Topological optimization design method and device for wind tunnel balance, storage medium and electronic equipment
By using topology optimization design methods, the problems of relying on engineering experience and long cycles in wind tunnel balance design were solved, and balance optimization under multiple constraints was achieved, improving design level and efficiency.
Patent Information
- Application Number
- CN202511529472.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-24
- Publication Date
- 2026-02-10
AI Technical Summary
Existing wind tunnel balance designs rely on engineering experience, have long design cycles, struggle to balance the conflict between sensitivity and stiffness, are difficult to optimize for multiple objectives, and lack the ability to perform multi-physics coupling analysis.
A topology optimization design method is adopted. By defining the design domain, setting optimization objectives and constraints, establishing a finite element calculation model, and using the moving asymptote algorithm for iterative optimization, the balance optimization under multiple constraints is achieved.
It achieves the minimization of multidimensional force transmission paths, solves the stiffness-sensitivity contradiction and measurement coupling interference problems, improves design level, shortens design cycle and reduces cost.
Smart Images
Figure CN121503117A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of aerodynamic testing, and in particular to a wind tunnel balance topology optimization design method and device, a storage medium and an electronic device. BACKGROUND
[0002] As the core equipment for accurately measuring aerodynamic loads in wind tunnel tests, the performance of a wind tunnel balance directly determines the reliability and accuracy of aerodynamic test data. Current wind tunnel balance design faces many technical challenges: 1. Strong dependence on experience: Existing designs are mainly based on engineering experience and analogy design, and the design quality is heavily dependent on the personal experience and level of the designer; 2. Long design cycle and high cost: A mature balance design / manufacturing cycle usually takes 6-12 months, which cannot meet the requirements of rapid iteration and low-cost research and development; 3. Performance contradiction is prominent: High measurement sensitivity requires the elastomer to have appropriate flexibility, while high strength / low measurement interference requires sufficient stiffness, and traditional design methods are difficult to fundamentally solve this inherent contradiction; 4. Difficulty in multi-objective / constraint optimization: Existing design methods cannot comprehensively consider the balance six-component sensitivity, the requirement of minimizing coupling measurement, and cannot achieve global performance optimization; at the same time, it is difficult to take into account the local stress concentration problem, affecting the fatigue life and long-term measurement stability.
[0003] In recent years, the rapid development of additive manufacturing technology has provided new opportunities for topology optimization and manufacturing feasibility for topology optimization results. Although topology optimization technology has been widely used in structural design, its application to high-precision wind tunnel balance design still has significant technical bottlenecks: commercial general-purpose optimization software lacks special modules for wind tunnel balance special requirements; wind tunnel balance design is a multi-stress constraint optimization problem, and the locality, nonlinearity and singularity of stress constraints make numerical calculation difficult; the multi-physical field coupling analysis capability is insufficient; the design and manufacturing are disconnected, etc.
[0004] Therefore, it is urgent to develop a topology optimization method specifically for wind tunnel balance design, which can systematically solve the above technical problems. SUMMARY
[0005] The purpose of the embodiments of the present application is to provide a wind tunnel balance topology optimization design method, device, storage medium and electronic device to solve the problems in the prior art.
[0006] The embodiments of the present invention adopt the following technical solution: a wind tunnel balance topology optimization design method, comprising: defining and discretizing the design domain of the wind tunnel balance topology in the XOY plane, and setting the attribute parameters of the design domain; setting the optimization objective and constraints of the wind tunnel balance topology; based on the design domain, establishing a finite element calculation model with stress relaxation and density-stiffness material interpolation model, and initializing the density field design variables and optimization parameters of the finite element calculation model; performing optimization iterations of the density field design variables using a moving asymptote algorithm or an improved algorithm of the moving asymptote algorithm, each iteration comprising: performing finite element analysis on the density field design variables, constructing the sensitivity of the optimization objective and the constraints to the density field design variables, updating the density field design variables and performing density filtering and projection correction on the density field design variables, detecting whether the updated density field design variables satisfy the optimization objective and the constraints; if the updated density field design variables do not satisfy the optimization objective and the constraints, performing the next iteration; if the updated density field design variables satisfy the optimization objective and the constraints, completing the iteration and outputting the optimized wind tunnel balance topology.
