Direct topology and shape optimization method for existing engineering structure model

Abstract

The application discloses a direct topology and shape optimization method for an existing engineering structure model, relates to the technical field of topology optimization and shape optimization, and comprises the following steps: mapping a finite element simulation model of an original engineering structure based on a regular hexahedron element to determine an approximate optimization simulation model; determining a typical design mode of multi-component non-interference optimization by transforming a design domain state and range based on the approximate optimization simulation model; determining a compatible unified optimization framework by converting the sensitivity of independent or combined application under different sensitivity algorithms based on the typical design mode; and determining a variable grouping strategy based on the compatible unified optimization framework to uniformly apply various manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability. The application realizes a typical design mode by reconstructing an original optimization simulation model, realizes free combination of different optimization algorithms by constructing a unified discrete adjoint equation, and improves optimization efficiency and engineering practicability of multi-component design.

Description

Technical Field

[0001] This application relates to the fields of structural topology optimization and shape optimization, and in particular to direct topology and shape optimization methods for existing engineering structural models. Background Technology

[0002] In modern engineering design, topology optimization is mainly used for structural design from scratch, requiring the initial model to have a sufficiently large design space. Therefore, when dealing with existing engineering structures, it is necessary to rebuild the model through CAD / CAE to expand the design space. The modeling process is often quite cumbersome. Although free-form optimization methods can directly optimize existing engineering structures, existing free-form optimization methods are prone to causing mesh distortion under large deformation conditions.

[0003] Currently, the existing approach is to use a single optimization method for structural design. However, single optimization methods such as BESO and SIMP have shortcomings. In practical engineering applications, facing complex and ever-changing engineering design scenarios, the capabilities of a single optimization method are limited. Moreover, existing structural optimization tools require engineers to have extensive experience and innovative thinking to establish optimization requirements, and they cannot consider interference situations when optimizing multiple components. They have poor engineering friendliness, high usage thresholds, and lack typical design patterns that comprehensively consider existing engineering structures. Furthermore, it is difficult to uniformly implement different manufacturing processes using a single method, resulting in significant development difficulties. Therefore, how to more efficiently perform direct topology and shape optimization for existing engineering structural models has become an urgent problem to be solved.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this application is to provide a direct topology and shape optimization method for existing engineering structure models, aiming to solve the technical problem of how to perform direct topology and shape optimization for existing engineering structure models more efficiently.

[0006] To achieve the above objectives, this application proposes a direct topology and shape optimization method for existing engineering structural models, the method comprising:

[0007] Based on the finite element simulation model of the original engineering structure, regular hexahedral elements are mapped to determine the approximate optimized simulation model.

[0008] Based on the approximate optimization simulation model, by transforming the state and range of the design domain, a typical design pattern for multi-component non-interference optimization is determined;

[0009] determine a compatible unified optimization framework based on the typical design mode by converting sensitivities of independent or combined applications under different sensitivity algorithms by using the same discrete adjoint equation;

[0010] determine a variable grouping strategy based on the compatible unified optimization framework to uniformly impose multiple manufacturing process constraints, and obtain a structure improvement scheme with strong manufacturability.

[0011] In an embodiment, the finite element simulation model based on the original engineering structure is mapped by using regular hexahedral elements, and the step of determining the approximate optimization simulation model comprises:

[0012] obtaining mesh requirement information and boundary adjustment conditions;

[0013] adjusting the background mesh resolution by setting a size scaling coefficient according to the mesh requirement information based on the average size of the mesh in the finite element simulation model based on the original engineering structure, and generating hexahedral element mesh information;

[0014] mapping the irregular elements of the corresponding component to be processed to the corresponding regular hexahedral elements for reconstruction based on the hexahedral element mesh information, and adjusting the boundary adjustment conditions to the regular hexahedral nodes by using the nearest node method to obtain the approximate optimization simulation model.

[0015] In an embodiment, the step of determining the typical design mode of multi-component non-interference optimization by transforming the design domain state and range based on the approximate optimization simulation model comprises:

[0016] identifying an initial design domain based on the approximate optimization simulation model;

[0017] transforming and adjusting the initial design domain to obtain the typical design mode of multi-component non-interference optimization, wherein the typical design mode comprises subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization, and topology-first shape-second design.

[0018] In an embodiment, the step of determining the compatible unified optimization framework based on the typical design mode by converting sensitivities of independent or combined applications under different sensitivity algorithms by using the same discrete adjoint equation further comprises:

[0019] simplifying the piecewise constant function by using the same discrete adjoint equation for the velocity interpolation function based on the typical design mode to obtain the compatible unified optimization framework, wherein the compatible unified optimization framework is used to adapt the sensitivity characteristics of different optimization algorithms to realize independent or combined application of BESO, SIMP, and VFLSM in the optimization process.

[0020] In an embodiment, after the step of simplifying the piecewise constant function of the velocity interpolation function based on the typical design pattern using the same discrete adjoint equation to obtain a structure improvement scheme with strong manufacturability based on the compatible unified optimization framework, the method further comprises:

[0021] The acquisition unit acquires unit-level design response parameter information, which includes volume fraction, compliance, stress, frequency, heat dissipation weakness, displacement, etc.

[0022] The mapping relationship between the design variables and the physical properties of the unit corresponding to the unit-level design response parameter information is analyzed using the discrete adjoint method, and an analysis result is determined.

[0023] The same discrete sensitivity is converted into different optimization algorithm sensitivities using the analysis result.

[0024] In an embodiment, the step of determining a variable grouping strategy based on the compatible unified optimization framework to uniformly apply multiple manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability comprises:

[0025] The approximate optimization simulation model identifies the initial design domain as a main domain and a sub-domain, and maps the design variable control points of the main domain to the corresponding sub-domain to form variable grouping information decoupled from the finite element mesh;

[0026] The corresponding typical design pattern is constrained based on the variable grouping information to obtain a structure improvement scheme with strong manufacturability, which includes plane symmetry, cyclic symmetry, extrusion, pattern repetition, and casting constraints.

[0027] In an embodiment, the step of constraining the corresponding typical design pattern based on the variable grouping information to obtain a structure improvement scheme with strong manufacturability comprises:

[0028] When the variable grouping information is that the variables in the constraint group have equal values, the manufacturing process constraint scheme is plane symmetry, rotational symmetry, extrusion, or periodic repetition structure.

[0029] When the variable grouping information is that the variables in the constraint group have an increasing or decreasing trend, the constraint structure scheme is a structure that simulates the casting draw direction or the layer thickness change process restriction structure of additive manufacturing.

[0030] In addition, to achieve the above-mentioned purpose, the application further provides a direct topology and shape optimization device for an existing engineering structure model, which comprises:

[0031] An acquisition module maps a regular hexahedral element based on a finite element simulation model of an original engineering structure to determine an approximate optimization simulation model.

[0032] a processing module configured to determine a typical design mode of multi-component non-interference optimization by transforming a design domain state and range based on the approximate optimization simulation model;

[0033] the processing module is further configured to determine a compatible unified optimization framework by converting sensitivities applied independently or in combination under different sensitivity algorithms using the same discrete adjoint equation based on the typical design mode;

[0034] an execution module configured to determine a variable grouping strategy to uniformly apply multiple manufacturing process constraints based on the compatible unified optimization framework to obtain a structure improvement scheme with strong manufacturability.

[0035] In addition, to achieve the above object, the present application further provides a device for direct topology and shape optimization for an existing engineering structure model, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the method for direct topology and shape optimization for an existing engineering structure model.

[0036] In addition, to achieve the above object, the present application further provides a storage medium, which is a computer readable storage medium, and a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the steps of the method for direct topology and shape optimization for an existing engineering structure model.

