Direct topology and shape optimization method for existing engineering structure model

Abstract

The invention discloses a direct topology and shape optimization method for an existing engineering structure model, and relates to the technical field of topology optimization and shape optimization, and the method comprises the steps: carrying out the mapping through a regular hexahedron unit based on a finite element simulation model of an original engineering structure, and determining an approximate optimization simulation model; based on the approximate optimization simulation model, determining a typical design mode of multi-component non-interference optimization by transforming the state and range of a design domain; based on the typical design mode, the same discrete adjoint equation is adopted to convert the sensitivity of independent or combined application under different sensitivity algorithms, and a compatible unified optimization framework is determined; and determining a variable grouping strategy based on the compatible unified optimization framework so as to uniformly apply various manufacturing process constraints, and obtaining a structure improvement scheme with high manufacturability. The typical design mode is realized by reconstructing the original optimization simulation model, the unified discrete adjoint equation is constructed to realize free combination of different optimization algorithms, and the optimization efficiency and the engineering practicability of multi-component design are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of structural topology optimization and shape optimization, in particular to a direct topology and shape optimization method for an existing engineering structure model. BACKGROUND

[0002] In modern engineering design, topology optimization is mainly used for structure design from scratch, which requires an initial model to have a large enough design space. Therefore, when dealing with an existing engineering structure, a CAD / CAE model needs to be reconstructed to expand the design space, and the modeling process is often cumbersome. Although the free shape optimization method can directly optimize the existing engineering structure, the existing free shape optimization method is prone to grid distortion under large deformation.

[0003] At present, the existing method is to use a single optimization method for structural optimization design. However, single optimization methods such as BESO and SIMP have defects. In actual engineering applications, the ability of a single optimization method is limited when facing complex and variable engineering design situations. Moreover, the existing structural optimization tools require engineers to have rich experience and innovative thinking to establish optimization requirements, and cannot consider the interference of multi-component optimization. The engineering friendliness is poor, the use threshold is high, there is a lack of typical design mode with strong pertinence for the existing engineering structure from multiple perspectives, and it is difficult to rely on a single method to achieve different manufacturing processes, which has a large development difficulty. Therefore, how to more efficiently perform direct topology and shape optimization for an existing engineering structure model has become a problem to be solved.

[0004] The above content is only used to assist in understanding the technical solutions of the present application and does not represent the acknowledgement of the above content as prior art. SUMMARY

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

[0006] To achieve the above purpose, the present application provides a direct topology and shape optimization method for an existing engineering structure model, which comprises: mapping a finite element simulation model based on an original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model; determining a 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 a compatible unified optimization framework by applying sensitivity of independent or combined application under different sensitivity algorithms based on the typical design mode using the same discrete adjoint equation; Determine a variable grouping strategy based on the compatible unified optimization framework to uniformly impose multiple manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability.

[0007] In an embodiment, the finite element simulation model based on the original engineering structure is mapped with regular hexahedral elements, and the step of determining the approximate optimization simulation model comprises: Obtain grid requirement information and boundary adjustment conditions; Based on the average size of the grid in the finite element simulation model based on the original engineering structure, set a size scaling factor to adjust the background grid resolution according to the grid requirement information, and generate hexahedral element grid information; Based on the hexahedral element grid information, map the corresponding irregular elements of the component to be processed to the corresponding regular hexahedral elements for reconstruction, and adjust the boundary adjustment conditions to the regular hexahedral nodes using the nearest node method to obtain the approximate optimization simulation model.

[0008] In an embodiment, the step of determining a typical design mode of multi-component non-interference optimization based on the approximate optimization simulation model by transforming the design domain state and range comprises: Identify the initial design domain based on the approximate optimization simulation model; Transform and adjust the initial design domain 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.

[0009] In an embodiment, the step of determining a compatible unified optimization framework based on the typical design mode using the same discrete adjoint equation to convert the sensitivity applied independently or in combination under different sensitivity algorithms further comprises: Based on the typical design mode, simplify the piecewise constant function of the velocity interpolation function using the same discrete adjoint equation to obtain a compatible unified optimization framework, which 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.

[0010] In an embodiment, after the step of determining a compatible unified optimization framework based on the typical design mode using the same discrete adjoint equation to simplify the piecewise constant function of the velocity interpolation function, the steps further comprise: Obtain unit-level design response parameter information, including volume fraction, compliance, stress, frequency, heat dissipation weakness, and displacement, etc. The mapping relationship between the design variables corresponding to the unit-level design response parameter information and the unit physical properties is analyzed by using a discrete adjoint method, and an analysis result is determined; The same discrete sensitivity is converted into sensitivities of different optimization algorithms by using the analysis result.