[0007] This invention also provides a wind tunnel balance topology optimization design device, comprising: a design domain definition module for defining and discretizing the design domain of the wind tunnel balance topology in the XOY plane, and setting attribute parameters of the design domain; a setting module for setting the optimization objective and constraints of the wind tunnel balance topology; a finite element analysis module for establishing a finite element calculation model with stress relaxation and density-stiffness material interpolation model based on the design domain; a sensitivity analysis module for constructing the sensitivity of the optimization objective and constraints to the density field design variables; and an iteration module for iterating based on the modified design using a moving line asymptotic algorithm or a moving line asymptotic algorithm. The algorithm iterates through the optimization of the density field design variables. Each iteration includes: calling the finite element analysis module to perform finite element analysis on the density field design variables; updating the density field design variables according to the sensitivity and performing density filtering and projection correction on the density field design variables; checking whether the updated density field design variables meet the optimization objective and the constraints; if the updated density field design variables do not meet the optimization objective and the constraints, proceeding to the next iteration; if the updated density field design variables meet the optimization objective and the constraints, the iteration is completed and the optimized wind tunnel balance topology is output.
[0008] This invention also provides a storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the above-described steps of wind tunnel balance topology optimization design.
[0009] This invention also provides an electronic device, including at least a memory and a processor, wherein the memory stores a computer program, and the processor, when executing the computer program in the memory, implements the above-described steps of the wind tunnel balance topology optimization design.
[0010] The beneficial effects of the embodiments of the present invention are as follows: (1) The present invention provides a balance optimization design method that can accurately decouple the structural response under different force loads, realize the multi-objective and multi-constraint optimization design of the balance under the minimized coupling measurement of multi-dimensional force transmission path, and fundamentally solve the stiffness-sensitivity contradiction and measurement coupling interference problem in balance design; (2) The embodiments of the present invention carry out optimization design from the perspective of physics and data, breaking through the bottleneck problem that the quality of existing designs based on engineering experience and analogy is heavily dependent on the personal experience and level of designers, and the design level of balance is greatly improved; (3) The embodiments of the present invention can shorten the design iteration cycle of the balance, save design costs, and significantly improve the design success rate. Attached Figure Description
[0011] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0012] Figure 1 This is a flowchart of the wind tunnel balance topology optimization design method in the first embodiment of the present invention; Figure 2 This is a schematic diagram of the design domain, boundary conditions, and the location of the strain gauges on the elastic beam in the first embodiment of the present invention; Figure 3 This is a schematic diagram of a single iteration process in the first embodiment of the present invention; Figure 4 This is an example diagram of the final topology in the first embodiment of the present invention; Figure 5 This is a Von Mises stress and directional stress distribution cloud diagram of the final topology in the first embodiment of the present invention; Figure 6 This is a convergence history curve of the objective and constraint functions during the optimization process in the first embodiment of the present invention; Figure 7 This is a schematic diagram of the wind tunnel balance topology optimization design device in the second embodiment of the present invention. Detailed Implementation
[0013] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.
[0014] To address the problems existing in the prior art, the first embodiment of the present invention provides a wind tunnel balance topology optimization design method, the flowchart of which is shown below. Figure 1 As shown, it mainly includes: S10 defines and discretizes the design domain of the wind tunnel balance topology in the XOY plane, and sets the attribute parameters of the design domain.
[0015] Figure 2 This diagram illustrates the design domain, boundary conditions, and strain gauge locations of the elastic beam in this embodiment. In this embodiment, the central axis of the wind tunnel balance topology is used as a reference. A two-dimensional plane, denoted as XOY, is constructed along this central axis, passing through it and parallel to the generatrix of the wind tunnel balance topology. X represents the horizontal direction parallel to the ground, and Y represents the direction perpendicular to X within the cutting plane. After defining the two-dimensional design domain, it is discretized into... In this embodiment, the rectangular grid cells are... , =120, grid size is 0.25mm.