[0037] The one or more technical solutions provided by the present application have at least the following technical effects:

[0038] The method for direct topology and shape optimization for an existing engineering structure model provided by the present embodiment is based on a finite element simulation model of an original engineering structure to map regular hexahedral elements and determine an approximate optimization simulation model; a typical design mode of multi-component non-interference optimization is determined by transforming a design domain state and range based on the approximate optimization simulation model; a compatible unified optimization framework is determined by converting sensitivities applied independently or in combination under different sensitivity algorithms using the same discrete adjoint equation based on the typical design mode; and a structure improvement scheme with strong manufacturability is obtained by determining a variable grouping strategy to uniformly apply multiple manufacturing process constraints based on the compatible unified optimization framework. The present application reconstructs the model by regular hexahedral elements to generate an approximate optimization simulation model, automatically identifies and determines a typical design mode, adjusts a target design domain boundary, and constructs a unified optimization framework compatible with multiple optimization methods, so as to convert sensitivities under different sensitivity algorithms in the framework, realize adjustment of sensitivities applied independently or in combination, generate a structure improvement scheme meeting actual manufacturing process requirements, significantly improve optimization efficiency, reduce operation complexity, and improve engineering friendliness and manufacturability of optimization design. BRIEF DESCRIPTION OF DRAWINGS

[0039] The accompanying drawings, which are incorporated herein and constitute part of the specification, illustrate embodiments consistent with the application and, together with the description, serve to explain the principles of the application.

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the accompanying drawings required by the embodiments or the prior art description will be briefly introduced as follows. Obviously, for those skilled in the field, under the premise of no creative labor, other drawings can also be obtained according to these drawings.

[0041] Figure 1 A flowchart schematic diagram provided for the embodiment of the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0042] Figure 2 A schematic diagram of the approximate optimization simulation model reconstruction for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0043] Figure 3 A schematic diagram of the initial design domain adjustment for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0044] Figure 4 A schematic diagram of the constraint typical design mode for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0045] Figure 5 A schematic diagram of the lightweight design mode for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0046] Figure 6 A schematic diagram of the local reconstruction design mode for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0047] Figure 7 A schematic diagram of the global reconstruction design mode of the endogenous domain for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0048] Figure 8 A schematic diagram of the global reconstruction design mode of the exogenous domain for the direct topology and shape optimization method of the existing engineering structure model of the present application;

[0049] Figure 9 A schematic diagram of the additive reinforcement design mode for the direct topology and shape optimization method of the existing engineering structure model of the present application, defining the entire original model as a non-design domain;

[0050] Figure 10A local search design mode schematic diagram for the direct topology and shape optimization method for the existing engineering structure model of the application;

[0051] Figure 11 A pure shape optimization design mode schematic diagram for the direct topology and shape optimization method for the existing engineering structure model of the application;

[0052] Figure 12 A two-stage collaborative optimization design mode schematic diagram for the direct topology and shape optimization method for the existing engineering structure model of the application;

[0053] Figure 13 A flow schematic diagram provided by the second embodiment of the direct topology and shape optimization method for the existing engineering structure model of the application;

[0054] Figure 14 A brief flow schematic diagram of the direct topology and shape optimization method for the existing engineering structure model of the application provided by the embodiment of the application;

[0055] Figure 15 A module structure schematic diagram of the direct topology and shape optimization device for the existing engineering structure model of the embodiment of the application;

[0056] Figure 16 A device structure schematic diagram of the hardware running environment involved in the direct topology and shape optimization method for the existing engineering structure model in the embodiment of the application.

[0057] The object implementation, functional features and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0058] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the application, and are not used to limit the application.

[0059] In order to better understand the technical solutions of the application, the following will be described in detail with reference to the drawings and specific embodiments of the specification.

[0060] The main solution of the embodiment of the application is: mapping the finite element simulation model based on the original engineering structure with regular hexahedral elements, determining the approximate optimization simulation model; determining the typical design mode of multi-component non-interference optimization by transforming the design domain state and range based on the approximate optimization simulation model; determining the compatible unified optimization framework by using the same discrete adjoint equation to convert the sensitivity applied independently or in combination under different sensitivity algorithms; determining the variable grouping strategy based on the compatible unified optimization framework to uniformly apply various manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability.

[0061] In the embodiment, for convenience of description, the following describes an execution subject of a direct topology and shape optimization device for an existing engineering structure model.

[0062] In the prior art, in actual engineering applications, in the face of existing complex and variable engineering design scenarios, due to the incompatibility of sensitivity, the limited ability of a single optimization method, the need for engineers to have rich experience and innovative thinking to establish optimization requirements, poor engineering friendliness, high use threshold, lack of a multi-directional consideration of the existing engineering structure, and a targeted design mode, and different manufacturing processes are difficult to be uniformly implemented by a single method, and the development difficulty is great.

[0063] The application provides a solution, which maps a finite element simulation model of an original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model; determines a typical design mode of multi-component non-interference optimization by transforming a design domain state and range based on the approximate optimization simulation model; determines a compatible unified optimization framework by converting the sensitivity under different sensitivity algorithms independently or in combination based on the typical design mode; and determines a variable grouping strategy to uniformly apply various manufacturing process constraints based on the compatible unified optimization framework to obtain a structure improvement scheme with strong manufacturability.

[0064] From the above embodiment, it can be seen that the application reconstructs the model with regular hexahedral elements to generate an approximate optimization simulation model, automatically identifies and determines a typical design mode, adjusts the boundary of the target design domain, and constructs a unified optimization framework compatible with various optimization methods, so as to convert the sensitivity under different sensitivity algorithms in the framework, realize the sensitivity adjustment of independent or combined application, and generate a structure improvement scheme meeting the requirements of actual manufacturing processes, thereby significantly improving the optimization efficiency, reducing the operation complexity, and improving the engineering friendliness and manufacturability of the optimization design.

[0065] Based on this, the embodiment of the application provides a direct topology and shape optimization method for an existing engineering structure model, which refers to Figure 1 , Figure 1 The flowchart of the first embodiment of the direct topology and shape optimization method for an existing engineering structure model of the application is shown in the figure.

[0066] In the embodiment, the direct topology and shape optimization method for an existing engineering structure model includes steps S10-S50:

[0067] Step S10, mapping a finite element simulation model of an original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model;

[0068] It should be noted that the approximate optimization simulation model is based on the finite element simulation model of the original engineering structure and is obtained by reconstructing it using regular hexahedral elements, thus possessing an expandable design domain boundary.

[0069] It is understood that the approximate optimization simulation model is obtained by replacing the irregular elements of the component to be processed in the finite element simulation model of the original engineering structure with regular hexahedral elements. The loads, boundary constraints and connection elements on the non-optimized region remain unchanged, and the loads, constraints and connection relationships acting on the optimized region are transferred to the corresponding regular hexahedral elements according to the principle of proximity mapping. The design domain boundary of the obtained approximate optimization simulation model has the ability to be expanded or transformed, and can be flexibly adjusted according to optimization needs, providing greater design space and flexibility.

[0070] Additionally, it should be noted that the finite element simulation model of the original engineering structure is a numerical model constructed based on the actual engineering structure. It is used to simulate the mechanical behavior of the structure under various loads and boundary conditions. It contains multiple finite element meshes, which divide the structure into many small units. Each unit has its own physical properties, such as material properties and geometric shape. The regular hexahedral unit is a special type of finite element mesh unit. Its geometric shape is a cuboid or cube. Compared with irregular units, such as tetrahedrons, hexahedrons, and triangular prisms, all sides of the regular hexahedral unit are equal or proportional, and all angles are right angles. The stiffness matrix of the unit is simple and consistent, which makes the calculation efficiency higher, the memory usage less, and also facilitates optimization design.

[0071] In a specific embodiment, such as Figure 2 As shown, Figure 2 This diagram illustrates the reconstruction of an approximate optimization simulation model based on the direct topology and shape optimization method for existing engineering structural models. According to the average size of the mesh in the original CAE model, and considering computational efficiency and accuracy requirements, a scaling factor is set to adjust the resolution of the background mesh, thereby generating a regular hexahedral element mesh. Using the directed volume method, the original irregular elements such as tetrahedrons, hexahedrons, and triangular prisms inside the component to be optimized are replaced with regular hexahedral elements. Simultaneously, the loads, boundary constraints, and connection elements on the non-optimized components remain unchanged. The loads, constraints, and connection relationships acting on the component to be optimized are migrated to the corresponding regular hexahedral elements according to the nearest mapping principle, thus obtaining an approximate simulation model that can replace the original CAE model for optimization calculations. This approximate optimization simulation model is similar to the original finite element simulation model of the engineering structure in size, topology, and shape, and possesses an expandable or transformable design domain boundary. By controlling the resolution, it can meet different needs in practice for rapid calculation and precise design.