[0011] 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 includes: An initial design domain is divided into a main domain and a sub-domain by an approximate optimization simulation model, and a design variable control point of the main domain is mapped to a corresponding sub-domain to form variable grouping information decoupled from a finite element grid; Based on the variable grouping information, a corresponding typical design mode is constrained to obtain a structure improvement scheme with strong manufacturability, and the structure improvement scheme includes plane symmetry, cyclic symmetry, extrusion, mode repetition, and casting constraints.

[0012] 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 includes: When the variable grouping information is that the variable values in the constraint group are equal, the manufacturing process constraint scheme is a plane symmetry, a rotational symmetry, an extrusion, or a periodic repetition structure; When the variable grouping information is that the variables in the constraint group show an increasing or decreasing trend, the constraint structure scheme is a structure that simulates a casting draw direction or an additive manufacturing layer thickness change process restriction structure.

[0013] In addition, to achieve the above object, the application further provides a direct topology and shape optimization device for an existing engineering structure model, which comprises: An acquisition module determines an approximate optimization simulation model based on a regular hexahedral element mapping of a finite element simulation model of an original engineering structure; A processing module is 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; 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; An execution module 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.

[0014] In addition, to achieve the above object, the present application also provides a device for direct topology and shape optimization of an existing engineering structure model, comprising 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 of an existing engineering structure model as described above.

[0015] In addition, to achieve the above object, the present application also provides a storage medium, which 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 method for direct topology and shape optimization of an existing engineering structure model as described above.

[0016] The one or more technical solutions provided by the present application have at least the following technical effects: The method for direct topology and shape optimization of 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; 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 sensitivities under different sensitivity algorithms for independent or combined application 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 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 the boundary of a target design domain, and constructs a unified optimization framework compatible with various optimization methods, so that the sensitivities under different sensitivity algorithms are converted in the framework, the sensitivities under independent or combined application are adjusted, a structure improvement scheme meeting the requirements of actual manufacturing processes is generated, the optimization efficiency is significantly improved, the operation complexity is reduced, and the engineering friendliness and manufacturability of the optimization design are improved. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0019] Figure 1Flowchart provided for the embodiment of the direct topology and shape optimization method for existing engineering structure model of the application; Figure 2 Approximate optimization simulation model reconstruction schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 3 Approximate optimization simulation model adjustment initial design domain schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 4 Constraint typical design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 5 Lightweight design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 6 Local reconstruction design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 7 Endogenous domain global reconstruction design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 8 Exogenous domain global reconstruction design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 9 Additive reinforcement design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application, defining the entire original model as a non-design domain; Figure 10 Local search design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 11 Pure shape optimization design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application; Figure 12 Two-stage collaborative optimization design mode schematic diagram for the direct topology and shape optimization method for existing engineering structure model of the application, topology first and shape second; Figure 13 Flowchart provided for the embodiment of the direct topology and shape optimization method for existing engineering structure model of the application; Figure 14 Brief flowchart schematic diagram of the direct topology and shape optimization method for existing engineering structure model provided by the embodiment of the application; Figure 15 Module structure schematic diagram of the direct topology and shape optimization device for existing engineering structure model of the embodiment of the application; Figure 16 A device structure schematic diagram of a hardware running environment involved in a direct topology and shape optimization method for an existing engineering structure model in an embodiment of the present application.

[0020] The object implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are merely intended to explain the technical solutions of the present application, and are not intended to limit the present application.

[0022] In order to better understand the technical solutions of the present application, the specific embodiments will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] The main solution of the embodiment of the present application is: mapping the finite element simulation model of the original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model; transforming the design domain state and range based on the approximate optimization simulation model to determine a typical design mode of multi-component non-interference optimization; using the same discrete adjoint equation to convert the sensitivity applied independently or in combination under different sensitivity algorithms based on the typical design mode to determine a compatible unified optimization framework; determining a variable grouping strategy based on the compatible unified optimization framework to uniformly apply various manufacturing process constraints to obtain a strong manufacturability structure improvement scheme.

[0024] In the present embodiment, for the sake of description, the following describes an identification direct topology and shape optimization device for an existing engineering structure model as an execution main body.