[0016] Further as Figure 2 As shown, the positions of the upper and lower elastic beams are specified with the central axis as the boundary, and strain gauge positions are set on the elastic beams to realize stress acquisition of the elastic beams during simulation. In this embodiment, the strain gauges are installed on the left and right sides of the elastic beam, but... Figure 2 The strain gauge positions shown are for illustrative purposes only and do not represent the actual strain gauge settings. Subsequently, property parameters such as elastic beam material properties, load conditions, and boundary conditions can be defined. Material settings can be based on the actual material selection from the wind tunnel balance, either by calling preset properties from the material library or configuring properties through custom materials. Then, combined with actual working conditions, one side of the two-dimensional design domain's element nodes is fixed, while the center node of the other side's elements is subjected to load. This embodiment uses the leftmost element node of the two-dimensional design domain being fixed, and the center node of the rightmost element being subjected to load as an example. In this embodiment, =20N, =300N, =18 N·m, which is a large load ratio balance design problem.
[0017] S20 sets the optimization objective and constraints for the wind tunnel balance topology.
[0018] Based on the actual functional requirements of the wind tunnel balance, this embodiment takes the overall structural compliance as the optimization objective and sets the following constraints: the global equivalent stress based on P-norm aggregation is used as the first constraint to ensure structural safety; the average stress in the Y direction of the elastic beam under specific loads is used as the second constraint to ensure measurement sensitivity; and the average stress in the Y direction of the elastic beam under other loads is used as the third constraint to ensure minimizing measurement interference. The above optimization objectives and constraints can be described based on the following set of formulas (1) to solve the topology optimization problem of the wind tunnel balance: (1) Specifically, formula (1.1) is used to calculate the overall structural compliance, aiming to minimize the overall structural compliance, thereby maximizing the overall structural stiffness of the balance to reduce measurement interference and improve measurement accuracy. Among these, For the overall structural flexibility, This is the global displacement matrix. This is the global stiffness matrix.
[0019] Formula (1.2) represents the physical constraints that are naturally satisfied. To load the load matrix.
[0020] To avoid the computational difficulties caused by numerous local constraints, the first constraint uses the P-norm to aggregate the global stress field into a continuously differentiable scalar function for constraint. The global equivalent stress based on the P-norm aggregation is calculated using formula (1.3). It is required that its stress not exceed the required safety stress. To ensure the safety of the structure during use. Among them, For the number of units, For the first Von-Mises stress after relaxation of each element This is the P-norm parameter. In this embodiment, =900MPa.
[0021] The average stress in the Y direction of the elastic beam under a specific load is calculated using formula (1.4). It is required that its stress is not less than the stress in a given direction. Ensure sufficient measurement sensitivity output. For a specific load, The average stress in the Y direction of the strain gauge on the left side of the upper elastic beam. The average stress in the Y direction of the strain gauge on the right side of the upper elastic beam is given. The average stress in the Y direction of the strain gauge on the left side of the lower elastic beam is given. The stress in the Y direction of the strain gauge on the right side of the lower elastic beam is taken as the average stress. In this embodiment, it is taken as... This is the axial force; =20MPa.
[0022] The average stress in the Y direction of the elastic beam under other loads is calculated using formula (1.5). It is required that its stress is not greater than the stress in a given direction. of This ensures that stress output under other loads can be suppressed, minimizing measurement interference. Among these, Other loads besides the specific load; in this embodiment, specifically, the normal force. and pitch moment ; These are the interference suppression parameters.
[0023] In some embodiments, the P-norm parameter The value range is 8~10, which is the interference suppression parameter. The value ranges from 0.02 to 0.05. In this embodiment, preferably, .
[0024] S30, based on the design domain, establishes a finite element calculation model with stress relaxation and density-stiffness material interpolation model, and initializes the density field design variables and optimization parameters of the finite element calculation model.