[0072] In a feasible implementation, step S10 can include steps A11-A13:

[0073] Step A11, obtaining grid requirement information and boundary adjustment conditions;

[0074] It should be noted that the grid requirement information is a detailed requirement for the grid determined according to specific engineering requirements and optimization objectives when constructing an approximate optimization simulation model, and the boundary adjustment conditions are a series of loads, constraints and connection relationships that need to be transferred from the original finite element model to the new approximate optimization simulation model when performing model geometry mapping and reconstruction.

[0075] It can be understood that the grid requirement information can include parameters such as resolution, element type, size scaling factor, etc. of the grid, thereby ensuring the calculation efficiency and optimization accuracy of the model, making the model better adapt to different engineering requirements and optimization objectives, and through setting reasonable grid requirement information, the efficiency and practicality of optimization design can be significantly improved, and unnecessary waste of computing resources is reduced. The boundary adjustment conditions can be forces, pressures, moments, etc. applied to the structure, or degrees of freedom limiting the displacement of the structure, such as fixed supports, hinges, sliding constraints, etc. In the original model, the boundary adjustment conditions can act on the nodes or element faces of the irregular grid, and when the model is reconstructed into a regular hexahedral grid, the original action position will change. Therefore, these conditions need to be repositioned to the nearest regular hexahedral grid node through the nearest node method to ensure accurate transmission of mechanical behavior.

[0076] Step A12, based on the average size of the grid in the finite element simulation model of the original engineering structure, setting a size scaling factor to adjust the background grid resolution according to the grid requirement information, and generating hexahedral element grid information;

[0077] It should be noted that the hexahedral element grid information is a collection of regular hexahedral elements formed by replacing irregular elements with regular hexahedral elements.

[0078] It can be understood that the hexahedral element grid information is generated by setting a size scaling factor and adjusting the background grid resolution, including the geometric parameters, topological connection relationships, and mapping relationship with the original model of each hexahedral element. The geometric parameters can be edge length, position, direction, etc. The topological connection relationship can be the connection mode of adjacent elements. The hexahedral element grid information can be used to represent the regularized grid structure, thereby improving the calculation efficiency and reducing the memory occupation.

[0079] Step A13, based on the hexahedral element mesh information, the irregular elements of the corresponding component to be processed are mapped to the corresponding regular hexahedral elements for reconstruction, and the boundary adjustment condition is adjusted to the regular hexahedral nodes by using the nearest node method to obtain an approximate optimization simulation model.

[0080] It can be understood that the irregular elements in the original model can be mapped to regular hexahedral elements by using the directed volume method, so as to ensure that the total volume and shape of the structure are maintained during the replacement process, simplify the grid structure, improve the calculation efficiency, and at the same time, the load and constraint migration is carried out, that is, the load, boundary constraint and connection elements on the non-optimized component are kept unchanged, and the load, constraint and connection relationship acting on the optimized component are migrated to the corresponding regular hexahedral elements according to the nearest mapping principle, so that the optimization result can accurately reflect the actual engineering demand. The approximate optimization simulation model generated not only has similar size, topology and shape to the original model, but also has an expandable or transformable design domain boundary, providing greater flexibility, allowing the size and shape of the design domain to be adjusted as needed during the optimization process.

[0081] Step S20, based on the approximate optimization simulation model, the typical design mode of multi-component non-interference optimization is determined by transforming the design domain state and range;

[0082] It should be noted that the typical design mode is an initial design domain identified based on the approximate optimization simulation model, and a plurality of standard design configurations formed by adjusting the initial design domain.

[0083] It is understood that the typical design patterns may include lightweight design patterns, local search design patterns, local reconstruction design patterns, additive reinforcement design patterns, external domain global reconstruction design patterns, internal domain global reconstruction design patterns, pure shape optimization design patterns, and two-stage collaborative optimization design patterns (topology first, shape second). The lightweight design pattern reduces the weight of the structure while maintaining or improving its mechanical properties. The local search design pattern performs fine-tuning adjustments to local areas of the structure. The local reconstruction design pattern redesigns local areas of the structure to meet specific performance requirements. The additive reinforcement design pattern enhances specific areas of the structure by adding materials to improve its load-bearing capacity. The external domain global reconstruction design pattern... The global reconstruction design mode is based on defining the main shape or external skeleton of the product structure in a non-design domain, and obtaining the main force transmission path inside the skeleton through global optimization. The internal domain global reconstruction design mode uses the maximum space covered by the initial design domain of the original model as the initial design domain of the approximate model of the optimization design, and performs global reconstruction design. The pure shape optimization design mode optimizes the shape of the structure to improve its mechanical performance. The two-stage collaborative optimization design mode of topology first and shape later performs topology optimization first and then shape optimization to achieve better design results. The use of the typical design modes provides diversified choices for optimization design, making the optimization process more flexible to cope with different engineering needs and design goals, and improving the efficiency and practicality of optimization design.

[0084] In a specific embodiment, such as Figure 3 As shown, Figure 3 This application adjusts the initial design domain diagram of the approximate optimization simulation model for the direct topology and shape optimization method for existing engineering structural models. The original engineering structure is analyzed to clarify the design domain and non-design domain. The design domain is the part that needs optimization, while the non-design domain remains unchanged. Operations are then performed on the design domain in the approximate optimization simulation model. Specifically, if it's necessary to increase the design space to explore more optimization possibilities, the design domain is expanded; if it's necessary to limit the optimization range to focus on a specific region, the design domain is restricted; if the original design domain remains unchanged, it is maintained. Through these corresponding operations, various initial design configurations can be formed. Based on this, and combined with actual engineering needs and optimization objectives, eight design patterns can be proposed, such as lightweight design pattern, local search design pattern, local reconstruction design pattern, additive reinforcement design pattern, external domain global reconstruction design pattern, internal domain global reconstruction design pattern, pure shape optimization design pattern, and a two-stage collaborative optimization design pattern (topology first, shape second). This yields typical design patterns, such as... Figure 4 As shown, Figure 4The typical design mode schematic diagram is constrained by the direct topology and shape optimization method of the existing engineering structure model of the application, wherein Master is the master control area in the design domain, which contains a group of design variable control points. These control points are the main variables of the optimization design, which are used to control the shape and topology changes of the structure. In the variable grouping strategy, the design variable control points of the master area are the mapping source of the design variable points of other areas, such as the slave area. Slave is the subordinate area in the design domain. The design variable points of the subordinate area are generated by the geometric transformation of the design variable control points of the master area. The design variable points of the slave area maintain consistent distribution and relationship with the design variable control points of the master area. In the optimization process, the design variable points of the slave area are updated according to the variable values of the master area. Casting Direction refers to the direction in the casting process. In the optimization design, casting direction is an important manufacturing process constraint that affects the quality and performance of the casting. By applying the casting direction constraint, it can be ensured that the optimized structure can be smoothly demolded during the casting process, reducing manufacturing defects. For example, in some designs, it is necessary to ensure that certain parts of the structure have a certain slope in a certain direction to facilitate demolding during casting. Therefore, only the design variable points in the master domain need to be generated, i.e. the position and range of the master domain are determined, and a group of design variable control points in the master domain are generated, which are used to control the shape and topology changes of the structure. According to the specific manufacturing process requirements, the design variable points in the master domain are mapped to each sub-domain through geometric transformation, such as translation, rotation, scaling and mirroring, to generate design variable points in the sub-domain. Multiple transformation operations are used to ensure that the design variable points in the sub-domain maintain consistent distribution and relationship with the design variable points in the master domain, thereby achieving global coordination of the design variables. The control points in the master domain and their corresponding points generated in each sub-domain are divided into the same variable group, forming multiple variable groups. The design variable points in each variable group will be subject to numerical constraints. By applying specific numerical constraints to the design variables in each group, various manufacturing process requirements can be achieved, such as plane symmetry, rotational symmetry or periodic repeating structure if the variables in the constraint group take equal values; if the variables in the constraint group show an increasing or decreasing trend, the casting demolding direction or the layer thickness change of additive manufacturing process limitation can be simulated, thereby improving the flexibility of the optimization design and significantly enhancing the manufacturability of the optimization result, so that the optimization design can better meet the actual engineering requirements.