[0025] Due to 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, engineers need to have rich experience and innovative thinking to establish optimization requirements, the engineering friendliness is poor, the use threshold is high, there is a lack of multi-directional consideration of existing engineering structures, and the design mode is strong in pertinence, and it is difficult to rely on a single method to uniformly implement different manufacturing processes, and the development difficulty is great.

[0026] The present application provides a solution, which maps the finite element simulation model of the original engineering structure with regular hexahedral elements to determine an approximate optimization simulation model; transforms the design domain state and range based on the approximate optimization simulation model to determine a typical design mode of multi-component non-interference optimization; uses the same discrete adjoint equation to convert the sensitivity applied independently or in combination under different sensitivity algorithms based on the typical design mode to determine a compatible unified optimization framework; determines a variable grouping strategy based on the compatible unified optimization framework to uniformly apply various manufacturing process constraints to obtain a strong manufacturability structure improvement scheme.

[0027] From the above embodiments, the application reconstructs the model by the regular hexahedral unit, generates an approximate optimization simulation model, automatically identifies and determines a typical design pattern, adjusts the boundary of the target design domain, constructs a unified optimization framework compatible with multiple optimization methods, thereby converting the sensitivity under different sensitivity algorithms under the framework, realizing the sensitivity adjustment of independent or combined application, generating a structure improvement scheme meeting the actual manufacturing process requirements, significantly improving the optimization efficiency, reducing the operation complexity, and improving the engineering friendliness and manufacturability of the optimization design.

[0028] Based on this, the embodiment of the application provides a direct topology and shape optimization method for an existing engineering structure model, referring to Figure 1 , Figure 1 The flowchart of the first embodiment of the direct topology and shape optimization method for the existing engineering structure model of the application is shown.

[0029] In this embodiment, the direct topology and shape optimization method for the existing engineering structure model comprises steps S10-S50: Step S10, mapping based on the finite element simulation model of the original engineering structure with regular hexahedral units to determine an approximate optimization simulation model; It should be noted that the approximate optimization simulation model is obtained by reconstructing the finite element simulation model of the original engineering structure with regular hexahedral units, and has an expandable design domain boundary.

[0030] It can be understood that the approximate optimization simulation model is obtained by replacing the irregular units of the components to be processed in the finite element simulation model of the original engineering structure with regular hexahedral units, keeping the load, boundary constraints and connection units on the non-optimized region unchanged, and migrating the load, constraints and connection relationships acting on the optimized region to the corresponding regular hexahedral units according to the nearest mapping principle. The design domain boundary of the obtained approximate optimization simulation model has the ability to expand or transform, can be flexibly adjusted according to the optimization requirements, and provides greater design space and flexibility.

[0031] In addition, it should be noted that the finite element simulation model of the original engineering structure is a numerical model based on the actual engineering structure, which is used to simulate the mechanical behavior of the structure under various loads and boundary conditions, and contains a plurality of finite element grids. The finite element grid divides the structure into many small units, each unit has its physical properties, such as material properties, geometric shape, etc. The regular hexahedral unit is a special finite element grid unit, which has a cuboid or cubic geometric shape, compared with irregular units such as tetrahedron, hexahedron, triangular prism, etc. 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 more efficient and occupies less memory, and also facilitates optimization design.

[0032] In specific embodiments, as shown in Figure 2 Figure 2 As an approximate optimization simulation model reconstruction schematic diagram for the direct topology and shape optimization method of the existing engineering structure model of the application, according to the average size of the mesh in the original CAE model, combined with the calculation efficiency and accuracy requirements, the size scaling factor is set to adjust the resolution of the background mesh, so as to generate a regular hexahedral element mesh, using the directed volume method, the original tetrahedron, hexahedron and triangular prism and other irregular elements inside the component to be optimized are replaced by regular hexahedral elements, while the load, boundary constraint and connection element on the non-optimized component are kept unchanged, the load, constraint and connection relationship acting on the component to be optimized are migrated to the corresponding regular hexahedral element according to the nearest mapping principle, so as to obtain an approximate simulation model which can be used to replace the original CAE model for optimization calculation, the approximate optimization simulation model is similar in size, topology and shape to the original finite element simulation model of the engineering structure, and has an expandable or transformable design domain boundary, and by controlling the resolution, different requirements of rapid calculation and precise design in practice can be met.