[0025] The density-stiffness material interpolation model (SIMP, Solid Isotropic Material with Penalization) correlates material stiffness and density through an exponential function and introduces a penalty factor to binarize intermediate density values towards [0,1], thereby improving optimization efficiency. Specifically, this embodiment uses the following formula to calculate element stiffness. Calculation:
[0026] in, For the first Density of each unit It is a very small positive number to prevent the stiffness matrix from becoming singular. For stiffness penalty parameters, The elastic modulus of the solid material is given. Simultaneously, formula (3) is used to calculate the stress in the relaxed element direction. To address the problem of spurious stress caused by low-density elements, the element directional stress... The calculation formula is:
[0027] in, For stress relaxation parameters, This represents the stress in the unrelaxed element direction. In this embodiment, the stiffness penalty parameter... The value range is 3~4, which is the stress relaxation parameter. The value range is 0.4 to 0.6. Preferably, in this embodiment... .
[0028] It should be noted that the unit mentioned in the finite element calculation model construction and iteration process in this embodiment is the rectangular mesh unit formed after discretization. The density field design variable is the density value corresponding to each rectangular mesh unit. The density value is optimized by iterative optimization of the calculation model to characterize the optimization of the wind tunnel balance topology.
[0029] S40 employs the moving asymptote algorithm or an improved version of the moving asymptote algorithm to iteratively optimize the density field design variables.
[0030] The Moving Asymptote Algorithm (MMA) is a nonlinear programming algorithm primarily used for topology and structural optimization. It approximates the original problem by constructing a series of convex subproblems, exhibiting strong accuracy and robustness in complex problems with multiple constraints, and stabilizing and accelerating the convergence of the optimization process. This embodiment employs the MMA algorithm or any improved version thereof as the optimization algorithm for iterative topology optimization of a balance scale, improving optimization speed while ensuring iterative effectiveness.
[0031] In this embodiment, each iteration process can be performed as follows: Figure 3 The process is as follows: S41, perform finite element analysis on density field design variables.
[0032] The finite element calculation model is called as a module in each iteration to calculate the stress / strain information of the entire density field (i.e., the balance structure), so as to solve the target-constraint and the sensitivity of the target-constraint.
[0033] S42, Construct the sensitivity of the optimization objective and the bound conditions to the density field design variables.
[0034] Based on the finite element analysis results, the adjoint method is used to construct explicit programmable sensitivity functions of the optimization objective function and the constraint function with respect to the density field design variables, namely: programmable sensitivity functions of the optimization objective function with respect to the density field design variables. The programmable sensitivity function of the first constraint function to the density field design variables. The programmable sensitivity function of the second constraint function to the density field design variables. Programmable sensitivity function of the third constraint function to density field design variables .
[0035] S43, update the density field design variables and perform density filtering on the density field design variables.
[0036] The density field design variables are updated using the MMA algorithm combined with a programmable sensitivity function, yielding the updated density field design variables. Subsequently, a convolutional filtering method is applied to the updated density field design variables to avoid pseudo-optimal solutions or numerical instability caused by the checkerboard phenomenon. Specifically, this is implemented based on the following formula:
[0037] in, Design variables for the density field after density filtering. For distance from the first Unit Cell index within the range, The filter radius is... This is a set of indices within the filtering radius. The filter weight matrix is calculated based on the following formula:
[0038] in, For unit and The center distance.
[0039] S44, Projection correction is applied to the density field design variables.
[0040] The design variable density is corrected by using Heaviside projection to make it more similar to [0,1] binarization, thus obtaining clear boundaries. This can be achieved based on the following formula:
[0041] in, Design variables for the projected density field. For projection slope parameters, This is the projection threshold. In this embodiment, the filter radius... The value range is 2.5 to 7 units, and the projection threshold is... The value range is 0.4 to 0.6. In this embodiment, preferably, =3.5, =0.5, projection slope parameter The method for determining the value is to gradually double the initial value of 2 by a preset number of iteration steps, for example, the preset number can be 150.
[0042] S45, check whether the corrected density field design variables meet the optimization objective and constraints. If the updated density field design variables do not meet the optimization objective and constraints, repeat step S41 for the next iteration. If the updated density field design variables meet the optimization objective and constraints, execute step S46. S46, the iteration is completed and the optimized wind tunnel balance topology is output.