[0085] Step S30, based on the typical design mode, the same discrete adjoint equation is used to convert the sensitivity applied independently or in combination under different sensitivity algorithms to determine a compatible unified optimization framework;

[0086] It should be noted that the compatible unified optimization framework is an integrated optimization platform that can be compatible with and cooperatively call multiple mainstream topology and shape optimization algorithms, such as the bidirectional evolutionary structural optimization (BESO) algorithm, the variable density level set method (VFLSM), and the solid isotropic material penalization (SIMP) method, so as to fully exert the advantageous characteristics of each optimization method rather than simply compensate for the limitations thereof.

[0087] It can be understood that the compatible unified optimization framework can seamlessly integrate multiple optimization algorithms such as BESO, VFLSM, and SIMP, and allow independent application or combined application of these algorithms in the same optimization process, so that the most suitable optimization method or method combination can be flexibly selected according to specific design requirements and optimization objectives. For example, the compatible unified optimization framework can fully utilize the advantages of the BESO method in material distribution optimization, such as no false material and easy generation of clear holes, the advantages of the VFLSM method in implicit boundary description and high-precision shape evolution, and the strong modeling capability of the SIMP method in handling multiple constraint and multiple objective optimization problems. Through complementary advantages, a more comprehensive and efficient optimization solution is provided. The compatible unified optimization framework integrates a variable grouping strategy, can efficiently apply manufacturing process constraints such as planar symmetry, rotational symmetry, mode repetition, and casting draft under different optimization modes, ensures that the optimization result is improved in performance, has good manufacturability, significantly improves the efficiency and practicality of optimization design, reduces the operation complexity, improves the human-computer interaction friendliness, and ensures that the optimization result can better meet the actual engineering requirements and manufacturing process requirements.

[0088] In specific embodiments, according to the selected typical design mode, the boundary of the target design domain in the optimization design approximate model is adjusted. For example, if the local reconstruction design mode is adopted, the specific region of the design domain is expanded or limited to focus on the part that needs to be optimized. If the global reconstruction design mode is adopted, the boundary of the entire design domain is redefined to explore a wider design space. The boundary adjustment operation is based on in-depth analysis of the original engineering structure performance and optimization objectives, and provides a suitable search space for the optimization algorithm. Using the adjusted design domain boundary, a compatible unified optimization framework is constructed. The compatible unified optimization framework can integrate multiple optimization algorithms such as BESO, VFLSM, and SIMP, and ensure that they work cooperatively under a unified calculation system, realizing seamless connection of sensitivity calculation and design variable updating of different optimization methods.

[0089] In a feasible implementation, step S30 can include step B11:

[0090] Step B11, based on the typical design mode, the same discrete adjoint equation is used to simplify the piecewise constant function of the velocity interpolation function, and a compatible unified optimization framework is obtained, which is used to adapt the sensitivity characteristics of different optimization algorithms to realize the independent or combined application of BESO, SIMP and VFLSM in the optimization process.

[0091] It can be understood that different sensitivity algorithms have unique sensitivity characteristics, which are the sensitivity of each optimization method to the design variables of the objective function, for example, the BESO method optimizes by gradually adding and removing materials, has the characteristics of no gray unit and step-by-step optimization, and is suitable for generating clear hole and material distribution, the VFLSM method describes the structure boundary through the level set function, has the characteristics of smooth boundary and high-precision shape evolution, and can effectively avoid grid distortion, the SIMP method optimizes through material density variables, has strong multi-objective optimization ability and gray unit processing characteristics, and is suitable for processing complex multi-objective and multi-constraint problems.

[0092] In addition, it should be noted that in the compatible unified optimization framework, the sensitivity of the independent or combined application of different sensitivity algorithms can be unified and converted by defining mapping relationships, conversion rules and adjusting parameters, so that they can work together under the same framework, significantly improving the optimization efficiency and the accuracy of the results.

[0093] In a feasible implementation mode, after step B11, steps C11-C13 can also be included:

[0094] Step C11, obtaining unit-level design response parameter information, the unit-level design response parameter information including volume fraction, compliance, stress, frequency, heat dissipation weakness and displacement, etc.

[0095] It should be noted that the unit-level design response parameter information is the parameter of the response of each unit to the change of the design variable, representing the mechanical properties of the structure under different design variables.

[0096] It can be understood that the volume fraction is the ratio of the volume of the material in the unit to the volume of the entire unit, which is a value between 0 and 1, indicating the relative content of the material in the unit, the compliance is the deformation degree of the structure under the action of external load, which is represented by displacement or strain energy, the smaller the compliance, the higher the stiffness of the structure, the stress is the distribution of the force generated inside the unit under the action of external load, the frequency is the natural frequency of the structure, that is, the frequency of free vibration of the structure when it is not subjected to external force, to avoid resonance, if the frequency of external excitation coincides with the natural frequency of the structure, resonance will occur, resulting in structure damage, the heat dissipation weakness is a "weakness" for measuring the heat dissipation efficiency of the structure. It can be generally understood as the highest temperature or average temperature of the structure. In equipment that requires good heat dissipation, by optimizing the layout and shape of the material to form an efficient heat conduction path, the working temperature of the key part can be reduced, and the displacement is the deformation degree of the unit under the action of external load, which characterizes the deformation of the structure under the action of load.

[0097] Step C12, analyzing the mapping relationship between the design variables corresponding to the unit-level design response parameter information and the physical properties of the unit by using the discrete adjoint method, and determining the analysis result;

[0098] It should be noted that the analysis result is a sensitivity expression analysis result obtained by analyzing and deducing the unit-level design response parameter information by the discrete adjoint method.

[0099] It can be understood that the analysis result can represent the sensitivity of the design variable to the objective function, ensuring that the sensitivity of different optimization methods can be interchanged and cooperated in the same calculation system under the unified optimization framework, thereby improving the flexibility and adaptability of the optimization algorithm, and realizing efficient and accurate structure optimization design.

[0100] Step C13, converting the same discrete sensitivity to different optimization algorithm sensitivities by using the analysis result.

[0101] It can be understood that the sensitivities of different optimization methods can be uniformly processed by the analysis result, ensuring that they can be effectively interchanged and cooperated in the same optimization framework, so that the optimization process can be flexibly switched between different methods, while ensuring that the optimization result meets the performance requirements and conforms to the constraints of the actual manufacturing process.

[0102] Step S40, determining a variable grouping strategy based on the compatible unified optimization framework to uniformly apply multiple manufacturing process constraints, and obtaining a structure improvement scheme with strong manufacturability.

[0103] It can be understood that the structural improvement scheme can achieve lightweight, stiffness improvement, stress balance and other performance improvement while still having good manufacturability, effectively bridging the gap between topology / shape optimization results and actual production, and significantly improving the engineering landing ability and practical value of the optimization design results.

[0104] In specific embodiments, as Figure 5 shown, Figure 5 is a direct topology and shape optimization method for lightweight design mode of existing engineering structure model of the application, the design domain of the optimization design approximation model is completely consistent with the design domain of the original model, without any expansion or restriction, so as to retain the integrity and boundary conditions of the original design, in order to meet the demand for high-precision design of size in engineering, the design domain is finely divided by high-resolution grid, so that the optimization calculation can capture more subtle structural changes, so as to realize more accurate lightweight design, on this basis, the material distribution in the design domain is optimized by using the solid isotropic material penalty method SIMP, the weight of the structure is reduced by adjusting the material density, while the mechanical properties of the structure are not affected, and the variable grouping method is used to apply the mode repeated manufacturing constraint, specifically, the design domain is divided into multiple sub-domains, and design variable points are generated in these sub-domains by multiple transformations, the generated design variable points are grouped and numerical constraints are applied, so that different size wing parts have similar structural characteristics, ensuring the lightweight effect of the optimized parts, facilitating the unified manufacturing of wings of different sizes, and significantly improving the production efficiency and consistency.

[0105] As shown in Figure 6 , Figure 6 is a direct topology and shape optimization method for local reconstruction design mode of existing engineering structure model of the application, the area in the original model design domain that needs to be locally expanded is appropriately expanded according to the optimization target and engineering demand, the expanded design domain is endowed with solid material as the initial state of optimization design, and the solid isotropic material penalty method SIMP is used for local reconstruction design, in this process, cyclic symmetry constraint needs to be introduced to ensure that the optimized structure meets the design requirements in terms of cyclic symmetry, specifically, if the cycle number of the original structure is 5, the optimization design will be based on this, the structure performance is optimized by adjusting the material distribution, while the cyclic symmetry is maintained, so that the optimization design can effectively optimize the topology of the existing structure and redesign it, so as to improve the performance and efficiency of the structure while meeting the engineering requirements.