[0033] In a feasible implementation, step S10 can include steps A11-A13: Step A11, acquiring mesh requirement information and boundary adjustment conditions; It should be noted that the mesh requirement information is a detailed requirement about the mesh determined according to specific engineering requirements and optimization targets when constructing the approximate optimization simulation model, and the boundary adjustment conditions are a series of load, constraint and connection relationship 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.

[0034] It can be understood that the mesh requirement information can include parameters such as the resolution, element type and size scaling factor of the mesh, so as to ensure the calculation efficiency and optimization accuracy of the model, so that the model can better adapt to different engineering requirements and optimization targets, and by setting reasonable mesh requirement information, the efficiency and practicability of optimization design can be significantly improved, and unnecessary waste of computing resources can be reduced. The boundary adjustment conditions can be forces, pressures, torques and the like applied to the structure, or degrees of freedom limiting the displacement of the structure, such as fixed supports, hinges and sliding constraints, etc. In the original model, the boundary adjustment conditions can act on the nodes or element faces of the irregular mesh, and when the model is reconstructed into a regular hexahedral mesh, the original action position will change, therefore, these conditions need to be repositioned to the nodes of the nearest regular hexahedral mesh by the nearest node method to ensure accurate transmission of mechanical behavior.

[0035] ​Step A12, according to the mesh requirement information, set a size scaling factor to adjust the background mesh resolution based on the average size of the mesh in the finite element simulation model of the original engineering structure, and generate hexahedral element mesh information; It should be noted that the hexahedral element mesh information is a collection of regular hexahedral elements formed by replacing irregular elements in the form of regular hexahedral elements.

[0036] It can be understood that the hexahedral element mesh information is generated by setting a size scaling factor and adjusting the background mesh resolution, including the geometric parameters, topological connection relationship 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 regularized mesh structure can be represented by using the hexahedral element mesh information, thereby improving the calculation efficiency and reducing the memory occupation.

[0037] 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 nearest node method is used to adjust the boundary adjustment condition to the regular hexahedral node to obtain an approximate optimization simulation model.

[0038] It can be understood that the directed volume method can be used to map the irregular elements in the original model to the regular hexahedral elements, ensuring that the total volume and shape of the structure are maintained during the replacement process, simplifying the mesh structure, improving the calculation efficiency, and simultaneously migrating the load and constraint, that is, keeping the load, boundary constraint and connection elements on the non-optimized component unchanged, and migrating the load, constraint and connection relationship acting on the optimized component 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 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 and allowing the size and shape of the design domain to be adjusted as needed during the optimization process.

[0039] Step S20, based on the approximate optimization simulation model, transform the design domain state and range to determine a typical design mode of multi-component non-interference optimization; 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.

[0040] It can be understood that the typical design mode can include a lightweight design mode, a local search design mode, a local reconstruction design mode, an additive reinforcement design mode, an exogenous domain global reconstruction design mode, an endogenous domain global reconstruction design mode, a pure shape optimization design mode, and a two-stage collaborative optimization design mode of topology first and shape second, wherein the lightweight design mode is used to reduce the weight of the structure while maintaining or improving its mechanical properties, the local search design mode is a fine optimization adjustment of the local area of the structure, the local reconstruction design mode is a redesign of the local area of the structure to meet specific performance requirements, the additive reinforcement design mode is to enhance the carrying capacity of the specific area of the structure by adding materials, the exogenous domain global reconstruction design mode is to define the main shape or external skeleton of the product structure based on the non-design domain, and to obtain the main force transmission path inside the skeleton through global optimization, the endogenous domain global reconstruction design mode is to take the maximum space covered by the original model initial design domain as the initial design domain of the approximate optimization model, and to perform global reconstruction design, the pure shape optimization design mode is to optimize the shape of the structure to improve its mechanical properties, and the two-stage collaborative optimization design mode of topology first and shape second is to perform topology optimization first and then shape optimization to achieve better design results. The use of the typical design mode provides a variety of choices for optimization design, making the optimization process more flexible to cope with different engineering requirements and design objectives, and improving the efficiency and practicality of optimization design.