[0043] Specifically, for the updated and corrected density field design variables, finite element analysis is performed again to determine whether the stress and strain information of the updated balance structure meets the optimization objectives and constraints. If the preset objectives and constraints are met, there is no need to iterate again, and the current density field design variables are output as the optimized wind tunnel balance topology. If not, step S41 is executed again for the next iteration until the objectives and constraints are met.
[0044] Figures 4 to 6 This paper illustrates an example of the final topology obtained using the optimization method of this embodiment, along with Von Mises stress and directional stress distribution cloud maps, and convergence history curves of the objective and constraint functions during the optimization process. As shown in the accompanying drawings, the method of this embodiment yields a multi-hinge structure capable of decoupling longitudinal and axial load measurements, achieving optimal force transmission path design. The stress distribution diagram shows that the sensitivity output and anti-interference capability of the elastic beam meet the design requirements. Figure 5 and Figure 6 The method in this embodiment achieves the compliance minimization objective and the requirements of the first, second, and third constraints.
[0045] This invention provides a balance optimization design method that can accurately decouple the structural response under different force loads. It achieves multi-objective and multi-constraint optimization design of the balance under coupled measurement with minimizing multi-dimensional force transmission paths, fundamentally solving the stiffness-sensitivity contradiction and measurement coupling interference problem in balance design. At the same time, it carries out optimization design from a physical and data-driven perspective, breaking through the bottleneck problem that the quality of existing designs based on engineering experience and analogy is heavily dependent on the personal experience and level of the designer, greatly improving the balance design level. Furthermore, it can shorten the balance design iteration cycle, save design costs, and significantly improve the design success rate.
[0046] Based on the same inventive concept, the second embodiment of the present invention provides a wind tunnel balance topology optimization design device, the structural schematic diagram of which is shown below. Figure 7 As shown, it mainly includes: design domain definition module 10, setting module 20, finite element analysis module 30, sensitivity analysis module 40, and iteration module 50.
[0047] Specifically, the design domain definition module 10 is used to define and discretize the two-dimensional design domain of the wind tunnel balance topology in the XOY plane, and set the attribute parameters of the two-dimensional design domain; the setting module 20 is used to set the optimization objectives and constraints of the wind tunnel balance topology; the finite element analysis module 30 is used to establish a finite element calculation model with stress relaxation and density-stiffness material interpolation model based on the two-dimensional design domain; the sensitivity analysis module 40 is used to construct the sensitivity of the optimization objectives and constraints to the density field design variables; the iteration module 50 is used to perform optimization iteration of the density field design variables based on the moving line asymptotic algorithm or an improved algorithm of the moving line asymptotic algorithm. Each iteration includes: calling the finite element analysis module to perform finite element analysis on the density field design variables, updating the density field design variables according to the sensitivity and performing density filtering and projection correction on the density field design variables, and checking whether the updated density field design variables meet the optimization objectives and constraints; if the updated density field design variables do not meet the optimization objectives and constraints, proceed to the next iteration; if the updated density field design variables meet the optimization objectives and constraints, the iteration is completed and the optimized wind tunnel balance topology is output.
[0048] In some embodiments, the design domain definition module 10 is specifically used to: discretize the two-dimensional design domain into The rectangular mesh elements are used; the positions of the upper elastic beam, lower elastic beam, and strain gauge in the two-dimensional design domain are set, and the element nodes on one side of the two-dimensional design domain are fixed, while the load is applied to the center node of the element on the other side.
[0049] In some embodiments, the setting module 20 is specifically used to: set the optimization target as the overall compliance of the wind tunnel balance topology. Minimum; constraints include: First constraint: global equivalent stress based on P-norm aggregation Less than or equal to the required safety stress Second constraint: Average stress in the Y direction of an elastic beam under a specific load. Stress greater than or equal to that in the given direction Third constraint: Average stress in the Y direction of the elastic beam under other loads. Less than or equal to stress in a given direction k times.
[0050] In some embodiments, the setting module 20 is specifically used to: calculate the element stiffness after interpolation using a density-stiffness material interpolation model. To drive the binarization of density field design variables, element stiffness The calculation formula is:
[0051] Calculate the stress in the relaxed element direction To address the issue of spurious stress caused by low-density elements, and the stress in the element direction. The calculation formula is:
[0052] in, For the first i Density of each unit It is a very small positive number to prevent the stiffness matrix from becoming singular. For stiffness penalty parameters, The elastic modulus of solid materials, For stress relaxation parameters, The stress in the unrelaxed element direction.