[0106] As shown in Figure 7 , Figure 7This diagram illustrates the global reconstruction design mode of the intrinsic domain for the direct topology and shape optimization method of this application for existing engineering structural models. The maximum spatial range covered by the initial design domain of the original model is set as the initial design domain of the approximate model of the optimization design. The solid isotropic material penalty method (SIMP) is used for the global reconstruction design of the intrinsic domain. In this mode, the number of iterations of the cyclic symmetry constraint is redefined according to the optimization requirements. For example, in this case, the number of iterations is set to 6. At the same time, in order to ensure that the optimization results meet the actual manufacturing process requirements, casting process constraints need to be applied to adjust the material distribution globally. This ensures that the design results meet the manufacturability requirements of the casting process while maintaining the structural performance. Through this global reconstruction design, an optimized structure that meets both engineering performance requirements and is easy to produce can be obtained.

[0107] like Figure 8 As shown, Figure 8 This is a schematic diagram of the external domain global reconstruction design mode of the direct topology and shape optimization method for existing engineering structure models in this application. The maximum spatial range covered by the initial non-design domain of the original model is set as the initial design domain of the approximate model of the optimization design. On this basis, the external domain global reconstruction design mode is adopted. This mode defines the main shape or external skeleton of the product structure based on the non-design domain. Through global optimization algorithms, such as topology optimization methods, the main force transmission paths inside the skeleton are searched and determined.

[0108] like Figure 9 As shown, Figure 9 This diagram illustrates the additive reinforcement design mode of the direct topology and shape optimization method for existing engineering structural models proposed in this application. The entire original model is defined as a non-design domain. Solid material of a certain size is uniformly extended onto the surface of the model to form an initial design domain. The extension size is determined based on the performance requirements and optimization objectives of the structure. The bidirectional evolutionary structural optimization method (BESO) is used to optimize the extended design domain. The BESO method optimizes the material distribution of the structure by gradually adding and removing materials, thereby improving the mechanical properties of the structure. During the optimization process, the BESO method can identify areas with poor performance in the structure and perform targeted material reinforcement. The optimization results can not only clearly indicate the specific areas that need reinforcement, but also provide a material distribution scheme after reinforcement.

[0109] like Figure 10 As shown, Figure 10This diagram illustrates the local search design mode of the direct topology and shape optimization method for existing engineering structural models. The original model's design domain is locally expanded, with the expansion range determined by the structure's performance requirements and optimization objectives. The expanded design domain is assigned empty material as the initial design; that is, in the initial state, the expanded region contains no material. The bidirectional evolutionary structural optimization method (BESO) is used for local search design. BESO optimizes the material distribution of the structure by progressively adding and removing materials, thereby improving the structure's mechanical properties. Since BESO does not have grayscale elements, there will be no intermediate state of partially material and partially void elements during the optimization process, ensuring that each iteration is an effective improvement to the original structure. Under the constraint of constant weight, the design boundary is automatically expanded as needed during the optimization process, thereby improving structural performance.

[0110] like Figure 11 As shown, Figure 11 This diagram illustrates the pure shape optimization design mode of the direct topology and shape optimization method for existing engineering structural models proposed in this application. After appropriately expanding the regions in the original model's design domain that require local expansion, the expanded design domain is assigned empty material as the initial design. That is, at the start of optimization, these expanded regions do not contain any material. Pure shape optimization design is performed using the Variable Density Level Set (VFLSM) method. The VFLSM method evolves the structural boundary by controlling design variables, optimizing the shape of the structure. During the optimization process, the design boundary is automatically expanded according to requirements by activating hexahedral elements around the boundary, avoiding mesh distortion problems and ensuring the stability and accuracy of the optimization process.

[0111] like Figure 12 As shown, Figure 12For the direct topology and shape optimization method of the existing engineering structure model of the application, the sensitivity of different optimization methods in the optimization framework can be converted, the two-stage collaborative optimization design mode of topology first and shape second is shown, the bi-directional evolutionary structure optimization BESO and the variable density level set method VFLSM are organically combined, specifically, the BESO method is used for topology optimization, the powerful hole generation capability is used to determine the distribution of materials and the overall shape of the structure, in the topology optimization stage, the BESO method optimizes the material distribution of the structure by gradually adding and removing materials, and the VFLSM method is used for shape optimization, the smooth boundary characteristics are used to finely adjust the structure boundary after topology optimization, the VFLSM method evolves the structure boundary by controlling the design variables, optimizes the shape of the structure, so that the structure boundary is smoother and the stress concentration phenomenon is reduced, through the optimization mode of topology first and shape second, the two methods complement each other, the optimization result with smooth boundary and excellent performance is obtained, the overall performance and manufacturability of the structure are significantly improved, the structure improvement scheme can be used to update the design variables, the sensitivity of the design variables to the objective function is characterized, so that the design variables are adjusted in each iteration to gradually improve the structure performance, and whether the structure meets the design requirements is verified, if not, the structure optimization is repeated until the optimization target is achieved, based on the optimized design variables, the corresponding structure improvement scheme is generated, so that the performance is significantly improved, and the constraints of the actual manufacturing process are considered to ensure the engineering practicability and manufacturability of the optimization result.

[0112] In a possible implementation, step S40 can include steps D11-D12:

[0113] In step D11, the approximate optimization simulation model identifies that the initial design domain is divided into a main domain and a plurality of sub-domains, and maps the design variable control points of the main domain to the corresponding sub-domains to form variable grouping information decoupled from the finite element grid;

[0114] It should be noted that the variable grouping information is a set composed of the design variable control points in the main domain and the corresponding design variable points generated by the transformation in each sub-domain after the design domain is divided into a main domain and a plurality of sub-domains.

[0115] It can be understood that the design variable points of the variable grouping information are divided into the same group in the optimization process, so as to apply uniform numerical constraints, thereby ensuring that the optimization result meets the specific manufacturing process requirements, wherein the design variable control points in the main domain and the corresponding points generated in each sub-domain through geometric transformation can be divided into the same variable group, and uniform numerical constraints are applied to the variables in these groups to achieve specific manufacturing process requirements, such as planar symmetry, rotational symmetry, pattern repetition, and casting draft, so as to ensure that the optimization design can better meet the actual engineering requirements.

[0116] In addition, it should be noted that the design domain is divided into a main domain and a plurality of sub-domains, the main domain contains a group of design variable control points decoupled from the finite element mesh, the design variable control points are main variables in the optimization process, used to control the shape and topology changes of the structure, and the control points in the main domain are mapped to each sub-domain according to the type and parameters of the manufacturing process constraints, to generate design variable points in the sub-domain, thereby ensuring that the design variable points in the sub-domain and the control points in the main domain maintain consistent distribution and relationship, and the control points in the main domain and the corresponding points generated in each sub-domain are divided into the same variable group, and the design variable points in each variable group will be subjected to uniform numerical constraints in the optimization process, thereby significantly improving the flexibility of the design, and ensuring that the optimization design can better meet the actual engineering requirements.

[0117] Step D12, constraint the corresponding typical design pattern based on the variable grouping information, to obtain a structure improvement scheme with strong manufacturability, wherein the structure improvement scheme includes planar symmetry, cyclic symmetry, extrusion, pattern repetition, and casting constraints.

[0118] It should be noted that the structure improvement scheme is an optimization design scheme obtained by constraining the typical design pattern based on the variable grouping information.

[0119] It can be understood that the variable grouping information can be used to divide the design domain into a main domain and a plurality of sub-domains, and map the design variable control points in the main domain to each sub-domain to form variable groups decoupled from the finite element mesh, and apply numerical constraints to the design variables in these variable groups to meet specific manufacturing process requirements, thereby significantly improving performance and having good manufacturability, and being able to be directly applied to actual production.