[0041] In specific embodiments, as shown in Figure 3 Figure 3 is a schematic diagram of the approximate optimization simulation model adjusting the initial design domain for the direct topology and shape optimization method of the existing engineering structure model. The original engineering structure is analyzed to determine the design domain and the non-design domain, wherein the design domain is the part that needs to be optimized, and the non-design domain is the part that remains unchanged. Therefore, the design domain is operated in the approximate optimization simulation model, that is, if the design space needs to be increased to explore more optimization possibilities, the design domain is expanded, if the optimization range needs to be limited to focus on a specific area, the design domain is limited, and if the original design domain remains unchanged, it is maintained as it is. Through corresponding operations, various initial design configurations can be formed. On this basis, combined with engineering actual requirements and optimization objectives, eight design modes can be proposed, such as lightweight design mode, local search design mode, local reconstruction design mode, additive reinforcement design mode, exogenous domain global reconstruction design mode, endogenous domain global reconstruction design mode, pure shape optimization design mode, and two-stage collaborative optimization design mode of topology first and shape second, thereby obtaining a typical design mode, as shown in Figure 4 Figure 4 ​​The typical design mode constraint diagram for 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 for 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. The design variable points of the slave area are generated by geometric transformation from 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 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 ensure 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. The use of multiple transformation operations ensures 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 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 variation of additive manufacturing process constraints can be simulated, thereby improving the flexibility of optimization design and significantly enhancing the manufacturability of optimization results, making the optimization design better meet the actual engineering requirements.

[0042] Step S30, 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 the compatible unified optimization framework; 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.

[0043] 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.

[0044] 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.

[0045] In a feasible implementation, step S30 can include step B11: 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.

[0046] 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 a 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.

[0047] 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.

[0048] In a feasible implementation manner, after step B11, steps C11-C13 can also be included: 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. 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.

[0049] 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, representing 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.

[0050] 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 an analysis result; 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.

[0051] 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.

[0052] Step C13, converting the same discrete sensitivity to different optimization algorithm sensitivities by using the analysis result.

[0053] 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.

[0054] 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.

[0055] 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.

[0056] 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, thereby realizing 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 structural weight 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 subjected to numerical constraints, so that different size wing parts have similar structural characteristics, ensuring the lightweight effect of the optimized parts, facilitating the unified manufacturing of different size wings, and significantly improving the production efficiency and consistency.

[0057] As Figure 6 shown, Figure 6 is a direct topology and shape optimization method for local reconstruction design mode of existing engineering structure model of the application. The region 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. Local reconstruction design is carried out by using the solid isotropic material penalty method SIMP. In this process, cyclic symmetry constraints need 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 carried out on this basis. The structure performance is optimized by adjusting the material distribution while maintaining the cyclic symmetry, so that the optimization design can effectively optimize the topology of the existing structure and redesign it under the condition of allowing local expansion, thereby improving the performance and efficiency of the structure while meeting the engineering requirements.

[0058] As Figure 7 shown, Figure 7As shown in FIG. 1, the direct topology and shape optimization method for the existing engineering structure model of the application is a schematic diagram of the endogenous domain global reconstruction design mode, the maximum space 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, and the endogenous domain global reconstruction design is performed by using the solid isotropic material penalization method (SIMP).

[0059] As shown in FIG. 2, the direct topology and shape optimization method for the existing engineering structure model of the application is a schematic diagram of the exogenous domain global reconstruction design mode, the maximum space 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, and the exogenous domain global reconstruction design mode is used on this basis. Figure 8 Figure 8 As shown in FIG. 3, the direct topology and shape optimization method for the existing engineering structure model of the application is a schematic diagram of the additive reinforcement design mode, the entire original model is defined as a non-design domain, a certain size of solid material is uniformly expanded on the surface of the model to form an initial design domain, wherein the expansion size is determined according to the performance requirements and optimization objectives of the structure, and the bidirectional evolutionary structure optimization method (BESO) is used to optimize the expanded design domain.

[0060] As shown in FIG. 4, the direct topology and shape optimization method for the existing engineering structure model of the application is a schematic diagram of the additive reinforcement design mode, the entire original model is defined as a non-design domain, a certain size of solid material is uniformly expanded on the surface of the model to form an initial design domain, wherein the expansion size is determined according to the performance requirements and optimization objectives of the structure, and the bidirectional evolutionary structure optimization method (BESO) is used to optimize the expanded design domain. Figure 9 Figure 9 As shown in FIG. 5, the direct topology and shape optimization method for the existing engineering structure model of the application is a schematic diagram of the additive reinforcement design mode, the entire original model is defined as a non-design domain, a certain size of solid material is uniformly expanded on the surface of the model to form an initial design domain, wherein the expansion size is determined according to the performance requirements and optimization objectives of the structure, and the bidirectional evolutionary structure optimization method (BESO) is used to optimize the expanded design domain.