[0053] Specifically, the P-norm parameter The value range is 8~10, the interference suppression parameter k ranges from 0.02~0.05, and the stiffness penalty parameter... The value range is 3~4, which is the stress relaxation parameter. The value range is 0.4 to 0.6.
[0054] In some embodiments, the sensitivity analysis module 40 is specifically used to: construct an explicit programmable sensitivity function of the optimization objective function and the constraint function on the density field design variables using the adjoint method; the iteration module 50 is specifically used to: use the moving asymptote algorithm or its improved algorithm as the optimizer, calculate the updated density field design variable values based on the current density field design variable values and the explicit programmable sensitivity function; and perform density filtering on the density field design variables based on the following formula:
[0055] in, Design variables for the density field after density filtering. For distance from the first Unit Cell index within the range, The filter radius is... This is a set of indices within the filtering radius. The filter weight matrix is calculated based on the following formula:
[0056] in, For unit and The center distance.
[0057] The density field design variables are projected and corrected based on the following formula:
[0058] in, Design variables for the projected density field. For projection slope parameters, This is the projection threshold.
[0059] Specifically, the filter radius The value ranges from 2.5 to 7 units, and the projection threshold is... The value range is 0.4~0.6, projection slope parameter The method for determining the value is to gradually double the initial value of 2 by a preset number of iteration steps.
[0060] This invention provides a balance optimization design device that can accurately decouple the structural response under different force loads, realizing multi-objective and multi-constraint optimization design of the balance under multi-dimensional force transmission path minimization coupled measurement. This fundamentally solves the stiffness-sensitivity contradiction and measurement coupling interference problem in balance design. At the same time, it carries out optimization design from a physical and data-driven perspective, breaking through the bottleneck problem that the quality of existing designs based on engineering experience and analogy is heavily dependent on the personal experience and level of designers, thus significantly improving the balance design level. Furthermore, it can shorten the balance design iteration cycle, save design costs, and significantly improve the design success rate.
[0061] Based on the same inventive concept, the third embodiment of the present invention provides a storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the wind tunnel balance topology optimization design provided in the first embodiment of the present invention.
[0062] Based on the same inventive concept, the fourth embodiment of the present invention provides an electronic device, including at least a memory and a processor, wherein the memory stores a computer program, characterized in that the processor, when executing the computer program in the memory, implements the steps of the wind tunnel balance topology optimization design provided in the first embodiment of the present invention.
[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for topology optimization design of a wind tunnel balance, characterized in that, include: Define and discretize the design domain of the wind tunnel balance topology in the XOY plane, and set the attribute parameters of the design domain; Define the optimization objective and constraints for the wind tunnel balance topology; Based on the design domain, a finite element calculation model with stress relaxation and density-stiffness material interpolation model is established, and the density field design variables and optimization parameters of the finite element calculation model are initialized. The density field design variables are optimized iteratively using the moving asymptote algorithm or an improved version of the moving asymptote algorithm. Each iteration includes: performing finite element analysis on the density field design variables, constructing the sensitivity of the optimization objective and the constraints to the density field design variables, updating the density field design variables and performing density filtering and projection correction on the density field design variables, and detecting whether the updated density field design variables satisfy the optimization objective and the constraints. If the updated density field design variables do not meet the optimization objective and the constraints, proceed to the next iteration; if the updated density field design variables meet the optimization objective and the constraints, the iteration is completed and the optimized wind tunnel balance topology is output.
2. The wind tunnel balance topology optimization design method according to claim 1, characterized in that, The design domain of the wind tunnel balance topology in the XOY plane is defined and discretized, and the attribute parameters of the design domain are set, including: Discretize the design domain as follows: Rectangular grid cells; Set the positions of the upper elastic beam, lower elastic beam, and strain gauge in the design domain, and set one side of the unit node in the design domain to be fixed, while the center node of the other side of the unit is subjected to load.
