing on the macroscopic material distribution problem, and cannot optimize the performance in the microscopic configuration. In addition, the current optimization design mostly focuses on the single-configuration lattice optimization design, ignoring the complex working conditions of the structure. Summary of the Invention

[0004] In view of the above-mentioned deficiencies of the prior art, the present invention provides a multi-scale thermal protection structure optimization design method based on heterogeneous fusion lattices, which solves the problems that the existing lattice design methods focus on the macroscopic material distribution problem, cannot optimize the performance in the microscopic configuration, and the existing optimization design mostly focuses on the single-configuration lattice optimization design, ignoring the complex working conditions of the structure. The technology analyzes the performance of multiple TPMS lattice structures, studies their performance differences, and numbers each type of configuration. Through topological optimization design, an excellent macroscopic material distribution and temperature distribution are obtained, and interpolation and pooling processing are performed. Based on the temperature distribution, the cell type is selected to give full play to the performance advantages of the lattice structure. The cell type of the structure, the pooled cell density field, and the spatial coordinates are associated according to the unit number. The heterogeneous fusion lattice design is realized by using the Gaussian radial basis function, effectively improving the heat insulation performance and thermal uniformity of the structure under active cooling conditions.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A multi-scale thermal protection structure optimization design method based on heterogeneous lattice fusion, comprising the following steps:

[0006] S1. Construct models of different types of TPMS lattice structures, numerically calculate their performance under active cooling conditions, and number different TPMS configurations to obtain the correlation curves of the equivalent thermal conductivity and relative density of different configurations;

[0007] S2. Establish a mathematical model for the topological optimization of the thermal insulation structure. According to the boundary conditions of the design domain and the initial parameters, use the variable density method for topological optimization design to obtain the structural density field and node temperature values;

[0008] S3. Perform bilinear interpolation on the node temperature values to obtain the element center temperature values, and then divide each element temperature by the highest element temperature in the structure to obtain the normalized temperature field of the structure;

[0009] S4. Perform average pooling on the topological optimized structural density field and the normalized temperature field of the structure to obtain the pooled element density field and the pooled normalized temperature field of the element;

[0010] S5. Based on the performance of different TPMS lattice structures in S1 and the pooled normalized temperature field of the element in S4, establish a cell selection mechanism based on the pooled normalized temperature field of the element;

[0011] S6. According to the cell selection mechanism, select the cell configuration of each element, and associate the cell configuration of the element, the pooled element density field, and the spatial coordinates through the element number;

[0012] S7. Use the Gaussian radial basis function to perform heterogeneous lattice fusion filling design on the design domain;

[0013] S8. Perform performance verification and comparative analysis on the optimized design heterogeneous fusion lattice to complete the multi-scale optimization design of the thermal protection structure.

[0014] Furthermore, in step S1, construct different types of TPMS lattice structure models, perform numerical calculations on their performance under the active cooling condition, and number different TPMS configurations to obtain the correlation curve between the equivalent thermal conductivity and relative density of different configurations. The specific process includes the following steps:

[0015] S11. The constructed TPMS lattice structure includes determining the lattice type, unit cell size, relative density, lattice scale, density ρ of the material used in the structure, thermal conductivity k, flow velocity v of the fluid, and fixed high temperature on the lower surface of the structure. The lattice type is four types of TPMS lattice configurations, namely Diamond diamond-type minimal surface lattice structure, Gyroid gyroid-type minimal surface lattice structure, Primitive primitive-type minimal surface lattice structure, and I-Wrapped Package wrapped-type minimal surface lattice structure;

[0016] S12. Calculate the equivalent thermal conductivity k of the structure according to the temperature difference between the upper and lower surfaces of the structure and the heat flux density of the heat source surface eff :

[0017]

[0018] where keff is the structural equivalent thermal conductivity; q is the heat flux density of the heat source surface; H is the heat flux transfer thickness; T a is the temperature of the heat source surface; T b is the average temperature of the upper surface of the structure;

[0019] S13. Number each type of cell. Among them, the Diamond structure is numbered D; the Gyroid structure is numbered G; the Primitive structure is numbered P; the I-WrappedPackage structure is numbered IWP;

[0020] S14. Construct the implicit function of the TPMS lattice structure to obtain the relative density correlation curve;

[0021] S15. In the computer programming language, establish an index for each type according to the performance differences of different cells, and the index needs to be unique.