[0061] As shown in FIG. 6, the direct topology and shape optimization method for the existing engineering structure model of the application is a schematic diagram of the additive reinforcement design mode, the entire original model is defined as a non-design domain, a certain size of solid material is uniformly expanded on the surface of the model to form an initial design domain, wherein the expansion size is determined according to the performance requirements and optimization objectives of the structure, and the bidirectional evolutionary structure optimization method (BESO) is used to optimize the expanded design domain. Figure 10 Figure 10 ​​​This 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.

[0062] 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.

[0063] 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.

[0064] In a possible implementation, step S40 can include steps D11-D12: 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; 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.

[0065] 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.

[0066] In addition, it should be noted that the design domain is divided into a main domain and multiple 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 the 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 subject 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.

[0067] 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.

[0068] 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.

[0069] It can be understood that the variable grouping information can be used to divide the design domain into a main domain and multiple 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.

[0070] In a feasible implementation manner, step D12 can include steps E11-E12: 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; 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.

[0071] 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 that simulates the casting draw direction or the layer thickness change of additive manufacturing.

[0072] 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.

[0073] The embodiment provides a direct topology and shape optimization method for an existing engineering structure model. A regular hexahedral element is used to map a finite element simulation model of an original engineering structure to 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 based on the typical design mode. A variable grouping strategy is determined based on the compatible unified optimization framework 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, which simplifies the model structure and improves the calculation efficiency. The design mode is identified and the design domain boundary is adjusted to provide a clear direction and accurate positioning for optimization. A unified framework compatible with various optimization methods is constructed to realize the collaborative application of different sensitivity algorithms, thereby obtaining sensitivity adjustment information. The optimization algorithm is used to accurately adjust the design variables to generate a structure improvement scheme that meets engineering requirements and manufacturing process constraints. The optimization efficiency, adaptability and result accuracy are significantly improved, the operation complexity is reduced, and the engineering practicability is enhanced.

[0074] 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-mentioned embodiment one can refer to the above introduction, and the subsequent will not be described in detail.

[0075] In the embodiment, reference is made to Figure 13 , Figure 13The flowchart provided for the second embodiment of the direct topology and shape optimization method for existing engineering structure model of the present application specifically comprises steps S21-S22: Step S21, identifying the initial design domain based on the approximate optimization simulation model; It should be noted that the initial design domain is the design region 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 optimization design, including all materials and spaces participating in optimization.

[0076] It can be understood that the initial design domain defines the spatial range of optimization design, that is, which part 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.

[0077] 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. According to the extracted information, the spatial range of the initial design domain can be determined in the approximate optimization simulation model, ensuring that the range covers all areas that need to be optimized. The material distribution in the initial design domain is initialized, giving uniform material density or reasonable material distribution setting 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 be used as constraint conditions in the optimization process. At the same time, design variables such as material density and shape parameters are defined in the initial design domain and assigned initial values, thereby accurately identifying the initial design domain.

[0078] Step S22, transforming and adjusting the initial design domain 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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 approximate optimization simulation model is used to identify the initial design domain, and the typical design mode is obtained through expansion, limitation, or maintenance mode adjustment, 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, significantly improve performance, and have good manufacturability, ensuring that the optimization design can be directly applied to actual production, significantly improving the engineering practicability and efficiency of structural optimization design.

[0084] 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: Referring to Embodiment 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 sensitivities 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 multiple manufacturing process constraints to obtain a structure improvement scheme with strong manufacturability. Referring to Embodiment 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, the typical design mode 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. 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, a unified discrete sensitivity analysis method is used for the optimization framework to realize independent application or combined cooperation of the above optimization methods, and in the independent or combined application process of different methods, a variable grouping strategy is introduced to meet actual manufacturing process constraints, and finally a structure improvement scheme with high engineering practical value considering performance improvement and manufacturability is obtained.

[0085] 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.

[0086] 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 includes: An acquisition module 10 is configured to map a regular hexahedral element based on a finite element simulation model of an original engineering structure to determine an approximate optimization simulation model. A 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. The processing module 20 is further configured to convert sensitivities 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. 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.

[0087] The acquisition module 10 is further configured to acquire grid requirement information and boundary adjustment conditions. 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. 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.