[0120] In a feasible implementation manner, step D12 can include steps E11-E12:

[0121] Step E11, when the variable grouping information is that the values of the variables in the constraint group are equal, the constraint structure scheme is planar symmetry, rotational symmetry, or periodic repetition structure.

[0122] It can be understood that when the variable grouping information shows that the variable values in the constraint group are equal, the optimization result will present a specific symmetry or repetitive structure, such as plane symmetry, rotational symmetry or periodic repetition structure, which improves the aesthetics and regularity of the optimization result, significantly enhances the manufacturability of the structure, and makes it more consistent with the process requirements in actual production, thereby ensuring that the optimization design not only meets the performance optimization but also has good engineering practicability and manufacturability.

[0123] In step E12, when the variable grouping information shows that the variables in the constraint group present an increasing or decreasing trend, the constraint structure scheme is a process constraint structure simulating the casting draw direction or the layer thickness change of additive manufacturing.

[0124] It can be understood that when the variable grouping information shows that the variables in the constraint group present an increasing or decreasing trend, the optimization result will simulate specific manufacturing process constraints, such as the casting draw direction or the layer thickness change of additive manufacturing, to ensure that the optimized structure can meet the specific process requirements in the manufacturing process, thereby improving the manufacturability and engineering practicability of the structure.

[0125] The direct topology and shape optimization method for an existing engineering structure model proposed in this embodiment is based on a regular hexahedral element mapping of the finite element simulation model of the original engineering structure to determine an approximate optimization simulation model; based on the approximate optimization simulation model, the state and range of the design domain are transformed to determine a typical design mode of multi-component non-interference optimization; based on the typical design mode, the same discrete adjoint equation is used to convert the sensitivity of independent or combined application under different sensitivity algorithms to determine a compatible unified optimization framework; and based on the compatible unified optimization framework, a variable grouping strategy is determined to uniformly apply various manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability. The technical problem of how to more efficiently perform direct topology and shape optimization for an existing engineering structure model is solved. Compared with the prior art, the regular hexahedral element is used to reconstruct the finite element simulation model of the original engineering structure in this application, which simplifies the model structure and improves the calculation efficiency, identifies the design mode and adjusts the design domain boundary, provides a clear direction and precise positioning for optimization, constructs a unified framework compatible with various optimization methods, realizes the collaborative application of different sensitivity algorithms, thereby obtaining sensitivity adjustment information, accurately adjusting the design variables using an optimization algorithm, generating a structure improvement scheme that meets engineering requirements and manufacturing process constraints, significantly improving optimization efficiency, adaptability and result accuracy, reducing operation complexity, and enhancing engineering practicability.

[0126] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as the above embodiment one can refer to the above introduction, and the subsequent will not be described in detail.

[0127] In this embodiment, reference is made toFigure 13 , Figure 13 The flowchart provided for the second embodiment of the direct topology and shape optimization method for the existing engineering structure model of the application specifically includes steps S21-S22:

[0128] In step S21, an initial design domain is identified based on the approximate optimization simulation model.

[0129] It should be noted that the initial design domain is a design area in the initial state determined based on the finite element simulation model of the original engineering structure in the optimization design process, which is the starting point of the optimization design and includes all materials and spaces involved in the optimization.

[0130] It can be understood that the initial design domain defines the spatial range of the optimization design, i.e., which parts of the structure will be considered for optimization, and the geometry and size of the original engineering structure need to be considered and expanded or limited according to the optimization target.

[0131] In specific embodiments, the finite element simulation model of the original engineering structure is analyzed to extract key information such as geometry, size, and boundary conditions. Based on the extracted information, the spatial range of the initial design domain can be determined in the approximate optimization simulation model to ensure that the range covers all areas that need to be optimized. The material distribution within the initial design domain is initialized, giving uniform material density or reasonable material distribution settings according to the pre-analysis results. The boundary conditions of the initial design domain are defined, including fixed boundaries and load-acting boundaries, which will serve as constraint conditions in the optimization process. At the same time, design variables such as material density and shape parameters within the initial design domain are defined and assigned initial values, thereby accurately identifying the initial design domain and obtaining the initial design domain.

[0132] In step S22, the initial design domain is transformed and adjusted to obtain a typical design mode for multi-component non-interference optimization, including subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization, and topology-first shape-second design.

[0133] It should be noted that the typical design mode is a standardized design configuration formed by mode adjustment based on the characteristics of the initial design domain and the optimization target, which is used for material distribution and shape adjustment within the design domain.

[0134] It can be understood that the mode adjustment is a series of operations on the initial design domain to adapt to different optimization requirements and design goals, wherein the mode adjustment includes expansion, restriction or retention, the expansion is to expand the boundary of the initial design domain outward to increase the design space, which is used to explore more optimization possibilities, to provide more degrees of freedom for the optimization algorithm, and to achieve more significant performance improvement, the restriction is to shrink the boundary of the initial design domain inward to reduce the design space, which is used to focus on a specific area for optimization, for example, in the local search or additive reinforcement design mode, the restriction improves the optimization efficiency, reduces the consumption of computing resources, and ensures the accuracy of the optimization result, the retention is to keep the boundary of the initial design domain unchanged, and to optimize directly in the original design space, which is suitable for lightweight design or pure shape optimization design mode, and in the case of not changing the design space, the performance is improved by adjusting the material distribution or shape.

[0135] Additionally, it needs to be noted that the subtractive design is to realize lightweighting within the design space of the original structure by removing material, without expanding the original design boundary, taking the original structure as the initial state, using optimization algorithms to dig holes or reduce material inside, to find the optimal material distribution, the local search is to add a small range of exploratory material in a specific local area of the original structure to improve the performance of the area, to expand the design domain of the local area to be optimized, but set these expanded areas to empty material in the initial state, then use BESO and other methods to allow the algorithm to generate material within the expanded domain, the local reconstruction is to completely redesign a certain sub-component or larger area of the structure, allowing its topology and shape to change significantly, select the component to be reconstructed, expand its design domain, and give it solid material as the initial state. Then use topology optimization methods to freely optimize within the expanded domain, the endogenous domain global reconstruction is to take the maximum space occupied by the original model itself as the new design domain, and completely reconstruct from the inside out, taking the outer envelope of the original model as the initial design domain of the optimization design, and then performing topology optimization, the exogenous domain global reconstruction is to take the original model as the skeleton or non-design domain, and find the optimal material distribution and force transmission path in the external space, set the original model as an immutable non-design domain, and then define the design domain in the larger external space around it, and perform topology optimization, the stiffening reinforcement is to add material to the surface of the original structure to enhance its performance, define the entire original model as a non-design domain, and uniformly expand a thin layer of material on the surface as a design domain. Then use BESO and other methods to optimize the layer of material to form a reinforcing rib, the shape optimization is to change the topology of the structure, only to adjust the boundary shape of the structure smoothly, using level set method, by moving the boundary to improve the stress distribution or other performance, the design domain is an expansion of the original model surface, initially empty, the topology first and then shape design is to combine the advantages of topology optimization and shape optimization, using BESO or SIMP to perform topology optimization to obtain a macroscopic, material-efficient layout, but the boundary is rough, and then taking the topology optimization result as the initial input, using VFLSM to perform shape optimization to smooth the boundary, further optimize the performance, and obtain the final design with high-efficiency material layout and smooth high-quality boundary.

[0136] In specific embodiments, according to the optimization target and design requirements, the state of the initial design domain is evaluated. If the target is to provide more optimization space for a specific area of the structure, such as in the local reconstruction design mode, the boundary of the initial design domain is expanded, the number and distribution range of design variables are increased, and the optimization algorithm can explore the optimization possibilities of the area more freely. If the optimization focus is to improve the local performance of the structure, such as in the local search design mode, the initial design domain is limited, the optimization range is reduced, and the key area is focused on, unnecessary calculations are reduced, and the optimization efficiency is improved. If optimization needs to be performed on the basis of the existing design, such as the lightweight design mode, the initial design domain boundary is kept unchanged, the material distribution or shape is directly adjusted in the original area, and the performance of the structure is improved. Through mode adjustment, different design requirements can be more flexibly adapted to.