[0022] Further, in step S14, the implicit function of the constructed TPMS lattice structure specifically includes:

[0023] f solid-D (x, y, z) = sinXsinYsinZ + sinXcosYcosZ +

[0024] cosXsinYcosZ + cosXcosYsinZ - t

[0025] f solid-G (x, y, z) = sinXcosY + sinYcosZ + sinZcosX - t

[0026] f solid-P (x, y, z) = cosX + cosY + cosZ -

[0027] 0.51(cosXcosY + cosYcosZ + cosZcosX) - t

[0028] f solid-IWP (x, y, z) = cosXcosY + cosXcosZ + cosYcosZ -

[0029] 0.51(cos2X + cos2Y + cos2Z) - t

[0030] where X = 2πx / L, Y = 2πy / L, Z = 2πz / L; L is the cell size of the TPMS; t is the level set constant for controlling the relative density of the TPMS; x, y, z are the three axial coordinates in the Cartesian coordinate system.

[0031] Further, in step S4, in step S2, the variable density method is used for topology optimization design to obtain the structural density field and the node temperature values, specifically including: the topology optimization takes the minimization of the average temperature on the upper surface of the structure as the optimization objective, and at the same time restricts the relative density of the overall structure. The topology optimization model is as follows:

[0032]

[0033] where ρ i represents the relative density of the i-th element; ρ is the relative density of the overall structure; minC is the topology optimization objective function, minimizing the average temperature on the upper surface of the structure; C is the average temperature on the upper surface of the structure; e is the set of nodes on the upper surface of the structure for target optimization; T is the node temperature; F is the thermal load vector of the overall structure; K is the heat transfer matrix of the overall structure; R is the node temperature vector of the overall structure; K i is the heat transfer matrix of the i-th element; R i is the node temperature vector of the i-th element; is the transpose of the node temperature vector of the i-th element; v i is the volume of the i-th element, and V is the volume constraint of the overall structure; ρ min , ρ max are the upper and lower limits of the element density.

[0034] Further, in step S4, bilinear interpolation is performed on the node temperature values, and the formula is as follows:

[0035]

[0036] where T 1 , T 3 , T 7 , T 9 are the temperature values of the four nodes of the element; T 2 , T 8 are the temperatures at the midpoints of the upper and lower sides of the element; T 5 is the temperature at the center of the element; x 1 , y 1 , x 1 , y 2 , x 2 , y 1 , x 2 , y 2 are the coordinates of the four nodes of the element; x, y are the coordinates of the center of the element.

[0037] Further, in step S4, average pooling processing is performed on the topology-optimized structural density field and the structural normalized temperature field, specifically including: regarding adjacent 2×2 elements as a complete element, adding the internal numerical values and then dividing by 4, and taking the obtained average value as the pooled element density field and the pooled element normalized temperature field.

[0038] Further, in step S5, based on the performance of different TPMS lattice structures in S1 and the pooled unit normalized temperature field in S4, a cell selection mechanism based on the pooled unit normalized temperature field is established. The specific process includes the following steps:

[0039] S51. Judge the temperature at the center of the unit, and divide the overall design domain into a high-temperature region and a low-temperature region through the pooled unit normalized temperature field;

[0040] S52. Fill the high-temperature region with a D-structure lattice type with a lower equivalent thermal conductivity, and fill the low-temperature region with a G-structure lattice type with better flow characteristics to obtain the unit configuration matrix S i (T′), as follows:

[0041]

[0042] where S i is the unit type; G is the Gyroid structure number; D is the Diamond structure number; T i ′ is the normalized temperature of the i-th unit after pooling.

[0043] Further, the cell configuration of the unit, the pooled unit density field, and the spatial coordinates are associated through the unit number, as follows:

[0044]

[0045] where S i is the cell type of the i-th unit; ρ i ′ is the relative density of the i-th unit after pooling; X i is the spatial coordinate of the i-th unit

[0046] Further, in step S7, the heterogeneous lattice fusion filling design of the design domain is carried out using the Gaussian radial basis function, and its formula is as follows:

[0047]

[0048] where, f fus is the composite lattice expression, f 1 , f 2 is the expression of two basic lattices, m is the transition interval regulation parameter, x 1 , y 1 , z 1 is the center point coordinate of lattice 1, x 2 , y 2 , z 2 is the center point coordinate of lattice 2, x, y, z are the coordinates of the middle position between two cells.