3. The wind tunnel balance topology optimization design method according to claim 2, characterized in that, The optimization objective and constraints for setting the wind tunnel balance topology include: The optimization objective is set as the overall compliance of the wind tunnel balance topology. Minimum; The constraints are defined as follows: First constraint: Global equivalent stress based on P-norm aggregation Less than or equal to the required safety stress ; Second constraint: Average stress in the Y direction of an elastic beam under specific loads Stress greater than or equal to that in the given direction ; Third constraint: Average stress in the Y direction of the elastic beam under other loads Less than or equal to stress in a given direction k times.
4. The wind tunnel balance topology optimization design method according to claim 3, characterized in that, The establishment of the finite element calculation model with stress relaxation and density-stiffness material interpolation model includes: Calculate the element stiffness after interpolation using the density-stiffness material interpolation model. To drive the binarization of density field design variables, the element stiffness The calculation formula is: Calculate the stress in the element direction after relaxation To address the problem of spurious stress caused by low-density elements, specifically the element directional stress. The calculation formula is: in, For the first i Density of each unit It is a very small positive number to prevent the stiffness matrix from becoming singular. For stiffness penalty parameters, The elastic modulus of solid materials, For stress relaxation parameters, The stress in the unrelaxed element direction.
5. The wind tunnel balance topology optimization design method according to claim 4, characterized in that, The P-norm parameter The value range is 8~10, the interference suppression parameter k ranges from 0.02~0.05, and the stiffness penalty parameter... The value range is 3~4, which is the stress relaxation parameter. The value range is 0.4 to 0.
6.
6. The wind tunnel balance topology optimization design method according to claim 4, characterized in that, The process of constructing the sensitivity of the optimization objective and constraints to the density field design variables, updating the density field design variables, and performing density filtering and projection correction on the density field design variables includes: An explicit programmable sensitivity function for the density field design variables is constructed using the adjoint method, which is a function of the optimization objective and a function of the constraints. The moving asymptote algorithm or its improved version is used as the optimizer to calculate the updated density field design variable values based on the current density field design variable values and the explicit programmable sensitivity function. Density filtering is performed on the updated density field design variables based on the following formula: in, Design variables for the density field after density filtering. For distance from the first Unit Cell index within the range, The filter radius is... This is a set of indices within the filtering radius. The filter weight matrix is calculated based on the following formula: in, For unit and The center distance; The density field design variables are projected and corrected based on the following formula: in, Design variables for the projected density field. For projection slope parameters, This is the projection threshold.
7. The wind tunnel balance topology optimization design method according to claim 6, characterized in that, The filter radius The value ranges from 2.5 to 7 units, and the projection threshold is... The value range is 0.4~0.6, projection slope parameter The method for determining the value is to gradually double the initial value of 2 by a preset number of iteration steps.
8. A wind tunnel balance topology optimization design device, characterized in that, include: The design domain definition module is used to define and discretize the design domain of the wind tunnel balance topology in the XOY plane, and set the attribute parameters of the design domain. The setting module is used to set the optimization objectives and constraints of the wind tunnel balance topology; The finite element analysis module is used to establish a finite element calculation model with stress relaxation and density-stiffness material interpolation model based on the design domain; A sensitivity analysis module is used to construct the sensitivity of the optimization objective and the constraints to the density field design variables; The iteration module is used to perform optimization iterations of the density field design variables based on a moving line asymptotic algorithm or an improved algorithm of the moving line asymptotic algorithm. Each iteration includes: calling the finite element analysis module to perform finite element analysis on the density field design variables; updating the density field design variables according to the sensitivity and performing density filtering and projection correction on the density field design variables; detecting whether the updated density field design variables meet the optimization objective and the constraints; if the updated density field design variables do not meet the optimization objective and the constraints, proceeding to the next iteration; if the updated density field design variables meet the optimization objective and the constraints, the iteration is completed and the optimized wind tunnel balance topology is output.
9. A storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the wind tunnel balance topology optimization design as described in any one of claims 1 to 7.
10. An electronic device, comprising at least a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program on the memory, it implements the steps of the wind tunnel balance topology optimization design as described in any one of claims 1 to 7.