[0088] The processing module 20 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 optimization typical design mode, 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.

[0089] 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.

[0090] 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, and displacement. The mapping relationship between the design variables and the unit physical properties corresponding to the unit-level design response parameter information is analyzed by using the discrete adjoint method, and an analysis result is determined. The analysis result is used to convert the same discrete sensitivity to obtain the sensitivity of different optimization algorithms.

[0091] 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. Based on the variable grouping information, the corresponding typical design mode is constrained to obtain a structure improvement scheme with high manufacturability, and the structure improvement scheme includes plane symmetry, cyclic symmetry, extrusion, mode repetition, and casting constraints.

[0092] The execution module 30 is further configured to, when the variable grouping information indicates that the variable values in the constraint group are equal, the manufacturing process constraint scheme is a planar symmetry, a rotational symmetry, an extrusion, or a periodically repeated structure. When the variable grouping information indicates that the variables in the constraint group have an increasing or decreasing trend, the constraint structure scheme is a simulated casting draw direction or an additive manufacturing layer thickness variation process restriction structure.

[0093] The device for directly optimizing topology and shape of an existing engineering structure model provided in the present application adopts the method for directly optimizing topology and shape of an existing engineering structure model in the above embodiment, and can solve the technical problem of how to more efficiently optimize topology and shape of an existing engineering structure model. Compared with the prior art, the device for directly optimizing topology and shape of an existing engineering structure model provided in the present application has the same beneficial effects as the method for directly optimizing topology and shape of an existing engineering structure model provided in the above embodiment, and other technical features of the device for directly optimizing topology and shape of an existing engineering structure model are the same as the features disclosed in the above embodiment, which will not be repeated here.

[0094] The present application provides a device for directly optimizing topology and shape of 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 method for directly optimizing topology and shape of an existing engineering structure model in the above embodiment one.

[0095] Reference will now be made to the drawings, in which Figure 16 which shows a structural schematic diagram of a device for directly optimizing topology and shape of an existing engineering structure model suitable for implementing the embodiments of the present application. The device for directly optimizing topology and shape of an existing engineering structure model in the embodiments of the present application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant), PADs (Portable Application Description), PMPs (Portable Media Player), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 16 The device for directly optimizing topology and shape of an existing engineering structure model shown is only an example, and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0096] As shown in Figure 16 Figure 16 The direct topology and shape optimization apparatus for an existing engineering structure model can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to a program stored in a ROM (Read Only Memory) 1002 or a program loaded from a storage device 1003 into a RAM (Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the direct topology and shape optimization apparatus for an existing engineering structure model are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. In general, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the direct topology and shape optimization apparatus for an existing engineering structure model to communicate wirelessly or wired with other devices to exchange data. Although the direct topology and shape optimization apparatus for an existing engineering structure model having various systems is shown in the figure, it should be understood that all of the shown systems are not required to be implemented or provided. More or less systems can be alternatively implemented or provided.

[0097] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the 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-described functions defined in the methods of embodiments of the present disclosure are performed.

[0098] The device for directly optimizing topology and shape of an existing engineering structure model provided by the application can solve the technical problem of how to more efficiently perform the direct optimization of topology and shape of an existing engineering structure model by using the method for directly optimizing topology and shape of an existing engineering structure model in the above embodiment. Compared with the prior art, the device for directly optimizing topology and shape of an existing engineering structure model provided by the application has the same beneficial effects as the method for directly optimizing topology and shape of an existing engineering structure model provided by the above embodiment, and other technical features of the device for directly optimizing topology and shape of an existing engineering structure model are the same as the features disclosed in the above embodiment, which will not be repeated here.

[0099] It should be understood that various parts of the present application can be realized by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0100] The above describes only 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 by the present application, which should be covered by 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.

[0101] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to perform the method for directly optimizing topology and shape of an existing engineering structure model in the above embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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 in that, The method includes: Based on the finite element simulation model of the original engineering structure, regular hexahedral elements are mapped to determine the approximate optimized simulation model. 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; Based on the typical design pattern, the sensitivity of different sensitivity algorithms is transformed by the same discrete adjoint equation, either independently or in combination, to determine a compatible and unified optimization framework. Based on the aforementioned compatible and unified optimization framework, a variable grouping strategy is determined to uniformly apply various manufacturing process constraints, resulting in a structural improvement scheme with strong manufacturability.