[0049] Further, in step S8, the STL model of the heterogeneous fusion lattice is repaired, materialized, a fluid domain is created, boundary conditions are applied, and CFD simulation analysis is performed.

[0050] With the above technical solutions, the present invention provides a multi-scale thermal protection structure optimization design method, system, device and medium based on heterogeneous lattice fusion, which at least has the following beneficial effects:

[0051] Through variable density topology optimization design, the present invention obtains the macroscopic material distribution and the temperature distribution field at this time under the optimal heat insulation performance, performs interpolation pooling processing on it, and performs structure zoning according to the pooled normalized temperature. Based on the performance differences of the cells, cell structure selection is carried out for different performance requirements in different regions, and then density mapping design is carried out to complete the heterogeneous fusion lattice design based on topology optimization.

[0052] The present invention innovatively combines topology optimization design with lattice structure design, gives full play to the advantages of the two design methods, realizes the macro-micro multi-scale optimization design of the thermal protection structure, and improves the heat insulation performance and continuity of the overall structure; innovatively proposes a new cell selection mechanism, selects different cell configurations in different regions according to the differences in structural performance requirements, and realizes the improvement of the comprehensive performance of the structure; proposes a heterogeneous fusion lattice design method based on Gaussian radial basis function, and realizes the continuity optimization design of complex transition intervals under large density gradients. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The schematic embodiments and descriptions thereof are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings:

[0054] Figure 1 is a schematic flow chart of the present invention;

[0055] Figure 2 is a schematic diagram of four TPMS equivalent performance curves;

[0056] Figure 3 is a schematic diagram of topology optimization boundaries and structures;

[0057] Figure 4 is a schematic diagram of the cell selection mechanism;

[0058] Figure 5 is a schematic diagram of a heterogeneous fusion lattice generated by an incidence matrix;

[0059] Figure 6 is a schematic diagram of the simulation analysis results and comparison diagrams. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0060] To make the above objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Thereby, a full understanding of the implementation process of how the present application uses technical means to solve technical problems and achieve technical effects can be obtained and implemented accordingly.

[0061] Those of ordinary skill in the art can understand that all or part of the steps in the methods of the above embodiments can be completed by instructing relevant hardware through a program. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0062] Please refer to Figures 1-6 , which shows a specific implementation manner of this embodiment. In this embodiment, through variable density topology optimization design, the present invention obtains the macroscopic material distribution under the optimized heat insulation performance and the temperature distribution field at this time, performs interpolation pooling processing on it, and based on the pooled normalized temperature, performs structural zoning. Based on the performance differences of the unit cells, different unit cell structure selections are made for different performance requirements in different regions, and then density mapping design is carried out to complete the heterogeneous fusion lattice design based on topology optimization, realizing the macro-micro multi-scale optimization design of the heat protection structure, and improving the heat insulation performance and continuity of the overall structure.

[0063] Please refer to Figure 1 , this embodiment proposes a multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion, and this method includes the following steps:

[0064] S1. Construct different types of TPMS lattice structure models, numerically calculate their performance under active cooling conditions, number different TPMS configurations, calculate the correlation model between the equivalent thermal performance of the lattice structure and the relative density, and obtain the correlation curve between the equivalent thermal conductivity and the relative density of different configurations;

[0065] As a preferred implementation manner of step S1, in step S1, different types of TPMS lattice structure models are constructed, their performance under active cooling conditions is numerically calculated, different TPMS configurations are numbered, and the correlation curve between the equivalent thermal conductivity and the relative density of different configurations is obtained. The specific process includes the following steps:

[0066] S11. The constructed TPMS lattice structure includes determining the lattice type, unit cell size, relative density, lattice scale, density ρ, thermal conductivity k of the material used for the structure, flow velocity v of the fluid, and fixed high temperature on the lower surface of the structure. Among them, the lattice type is four types of TPMS lattice configurations, namely Diamond diamond-type minimal surface lattice structure, Gyroid gyroid-type minimal surface lattice structure, Primitive primitive-type minimal surface lattice structure, and I-WrappedPackage wrapped-type minimal surface lattice structure;

[0067] S12. Calculate the equivalent thermal conductivity k of the structure according to the temperature difference between the upper and lower surfaces of the structure and the heat flux density of the heat source surface eff :

