65 results about "Shape optimization" patented technology

A method for training a shape optimization neural network to produce an optimized point cloud defining desired shapes of materials with given properties is provided. The method comprises collecting a subject point cloud including points identified by their initial coordinates and material properties and jointly training a first neural network to iteratively modify a shape boundary by changing coordinates of a set of points in the subject point cloud to maximize an objective function and a second neural network to solve for physical fields by satisfying partial differential equations imposed by physics of the different materials of the subject point cloud having a shape produced by the changed coordinates output by the first neural network. The method also comprises outputting optimized coordinates of the set of points in the subject point cloud, produced by the trained first neural network.

The invention discloses a method for optimizing a metal frame structure of a super-large panel satellite. Relates to the technical field of large metal structure optimization, in particular to the technical field of ultra-large panel satellite metal frame structure optimization. The problem of topological optimization of the whole-satellite metal structure of the large-size flat satellite with wide single-machine mass coverage range and complex working conditions is solved. The method comprises the following steps: S1, establishing a whole satellite finite element model, and setting the side length of a cell; s2, size optimization is carried out to determine the thickness of the structure foundation; s3, topological optimization is carried out to determine the minimum quality constraint; s4, overall index-oriented topological optimization in the overall design area is carried out; s5, topological optimization facing local indexes in the local design area; s6, optimizing the size of the reduced unit; s7, establishing a whole satellite finite element detailed model, and removing rigidity redundancy of the structure; s8, shape optimization is carried out; and S9, verifying the indexes. And a light-weight structural form meeting the structural continuity requirement is obtained by adopting a batch optimization method. The method shortens the satellite structure development period and reduces the structure mass.

The invention discloses a spatial reticulated shell structure shape optimization method based on a genetic algorithm, and relates to the technical field of data processing, and the method comprises the steps: generating a structural force path topological knowledge graph based on node stress feature data, so as to extract feature vectors representing the integrity and coherence of a main bearing path of a structure; determining a key node disturbance sequence by taking the feature vector as input and the integrity and coherence of a main bearing path of the structure as a reward function, carrying out genetic algorithm coding on node coordinates, and obtaining an optimized position of a structure node through population iteration and fitness evaluation; a non-functional force path loss area in the structure is identified, the digital twin model is fed back and updated until the integrity and coherence of the main bearing path of the structure meet an optimization threshold value, and an optimized reticulated shell structure geometric shape is output; according to the method, accurate identification and disturbance optimization of the key nodes of the spatial reticulated shell structure are realized, so that the integrity and coherence of the main bearing path of the structure are remarkably improved.

The invention relates to a node semi-rigid modeling-based complex curved surface reticulated shell multi-objective form optimization method. According to the method, through integration of parametric modeling, numerical simulation and a multi-objective optimization algorithm, efficient optimization design of the irregular boundary free-form surface latticed shell structure is achieved. The control point coordinate matrix of the NURBS curved surface is used for generating a geometric model of the complex curved surface reticulated shell, and high-quality grid division is automatically generated; semi-rigid mechanical behaviors of nodes are simulated through combination of a rigid beam and a spring in a numerical model, semi-rigid characteristics of the nodes are integrated into a rod piece unit, and the mechanical performance of the structure is accurately evaluated; and a non-dominated sorting genetic algorithm is adopted, the minimization of the total strain energy of the structure, the minimization of the total weight of the structure and the maximization of the minimum node configuration degree serve as objective functions, and the multi-objective form optimization design of the complex curved surface reticulated shell is completed. The method is suitable for a single-layer latticed shell structure with any node form and any special-shaped contour boundary, and has wide applicability and good transportability.

The invention belongs to the technical field of material science, and discloses a shape optimization method for a high-temperature alloy disc type pre-forged piece. According to the method, finite element numerical simulation, a support vector machine and a genetic algorithm are combined, a GA-SVR prediction model between an input variable and a target function is established, the optimal value of the target function is predicted, and the optimal geometric parameter combination of the pre-forged piece is obtained. Firstly, the shape of a pre-forged piece is preliminarily designed through experience, then a finite element simulation result is extracted to establish a data set, parameters of a support vector machine model serve as a target function of a genetic algorithm by means of the data set, the parameters of the support vector machine model are optimized by means of the genetic algorithm, and an optimal prediction model is obtained. And for the size parameter combination of the pre-forged piece when the best deformation uniformity evaluation index is obtained, the deformation uniformity of finish forging is effectively improved through global optimization of the genetic algorithm, so that the final performance of the forged piece is improved.