2. The method as described in claim 1, characterized in that, The steps for determining the approximate optimized simulation model based on the finite element simulation model of the original engineering structure by mapping it with regular hexahedral elements include: Obtain grid requirements and boundary adjustment conditions; Based on the average size of the mesh in the finite element simulation model of the original engineering structure, the background mesh resolution is adjusted by setting a size scaling factor according to the mesh requirement information, and hexahedral element mesh information is generated. 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. The nearest node method is used to adjust the boundary adjustment conditions to the regular hexahedral nodes to obtain an approximate optimized simulation model.

3. The method as described in claim 1, characterized in that, The steps for determining typical design patterns for multi-component non-interference optimization based on the approximate optimization simulation model by transforming the design domain state and range include: Identifying the initial design domain based on an approximate optimization simulation model; The initial design domain is transformed and adjusted to obtain typical design patterns for multi-component non-interference optimization. These typical design patterns include subtractive design, local search, local reconstruction, global reconstruction of internal domain, global reconstruction of external domain, reinforcement, shape optimization, and topology-first-shape design.

4. The method as described in claim 1, characterized in that, The step of determining the sensitivity of independent or combined applications under different sensitivity algorithms based on the typical design pattern and using the same discrete adjoint equation to transform the sensitivity, and thus determine the compatible unified optimization framework, further includes: Based on the typical design pattern, the velocity interpolation function is simplified by using a piecewise constant function with the same discrete adjoint equation to obtain a compatible unified optimization framework. The compatible unified optimization framework is used to adapt to the sensitivity characteristics of different optimization algorithms so as to realize the independent or combined application of BESO, SIMP and VFLSM in the optimization process.

5. The method as described in claim 4, characterized in that, After the step of simplifying the velocity interpolation function using a piecewise constant function based on the same discrete adjoint equation according to the typical design pattern to obtain a compatible unified optimization framework, the method further includes: Obtain unit-level design response parameter information, including volume fraction, compliance, stress, frequency, heat dissipation weakness, and displacement, etc. The discrete adjoint method is used to analyze the mapping relationship between the design variables corresponding to the unit-level design response parameter information and the unit physical properties, and the analysis results are determined. The analysis results are used to convert the same discrete sensitivity to obtain the sensitivity of different optimization algorithms.

6. The method as described in claim 1, characterized in that, The steps of determining a variable grouping strategy based on the aforementioned compatible and unified optimization framework to uniformly apply multiple manufacturing process constraints and obtain a structural improvement scheme with strong manufacturability include: The approximate optimization simulation model identifies the initial design domain as a main domain and a subdomain, and maps the design variable control points of the main domain to the corresponding subdomain, forming variable grouping information decoupled from the finite element mesh; Based on the variable grouping information, the corresponding typical design patterns are constrained to obtain a structural improvement scheme with strong manufacturability. The structural improvement scheme includes planar symmetry, cyclic symmetry, extrusion, pattern repetition, and casting constraints.

7. The method as described in claim 6, characterized in that, The step of constraining the corresponding typical design patterns based on the variable grouping information to obtain a structural improvement scheme with high manufacturability includes: When the variable grouping information indicates that the values ​​of variables within the constraint group are equal, the manufacturing process constraint scheme is a planar symmetric, rotationally symmetric, extrusion, or periodically repeating structure. When the variable grouping information indicates that the variables within the constraint group show an increasing or decreasing trend, the constraint structure scheme is a process constraint structure that simulates the draft direction of casting or the layer thickness variation of additive manufacturing.

8. A direct topology and shape optimization device for existing engineering structure models, characterized in that, The device includes: The acquisition module maps the finite element simulation model of the original engineering structure to regular hexahedral elements to determine the approximate optimized simulation model. The processing module is used to determine the typical design pattern of multi-component non-interference optimization by transforming the state and range of the design domain based on the approximate optimization simulation model. The processing module is also used to transform the sensitivity of independent or combined applications under different sensitivity algorithms based on the typical design pattern using the same discrete adjoint equation, and to determine a compatible unified optimization framework. The execution module is used to determine the variable grouping strategy based on the aforementioned compatible unified optimization framework to uniformly apply multiple manufacturing process constraints, thereby obtaining a structural improvement scheme with strong manufacturability.

9. A direct topology and shape optimization device for existing engineering structure models, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the direct topology and shape optimization method for an existing engineering structure model as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the direct topology and shape optimization method for existing engineering structure models as described in any one of claims 1 to 7.

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