[0068]

[0069] where k eff is the equivalent thermal conductivity of the structure; q is the heat flux density of the heat source surface; H is the heat transfer thickness; T a is the temperature of the heat source surface; T b is the average temperature of the upper surface of the structure;

[0070] S13. Number each type of cell. Among them, the Diamond structure is numbered D; the Gyroid structure is numbered G; the Primitive structure is numbered P; the I-WrappedPackage structure is numbered IWP;

[0071] S14. Construct the implicit function of the TPMS lattice structure to obtain the relative density correlation curve;

[0072] More specifically, in step S14, the implicit function of the constructed TPMS lattice structure specifically includes:

[0073] f solid-D (x,y,z) = sinXsinYsinZ + sinXcosYcosZ +

[0074] cosXsinYcosZ + cosXcosYsinZ - t

[0075] f solid-G (x,y,z) = sinXcosY + sinYcosZ + sinZcosX - t

[0076] f solid-P (x,y,z) = cosX + cosY + cosZ -

[0077] 0.51(cosXcosY + cosYcosZ + cosZcosX) - t

[0078] fsolid-IWP (x, y, z) = cosX cosY + cosX cosZ + cosY cosZ -

[0079] 0.51(cos2X + cos2Y + cos2Z) - t

[0080] where X = 2πx / L, Y = 2πy / L, Z = 2πz / L; L is the cell size of the TPMS; t is the level set constant controlling the relative density of the TPMS; x, y, z are the three axial coordinates in the Cartesian coordinate system;

[0081] S15. In computer programming languages, according to the performance differences of different cells, establish an index for each type, and the index needs to be unique.

[0082] S2. Establish a mathematical model for the topological optimization of the thermal insulation structure. According to the boundary conditions of the design domain and the initial parameters, use the variable density method for topological optimization design to obtain the structural density field and the node temperature values;

[0083] As a preferred implementation of step S2, in step S2, using the variable density method for topological optimization design to obtain the structural density field and the node temperature values specifically includes: The topological optimization takes the minimization of the average temperature of the upper surface of the structure as the optimization goal, and at the same time restricts the relative density of the overall structure. The topological optimization model is as follows:

[0084]

[0085] where ρ i represents the relative density of the i-th element; ρ is the relative density of the overall structure; minC is the topological optimization objective function, minimizing the average temperature of the upper surface of the structure; C is the average temperature of the upper surface of the structure; e is the set of nodes on the upper surface of the structure to be optimized; T is the node temperature; F is the thermal load vector of the overall structure; K is the heat transfer matrix of the overall structure; R is the node temperature vector of the overall structure; K i is the heat transfer matrix of the i-th element; R i is the node temperature vector of the i-th element; is the transpose of the node temperature vector of the i-th element; v i is the volume of the i-th element, V is the volume constraint of the overall structure; ρ min , ρ max are the upper and lower limits of the element density.

[0086] S3. Perform bilinear interpolation on the node temperature values to obtain the element center temperature values, and then divide each element temperature by the highest element temperature in the structure to obtain the normalized temperature field of the structure;

[0087] As a preferred embodiment of step S3, in step S3, bilinear interpolation is performed on the node temperature values, and the formula is as follows:

[0088]

[0089]

[0090] where T 1 , T 3 , T 7 , T 9 are the temperature values of the four nodes of the unit; T 2 , T 8 are the midpoint temperatures of the upper and lower sides of the unit; T 5 is the central temperature of the unit; (x 1 , y 1 ), (x 1 , y 2 ), (x 2 , y 1 ), (x 2 , y 2 ) are the coordinates of the four nodes of the unit; (x, y) is the central coordinate of the unit.

[0091] S4. Perform average pooling on the structure density field and the structure normalized temperature field of the topology optimization to obtain the pooled unit density field and the pooled unit normalized temperature field;

[0092] As a preferred embodiment of step S4, performing average pooling on the structure density field and the structure normalized temperature field of the topology optimization specifically includes: regarding adjacent 2×2 units as a complete unit, adding the internal values and dividing by 4, and using the obtained average value as the pooled unit density field and the pooled unit normalized temperature field.