[0137] The direct topology and shape optimization method for existing engineering structure model proposed in this embodiment identifies the initial design domain based on the approximate optimization simulation model; the initial design domain is transformed and adjusted to obtain a typical design mode for multi-component non-interference optimization, which includes subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization, and topology-first shape-second design. The technical problem of how to more efficiently perform direct topology and shape optimization for existing engineering structure model is solved. Compared with the prior art, the initial design domain is identified by the approximate optimization simulation model, and the typical design mode is obtained through mode adjustment means such as expansion, limitation or maintenance, reducing the need for a large amount of preprocessing of the original engineering structure, reducing the operation complexity of engineers, improving the friendliness of human-computer interaction, and enhancing the adaptability and flexibility of optimization design through flexible mode adjustment, so that it can better meet different engineering requirements and design targets, and significantly improve the performance. At the same time, it has good manufacturability, ensures that the optimization design can be directly applied to actual production, and significantly improves the engineering practicability and efficiency of structural optimization design.

[0138] For the purpose of assisting understanding of the implementation process of the direct topology and shape optimization method for existing engineering structure model obtained after combining the above-mentioned embodiment one, please refer to Figure 14 , Figure 14 A brief flowchart of the direct topology and shape optimization method for existing engineering structure model is provided, specifically:

[0139] Referring to Example 1, based on the finite element simulation model of the original engineering structure, a regular hexahedral element is mapped to determine an approximate optimization simulation model; based on the approximate optimization simulation model, a design domain state and range are transformed to determine a typical design mode of multi-component non-interference optimization; based on the typical design mode, a same discrete adjoint equation is used to convert the sensitivity applied independently or in combination under different sensitivity algorithms to determine a compatible unified optimization framework; and based on the compatible unified optimization framework, a variable grouping strategy is determined to uniformly apply various manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability. Referring to Example 2, based on the approximate optimization simulation model, an initial design domain is identified; the initial design domain is transformed and adjusted to obtain a typical design mode of multi-component non-interference optimization, which includes subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization, and topology-first shape-second design. Based on the finite element simulation model of the original engineering structure, an approximate optimization simulation model for optimization design is constructed, an initial design domain of the approximate optimization simulation model is automatically identified and adjusted, and eight design modes suitable for the original engineering structure are proposed. Based on the eight design modes, a unified optimization framework compatible with BESO, VFLSM, and SIMP methods is constructed. For the optimization framework, a unified discrete sensitivity analysis method is used to realize independent application or combined cooperation of the above optimization methods. In the independent or combined application process of different methods, a variable grouping strategy is introduced to meet the actual manufacturing process constraints, and finally a structure improvement scheme with high engineering practical value considering performance improvement and manufacturability is obtained.

[0140] It should be noted that the above examples are only used for understanding the present application and do not constitute a limitation on the direct topology and shape optimization method of the existing engineering structure model faced by the present application. More forms of simple transformation based on this technical concept are within the protection scope of the present application.

[0141] The present application also provides a direct topology and shape optimization device for an existing engineering structure model. Please refer to Figure 15 The direct topology and shape optimization device for an existing engineering structure model comprises:

[0142] The acquisition module 10 is configured to map a regular hexahedral element based on the finite element simulation model of the original engineering structure to determine an approximate optimization simulation model.

[0143] The processing module 20 is configured to transform a design domain state and range based on the approximate optimization simulation model to determine a typical design mode of multi-component non-interference optimization.

[0144] The processing module 20 is further configured to convert the sensitivity applied independently or in combination under different sensitivity algorithms based on the typical design mode using a same discrete adjoint equation to determine a compatible unified optimization framework.

[0145] The execution module 30 is configured to determine a variable grouping strategy based on the compatible unified optimization framework to uniformly apply multiple manufacturing process constraints, so as to obtain a structure improvement scheme with high manufacturability.

[0146] The acquisition module 10 is further configured to acquire grid requirement information and boundary adjustment conditions.

[0147] Based on the average size of the grid in the finite element simulation model of the original engineering structure, the size scaling coefficient is set according to the grid requirement information to adjust the background grid resolution, and hexahedral element grid information is generated.

[0148] Based on the hexahedral element grid information, the irregular elements of the corresponding component to be processed are mapped to the corresponding regular hexahedral elements for reconstruction, and the nearest node method is used to adjust the boundary adjustment conditions to the regular hexahedral nodes, so as to obtain an approximate optimization simulation model.

[0149] The processing module 20 is further configured to identify an initial design domain based on the approximate optimization simulation model.

[0150] The initial design domain is transformed and adjusted to obtain a typical design mode of multi-component non-interference optimization, and the typical design mode includes subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization, and topology-first shape-second design.

[0151] The processing module 20 is further configured to simplify the piecewise constant function of the velocity interpolation function based on the same discrete adjoint equation based on the typical design mode, so as to obtain a compatible unified optimization framework, and the compatible unified optimization framework is used to adapt the sensitivity characteristics of different optimization algorithms, so as to realize independent or combined application of BESO, SIMP and VFLSM in the optimization process.

[0152] The processing module 20 is further configured to acquire unit-level design response parameter information, and the unit-level design response parameter information includes volume fraction, compliance, stress, frequency, heat dissipation weakness, displacement, etc.

[0153] The mapping relationship between the design variables and the physical properties of the unit corresponding to the unit-level design response parameter information is analyzed by using the discrete adjoint method, and an analysis result is determined.

[0154] The analysis result is used to convert the same discrete sensitivity to obtain the sensitivity of different optimization algorithms.

[0155] The execution module 30 is further configured to divide the initial design domain identified by the approximate optimization simulation model into a main domain and a sub-domain, and map the design variable control points of the main domain to the corresponding sub-domain, so as to form variable grouping information decoupled from the finite element grid.

[0156] Constraining the corresponding typical design pattern based on the variable grouping information, to obtain a structure improvement scheme with strong manufacturability, the structure improvement scheme including plane symmetry, cyclic symmetry, extrusion, pattern repetition and casting constraint.

[0157] The execution module 30 is further configured to, when the variable grouping information is that variable values in the constraint group are equal, the manufacturing process constraint scheme is plane symmetry, rotational symmetry, extrusion or periodic repetition structure.

[0158] When the variable grouping information is that variables in the constraint group show an increasing or decreasing trend, the constraint structure scheme is a simulated casting draw direction or an additive manufacturing layer thickness change process restriction structure.

[0159] The direct topology and shape optimization device for an existing engineering structure model provided in the present application adopts the direct topology and shape optimization method for an existing engineering structure model in the above embodiment, and can solve the technical problem of how to more efficiently perform direct topology and shape optimization for an existing engineering structure model. Compared with the prior art, the direct topology and shape optimization device for an existing engineering structure model provided in the present application has the same beneficial effects as the direct topology and shape optimization method for an existing engineering structure model provided in the above embodiment, and other technical features of the direct topology and shape optimization device for an existing engineering structure model are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0160] The present application provides a direct topology and shape optimization device for an existing engineering structure model, which comprises at least one processor and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the direct topology and shape optimization method for an existing engineering structure model in the above embodiment one.

[0161] The following refers to Figure 16This document illustrates a structural schematic diagram of a direct topology and shape optimization device suitable for implementing embodiments of this application for existing engineering structure models. The direct topology and shape optimization device for existing engineering structure models in embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 16 The direct topology and shape optimization device for existing engineering structure models shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0162] like Figure 16 Figure 16 As shown, the direct topology and shape optimization device for existing engineering structure models may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the direct topology and shape optimization device for existing engineering structure models. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the direct topology and shape optimization device for existing engineering structure models to exchange data wirelessly or wiredly with other devices. Although the figure shows a direct topology and shape optimization device for existing engineering structure models with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0163] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiments disclosed in the present application are executed.

[0164] The direct topology and shape optimization device for an existing engineering structure model provided by the present application adopts the direct topology and shape optimization method for an existing engineering structure model in the above-mentioned embodiments, and can solve the technical problem of how to more efficiently perform direct topology and shape optimization for an existing engineering structure model. Compared with the prior art, the direct topology and shape optimization device for an existing engineering structure model provided by the present application has the same beneficial effects as the direct topology and shape optimization method for an existing engineering structure model provided by the above-mentioned embodiments, and other technical features in the direct topology and shape optimization device for an existing engineering structure model are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0165] It should be understood that parts of the present application can be realized by hardware, software, firmware or a combination thereof. In the description of the above-mentioned embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0166] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0167] The present application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e. computer program) for executing the direct topology and shape optimization method for an existing engineering structure model in the above-mentioned embodiments.