The invention discloses a variant reconstruction AUV (Autonomous Underwater Vehicle) shape optimization method based on proxy-assisted multi-starting-point space reduction. The variant reconstruction AUV shape optimization method comprises the following steps: establishing a parameterized model of a variant reconstruction AUV; constructing a variant reconstruction AUV shape modeling-grid division-performance simulation automation framework, realizing input of design variables, and automatically performing variant reconstruction AUV shape modeling and watershed grid division; a variant reconstruction AUV shape hydrodynamic force simulation calculation framework is built, and assessment of variant reconstruction AUV hydrodynamic force performance is achieved; generating a plurality of groups of initial samples for a design space of design variables, calculating target function values corresponding to the samples by utilizing the simulation automation framework and the simulation calculation framework, and importing the samples and corresponding sailing resistance into a sample library; and performing optimization in the design space of the design variables by utilizing an agent-assisted multi-starting-point space reduction method to obtain an optimal solution of the variant reconstruction AUV shape design problem. According to the method, the reliability of an optimization result and the design efficiency can be improved, and the optimization time is shortened.

The invention belongs to the technical field of road traffic noise reduction, and particularly relates to a sound barrier shape optimization method based on an isogeometric particle swarm singular boundary method. Comprising the steps of building a sound barrier geometric model, building a sound barrier shape optimization model, building a Burton Miller type singular boundary method program, calculating sound pressure, carrying out particle swarm iterative solution, outputting an optimization result and the like. According to the method, the model is optimized based on the isogeometric singular boundary method of the basic solution of the acoustic control equation for the first time, the model is applied to the optimization design of the sound barrier, the sound barrier is optimized by combining the particle swarm optimization method, only the size of the target function is needed, complex sensitivity derivation is not needed, and when the sound barrier with the complex shape is calculated, the method is simple and convenient to operate. The method has great flexibility and high efficiency, seamless integration between CAD and CAE is realized by introducing isogeometric analysis, namely representing geometric boundaries by using an NURBS function, and a tedious grid division step in an optimization process is avoided, so that the precision and efficiency of sound barrier optimization are remarkably improved.

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.

The data-driven non-intrusive shape-topology collaborative optimization method and system disclosed by the present invention relate to the field of structural optimization. First, the present invention uses mesh deformation technology to perform parametric modeling on the structure, and uses shape equations to constrain the displacements of the structure control points, ensuring the regular and smooth shape of the structure after mesh deformation; secondly, the present invention uses a variety of solvers to perform topology optimization on models of different shapes to obtain multi-source topology optimization response data; finally, the present invention establishes a non-intrusive surrogate model between the shape design variables and the topology optimization response data, and obtains a shape-topology collaborative optimization scheme based on the non-intrusive surrogate model. The present invention takes into account the interaction between shape optimization and topology optimization, helps to expand the design space, has higher optimization efficiency and optimization ability compared with other shape-topology optimization methods, and does not require complex sensitivity formula derivation, facilitating its application to practical engineering.

The application discloses a centrifugal pump impeller design method, which comprises the following steps: initial parameter determination; parameterized geometric modeling, wherein the profile lines of the front cover plate and the rear cover plate of the impeller are constructed based on a cubic spline curve, and a blade surface model is generated by controlling point coordinates, a curvature radius and an inlet and outlet angle parameter; manufacturing process coupling design, wherein three-dimensional modeling software is used for parameterized modeling of the impeller, and a cutter kinematics equation of a five-axis machine tool is synchronously introduced; CFD numerical simulation analysis; construction of an artificial neural network; and compound shape reverse optimization. The application solves a three-dimensional RANS equation in a rotating column coordinate system to perform CFD verification, and combines the design strategy of the artificial neural network and the compound shape optimization algorithm to quickly and optimally select an optimal impeller model. The design of the impeller is based on the cubic spline curve to construct an impeller geometric model, and the generative machining technology of the five-axis numerical control machine tool is combined to realize deep cooperation of hydraulic design, three-dimensional modeling and manufacturing process.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes. A method includes: obtaining a design space and design criteria for a modeled object including a design constraint on an acceptable likelihood of failure, wherein a statistical model that relates a structural performance metric to specific likelihoods of failure for material(s) is used to translate between the acceptable likelihood of failure and a value for the structural performance metric; iteratively modifying a generatively designed shape of the modeled object in the design space in accordance with the design criteria including the design constraint to stay under the acceptable likelihood of failure for the physical structure, wherein the numerical simulation includes computing the structural performance metric, which is evaluated against the design constraint; and providing the generatively designed shape of the modeled object for use in manufacturing a physical structure.