[0093] S5. Based on the performance of different TPMS lattice structures in S1 and the pooled unit normalized temperature field in S4, establish a cell selection mechanism based on the pooled unit normalized temperature field;

[0094] As a preferred embodiment of step S5, based on the performance of different TPMS lattice structures in S1 and the pooled unit normalized temperature field in S4, establishing a cell selection mechanism based on the pooled unit normalized temperature field, the specific process includes the following steps:

[0095] S51. Judge the central temperature of the unit, and divide the overall design domain into a high-temperature area and a low-temperature area through the pooled unit normalized temperature field;

[0096] S52. Since the flow characteristics are highly correlated with the configuration of the structure itself. Due to the relatively large pore size of the G structure itself, it has the lowest friction coefficient among the four structures, which is more conducive to fluid flow. Fill the lattice type of the D structure with a lower equivalent thermal conductivity in the high-temperature region and fill the lattice type of the G structure with better flow characteristics in the low-temperature region to obtain the unit configuration matrix S within the design domain. i (T′) is as follows:

[0097]

[0098] where S i is the unit type; G is the Gyroid structure number; D is the Diamond structure number; T i ′ is the normalized temperature of the i-th unit after pooling.

[0099] S6. According to the cell selection mechanism, select the cell configuration of each unit, and associate the cell configuration of the unit, the unit density field after pooling, and the spatial coordinates through the unit number;

[0100] As a preferred implementation of step S6, in step S6, the cell configuration of the unit, the unit density field after pooling, and the spatial coordinates are associated through the unit number, as follows:

[0101]

[0102] where S i is the cell type of the i-th unit; ρ i ′ is the relative density of the i-th unit after pooling; X i is the spatial coordinate of the i-th unit.

[0103] S7. Use the Gaussian radial basis function to perform heterogeneous lattice fusion filling design on the design domain;

[0104] As a preferred implementation of step S7, in step S7, use the Gaussian radial basis function to perform heterogeneous lattice fusion filling design on the design domain, and its formula is as follows:

[0105]

[0106] where f fus is the composite lattice expression, f 1 , f 2 are the expressions of two basic lattices, which is an arbitrary surface lattice equation, not limited to the G and D structures; m is the transition interval control parameter, x 1 , y 1 , z 1 are the central point coordinates of lattice 1, x 2 , y 2 , z 2is the central point coordinate of the lattice 2, and x, y, and z are the coordinates of the middle position between two unit cells.

[0107] S8. Conduct performance verification and comparative analysis on the optimized heterogeneous fusion lattice, and complete the multi-scale optimization design of the thermal protection structure.

[0108] As a preferred implementation manner of step S8, repair the STL model of the heterogeneous fusion lattice, solidify it, create a fluid domain, apply boundary conditions, and conduct CFD simulation analysis.

[0109] Based on the existing thermal protection structure optimization design in the above technical background, the macro-micro reasonable distribution of materials cannot be achieved, and it is difficult to give full play to the structural advantages. To solve this problem, the embodiments of the present invention provide a multi-scale thermal protection structure design method based on heterogeneous fusion lattice, and the design process is as Figure 1 shown.

[0110] Specifically: The present invention will be described below by taking a design plane of 50mm×25mm as an example.

[0111] S1: First, analyze four types of TPMS lattice configurations with different relative densities to obtain the correlation curves between the equivalent thermal conductivity and relative density of different configurations. The abscissa is the relative density of the structure, and the ordinate is the ratio of the equivalent thermal conductivity of the structure to the thermal conductivity of the material. The smaller the value, the better the heat insulation performance of the structure, and number them respectively. Among them, the Diamond structure is numbered D; the Gyroid structure is numbered G; the Primitive structure is numbered P; the I-Wrapped Package structure is numbered IWP, and the unit size is 5mm; the results are as Figure 2 shown.

[0112] S2 - S4: Divide the plane design domain into 20×10 units, set the fixed temperature boundary condition on the lower surface of the structure, and conduct topology optimization design with the lowest average temperature on the upper surface as the optimization target based on variable density topology optimization design to obtain the structure density distribution field and node temperature values, as Figure 3 shown. Interpolate the node temperature to the unit center point temperature through bilinear interpolation, and then perform normalization processing to obtain the structure normalized temperature field. Perform average pooling processing on the density field and the structure normalized temperature field of the structure, and adjust the unit size of the design domain to 5mm.