[0168] The computer readable storage medium provided in the application may be, for example, a U disk, but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination of the above. More specific examples of the computer readable storage medium may include, but are not limited to, an electrical connection with one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the embodiment, the computer readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electrical wire, an optical cable, an RF (Radio Frequency), and the like, or any suitable combination of the above.

[0169] The computer readable storage medium described above may be included in the existing engineering structure model oriented direct topology and shape optimization device, or may exist independently without being assembled into the existing engineering structure model oriented direct topology and shape optimization device.

[0170] The computer readable storage medium described above carries one or more programs, when the one or more programs are executed by the existing engineering structure model oriented direct topology and shape optimization device, the existing engineering structure model oriented direct topology and shape optimization device is caused to: map a finite element simulation model of an original engineering structure based on a regular hexahedral element to determine an approximate optimization simulation model; determine a typical design mode of multi-component non-interference optimization by transforming a design domain state and range based on the approximate optimization simulation model; determine a compatible unified optimization framework by converting sensitivities applied independently or in combination under different sensitivity algorithms using the same discrete adjoint equation based on the typical design mode; and determine a variable grouping strategy based on the compatible unified optimization framework to uniformly apply various manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability.

[0171] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0172] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0173] The modules involved in the embodiments of the present application can be implemented in software or hardware. In some cases, the names of the modules do not constitute a limitation on the modules themselves.

[0174] The readable storage medium provided by the application is a computer readable storage medium, which stores computer readable program instructions (i.e. computer programs) for executing the direct topology and shape optimization method for the existing engineering structure model, and can solve the technical problem of how to more efficiently perform the direct topology and shape optimization for the existing engineering structure model. Compared with the prior art, the computer readable storage medium provided by the application has the same beneficial effects as the direct topology and shape optimization method for the existing engineering structure model provided by the above-mentioned embodiments, and will not be described here.

[0175] The above-mentioned is only part of the embodiments of the application, and does not limit the patent scope of the application. Any equivalent structural transformation, direct / indirect application in other related technical fields, or the like made by using the content of the application specification and drawings under the technical concept of the application is included in the patent protection scope of the application.

Claims

1. A direct topology and shape optimization method for existing engineering structure models, characterized by, The method comprises: mapping a finite element simulation model of an original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model; transforming a design domain state and range based on the approximate optimization simulation model to determine a typical design mode of multi-component non-interference optimization; adopting a same discrete adjoint equation to convert sensitivities applied independently or in combination under different sensitivity algorithms based on the typical design mode to determine a compatible unified optimization framework, the compatible unified optimization framework integrating a bidirectional evolutionary structural optimization algorithm, a variable density level set method and a solid isotropic material penalization method for independent application or combined application in a same optimization process; determining a variable grouping strategy based on the compatible unified optimization framework to uniformly apply multiple manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability; the step of transforming a design domain state and range based on the approximate optimization simulation model to determine a typical design mode of multi-component non-interference optimization comprises: identifying an initial design domain based on the approximate optimization simulation model; transforming and adjusting the initial design domain to obtain a typical design mode of multi-component non-interference optimization, the typical design mode comprising subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization and topology-first shape-second design, being a standardized design configuration formed by mode adjustment based on features of the initial design domain and optimization objectives, the mode adjustment comprising expansion, limitation or maintenance, the expansion being outward expansion of a boundary of the initial design domain, the limitation being inward contraction of the boundary of the initial design domain, and the maintenance being maintenance of the boundary of the initial design domain unchanged for optimization in the original design space.

2. The method of claim 1, wherein, the step of mapping a finite element simulation model of an original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model comprises: obtaining grid requirement information and boundary adjustment conditions; adjusting background grid resolution by setting a size scaling coefficient based on the grid requirement information according to an average size of grids in the finite element simulation model of the original engineering structure to generate hexahedral element grid information; mapping irregular elements of a corresponding component to be processed to corresponding regular hexahedral elements for reconstruction based on the hexahedral element grid information, and adjusting the boundary adjustment conditions to regular hexahedral nodes using a nearest node method to obtain the approximate optimization simulation model.

3. The method of claim 1, wherein, the step of adopting a same discrete adjoint equation to convert sensitivities applied independently or in combination under different sensitivity algorithms based on the typical design mode to determine a compatible unified optimization framework further comprises: adopting a same discrete adjoint equation to simplify a piecewise constant function for a velocity interpolation function based on the typical design mode to obtain the compatible unified optimization framework, the compatible unified optimization framework being used to adapt sensitivity characteristics of different optimization algorithms to enable independent or combined application of a bidirectional evolutionary structural optimization algorithm, a variable density level set method and a solid isotropic material penalization method in an optimization process.

4. The method of claim 3, wherein, After the step of simplifying the piecewise constant function of the velocity interpolation function by using the same discrete adjoint equation based on the typical design pattern to obtain the compatible unified optimization framework, the method further includes: obtaining unit-level design response parameter information, the unit-level design response parameter information including volume fraction, compliance, stress, frequency, heat dissipation weakness, and displacement; analyzing a mapping relationship between design variables and unit physical properties corresponding to the unit-level design response parameter information by using a discrete adjoint method to determine an analysis result; converting the same discrete sensitivity into different optimization algorithm sensitivities by using the analysis result.

5. The method of claim 1, wherein, The step of determining a variable grouping strategy based on the compatible unified optimization framework to uniformly apply multiple manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability includes: identifying an initial design domain into a main domain and a sub-domain by using an approximate optimization simulation model, and mapping design variable control points of the main domain to corresponding sub-domains to form variable grouping information decoupled from finite element grid solutions; constraining a corresponding typical design pattern based on the variable grouping information to obtain a structure improvement scheme with strong manufacturability, the structure improvement scheme including plane symmetry, cyclic symmetry, extrusion, pattern repetition, and casting constraints.

6. The method of claim 5, wherein, The step of constraining a corresponding typical design pattern based on the variable grouping information to obtain a structure improvement scheme with strong manufacturability includes: when the variable grouping information is that variables in a constraint group take equal values, the structure improvement scheme is a plane symmetric, rotationally symmetric, extruded, or periodically repeated structure; when the variable grouping information is that variables in a constraint group show an increasing or decreasing trend, the structure improvement scheme is a structure simulating a casting draw direction or an additive manufacturing layer thickness change process restriction structure.

7. An apparatus for direct topology and shape optimization oriented to an existing engineering structure model, characterized by, The device includes: an obtaining module that maps a finite element simulation model of an original engineering structure by using regular hexahedral elements to determine an approximate optimization simulation model; a processing module that is configured to determine a typical design pattern of multi-component non-interference optimization by transforming a design domain state and range based on the approximate optimization simulation model; the processing module is further configured to convert sensitivities applied independently or in combination under different sensitivity algorithms by using the same discrete adjoint equation based on the typical design pattern to determine a compatible unified optimization framework, the compatible unified optimization framework integrating a bidirectional evolutionary structure optimization algorithm, a variable density level set method, and a solid isotropic material penalization method, and independently or in combination applying in the same optimization process; an executing module that is configured to determine a variable grouping strategy based on the compatible unified optimization framework to uniformly apply multiple manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability; the processing module is further configured to identify an initial design domain based on the approximate optimization simulation model. The initial design domain is transformed and adjusted to obtain a multi-component non-interference optimized typical design mode, which includes subtractive design, local search, local reconstruction, endogenous domain global reconstruction, exogenous domain global reconstruction, stiffening reinforcement, shape optimization and shape design after topology, is a standardized design configuration formed by mode adjustment based on the characteristics of the initial design domain and the optimization target, and the mode adjustment includes expansion, limitation or maintenance, the expansion is to expand the boundary of the initial design domain outward, the limitation is to shrink the boundary of the initial design domain inward, and the maintenance is to keep the boundary of the initial design domain unchanged to optimize in the original design space.

8. A direct topology and shape optimization apparatus for an existing engineering structure model, characterized by, The device comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the direct topology and shape optimization method for the existing engineering structure model according to any one of claims 1 to 6.

9. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the direct topology and shape optimization method for the existing engineering structure model according to any one of claims 1 to 6.

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