[0113] S5 - S6: Establish a unit selection mechanism, as Figure 4 shown. Through the pooled unit normalized temperature field, divide the overall design domain into a high-temperature area and a low-temperature area. Fill the D structure with a lower equivalent thermal conductivity in the high-temperature area, and fill the G structure with better flow characteristics in the low-temperature area to obtain the unit configuration matrix S within the design domain i(T′), which correlates the density field and the cell configuration field by a spatial coordinate matrix, and completes the design of the heterogeneous fusion lattice through Gaussian radial basis functions, as Figure 5 shown.

[0114] S7: Perform performance verification and comparative analysis on the optimized design of the heterogeneous fusion lattice. The material selected is superalloy 4169. A fixed temperature of 700 °C is applied to the bottom of the structure, and an air flow of 1 m / s is set on the left side. Homogeneous D lattice and gradient D lattice with the same relative density are established, and the same boundary conditions are applied. The comparison of the simulation results is as Figure 6 shown. The average temperature and the highest temperature on the upper surface of the designed structure of the present invention are reduced by 38.53% and 49.53% compared with the homogeneous D lattice; compared with the gradient-optimized D structure, they are also reduced by 6.9% and 20.82%. The comprehensive heat insulation performance of the structure is improved.

[0115] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0116] The logic and / or steps represented in the flowchart or described in other ways 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 an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatus, or devices.

[0117] The above embodiments have introduced the present invention in detail. Specific examples are used herein to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion, characterized in that: The following steps are involved: S1. Construct different types of TPMS lattice structure models, perform numerical calculations on their performance under active cooling conditions, number different TPMS configurations, and obtain correlation curves between equivalent thermal conductivity and relative density of different configurations; S2. Establish a mathematical model for topological optimization of thermal insulation structure, and use variable density method to perform topological optimization design according to the boundary conditions of the design domain and initial parameters to obtain the structural density field and node temperature values; S3, bilinearly interpolate the node temperature values ​​to obtain the unit center temperature value, and then divide the unit temperatures one by one by the highest unit temperature in the structure to obtain the normalized temperature field of the structure; S4, performing average pooling processing on the topology optimized structural density field and the structural normalized temperature field to obtain a pooled unit density field and a pooled unit normalized temperature field; S5, according to the performance of different TPMS lattice structures in S1 and the unit normalized temperature field after pooling in S4, a cell selection mechanism based on the unit normalized temperature field after pooling is established; S6. According to the cell selection mechanism, the cell configuration of each unit is selected, and the cell configuration of the unit, the pooled cell density field, and the spatial coordinates are associated with each other through the unit number; S7, using Gaussian radial basis function to perform heterogeneous lattice fusion filling design on the design domain; S8. Perform performance verification and comparative analysis on the optimized design of heterogeneous fusion lattices to complete the multi-scale optimization design of the thermal protection structure.

2. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 1 is characterized by: In step S1, different types of TPMS lattice structure models are constructed, and their performance under active cooling conditions is numerically calculated. Different TPMS configurations are numbered to obtain correlation curves between equivalent thermal conductivity and relative density of different configurations. The specific process includes the following steps: S11. The constructed TPMS lattice structure includes determining the lattice type, unit cell size, relative density, lattice scale, density ρ of the material used in the structure, thermal conductivity k, flow velocity v of the fluid, and the fixed high temperature of the lower surface of the structure. The lattice type includes four types of TPMS lattice configurations, namely Diamond type minimal surface lattice structure, Gyroid spiral type minimal surface lattice structure, Primitive type minimal surface lattice structure and I-Wrapped Package type minimal surface lattice structure; S12. Calculate the equivalent thermal conductivity k of the structure based on the temperature difference between the upper and lower surfaces of the structure and the heat flux density of the heat source surface. eff : where k eff is the equivalent thermal conductivity of the structure; q is the heat flux density of the heat source surface; H is the heat flux transfer thickness; T a is the temperature of the heat source surface; T b is the average surface temperature of the structure; S13. Number each type of cell, where the Diamond structure is numbered D; the Gyroid structure is numbered G; the Primitive structure is numbered P; and the I-Wrapped Package structure is numbered IWP; S14, constructing the implicit function of the TPMS lattice structure to obtain the relative density correlation curve; S15. In computer programming languages, each type of index is established based on the performance differences of different cells, and the index must be unique.

3. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 2 is characterized by: In step S14, the constructed TPMS lattice structure implicit function specifically includes: f solid-D (x,y,z)=sinXsinYsinZ+sinXcosYcosZ+cosXsinYcosZ+cosXcosYsinZ-t f solid-G (x,y,z)=sinXcosY+sinYcosZ+sinZcosX-t f solid-P (x,y,z)=cosX+cosY+cosZ-0.51(cosXcosY+cosYcosZ+cosZcosX)-t f solid-IWP (x,y,z)=cosXcosY+cosXcosZ+cosYcosZ-0.51(cos2X+cos2Y+cos2Z)-t Wherein, X=2πx / L, Y=2πy / L, Z=2πz / L; L is the cell size of TPMS; t is the level set constant that controls the relative density of TPMS; x, y, z are the three axial coordinates in the Cartesian coordinate system.

4. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 1 is characterized by: In step S2, the variable density method is used to perform topology optimization design to obtain the structural density field and node temperature values, specifically including: the topology optimization takes minimizing the average surface temperature of the structure as the optimization goal, while constraining the relative density of the overall structure. The topology optimization model is as follows: Among them, ρ i represents the relative density of the i-th unit; ρ is the relative density of the overall structure; minC is the topology optimization objective function, which minimizes the average surface temperature of the structure; C is the average surface temperature of the structure; e is the surface node set of the target optimized structure; T is the node temperature; F is the thermal load vector of the overall structure; K is the heat transfer matrix of the overall structure; R is the node temperature vector of the overall structure; K i is the heat transfer matrix of the ith unit; R i is the temperature vector of the i-th unit node; is the transpose of the temperature vector of the ith unit node; v i is the volume of the i-th unit, V is the volume constraint of the overall structure; ρ min , ρ max are the upper and lower limits of the cell density.

5. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 1 is characterized by: In step S3, bilinear interpolation is performed on the node temperature values, and the formula is as follows: Among them, T1, T3, T7, and T9 are the temperature values ​​of the four nodes of the unit; T2 and T8 are the midpoint temperatures of the upper and lower sides of the unit; T5 is the center temperature of the unit; x1, y1, x1, y2, x2, y1, x2, y2 are the coordinates of the four nodes of the unit; x and y are the coordinates of the center of the unit.

6. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 1 is characterized by: In step S4, the topology optimized structural density field and structural normalized temperature field are averaged and pooled, specifically including: considering adjacent 2×2 units as a complete unit, adding the internal values ​​and dividing by 4, and obtaining the average value as the unit density field after pooling and the unit normalized temperature field after pooling.

7. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 6 is characterized by: In step S5, according to the performance of different TPMS lattice structures in S1 and the unit normalized temperature field after pooling in S4, a cell selection mechanism based on the unit normalized temperature field after pooling is established. The specific process includes the following steps: S51, judging the unit center temperature, and dividing the overall design domain into a high temperature zone and a low temperature zone through the unit normalized temperature field after pooling; S52, fill the D structure lattice type with lower equivalent thermal conductivity in the high temperature area, and fill the G structure lattice type with better flow characteristics in the low temperature area, and obtain the unit configuration matrix S in the design domain i (T′), as follows: Where S i is the unit type; G is the Gyroid structure number; D is the Diamond structure number; T i ′ is the normalized temperature of the i-th unit after pooling.

8. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 6 is characterized by: In step S6, the cell configuration of the unit, the pooled cell density field, and the spatial coordinates are associated by the unit number, as follows: Where S i is the cell type of the i-th unit; ρ i ′ is the relative density of the i-th unit after pooling; X i is the spatial coordinate of the ith unit.

9. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 1 is characterized by: In step S7, Gaussian radial basis function is used to perform heterogeneous lattice fusion filling design on the design domain, and the formula is as follows: Among them, f fus is a composite lattice expression, f1 and f2 are expressions of two basic lattices, m is the transition interval control parameter, x1, y1, z1 are the coordinates of the center point of lattice 1, x2, y2, z2 are the coordinates of the center point of lattice 2, and x, y, z are the coordinates of the middle position of the two cells.

10. The multi-scale heat protection structure optimization design method based on heterogeneous lattice fusion according to claim 1, characterized in that: In step S8, the heterogeneous fusion lattice is repaired and solidified by STL model, a fluid domain is created, boundary conditions are applied, and CFD simulation analysis is performed.

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