A model representing a physical object in a shape optimization according to a design objective, and a control point for altering a shape of the physical object are received. The shape is defined by a set of nodes in the model. Sibling models are generated from the model according to a perturbation scheme. The control point is perturbed with respective perturbed values for the sibling models. Each sibling model contains nodal location changes for the nodes. The nodal location changes are determined based on a respective shape function formulated according to a respective perturbed value at the control point and one or more simulated physical behaviors of the model. The model is updated to have an optimal value for the control point. The optimal value is identified from a relationship according to the design objective. The relationship correlates a physical characteristic of the sibling models to the respective perturbed values.

The present invention discloses a shape space experimental design method for aerodynamic shape optimization, which includes the following steps: Step 1, given the calculation conditions for experimental design, including the number of sampling points in each experimental design matrix, the dimension of design variables, geometric constraint conditions, and the shape parameterization method; Step 2, construct a multi-objective optimization model with the sample point set as the design variable and the number of feasible solutions and the spatial uniformity evaluation index as the objective function; Step 3, use the non-dominated sorting genetic algorithm to iteratively solve the multi-objective optimization model to obtain the optimal experimental design scheme. The method of the present invention considers the uniformity of the distribution of the aerodynamic geometric shapes generated by the sample point set in the shape space and the feasibility of geometric constraints, making the initial sample point set more reasonable, obtaining more comprehensive spatial information, and having a higher quality of the initial surrogate model, thereby improving the efficiency of optimization design and analysis. The present invention is applied to the field of aerodynamic optimization technology for aircraft design.

The present invention utilizes Bayesian optimization and GCN to optimize the shape of a gas turbine turbine disk. The method comprises the following steps: first, parameterizing the gas turbine disk using Bezier curves to determine and construct an optimization space for design variables; second, sampling within the optimization space, using the sample data to establish a geometric model and perform finite element analysis to obtain maximum radial deformation, maximum stress, and mass data, thereby constructing an optimized design database; third, pre-processing each sub-dataset in the database; fourth, constructing a graph convolutional neural network and training it using the data set obtained in step three to obtain a disk prediction model from geometric parameters to displacement and stress field distributions; and fifth, using Bayesian optimization combined with the trained disk prediction model to perform automatic optimization and target optimization to obtain a final optimized design solution for the disk geometry. This invention has significant engineering application benefits and promotional value.

The present application belongs to the technical field of image processing, and specifically relates to a three-dimensional face model automatic generation method, which is characterized by the following specific steps: data loading processing, user model generation based on computer vision, user model grid re-topology, model grid local shape optimization, model grid fusion splicing, and output result model. The grid generation method ensures 2D mapping accuracy according to face key points; the grid deformation and smoothing method makes the user model and the standard face model closer in 3D space under the premise of reasonable deformation, so that the mapping is more accurate; the re-topology model grid local shape optimization utilizes original grid information to correct the grid deformity and improve the quality of the model. The model grid fusion splicing adopts the grid deformation and grid smoothing method, so that the output result meets the design requirements, guarantees the integrity and high quality of the model, and reduces the post-processing work.

A method for suppressing vibration and noise of a bearingless switched reluctance motor. The 12 / 8-pole BSRMWR includes a double salient stator and rotor and an asymmetric half-bridge power converter composed of 12 sets of windings. Due to its body structure and asymmetric power supply method, the motor has relatively large vibration and noise. The shape optimization method is to establish a dynamic optimization model and perform iterative optimization on the BSRMWR motor housing. When the termination condition is met, the finally output motor housing model after iterative optimization is obtained. The modal strain energy of the BSRMWR housing before and after optimization is obtained through finite element modal analysis. The modal strain energy can accurately reflect the change of the actual local force on the motor housing and effectively analyze the stiffness of the motor housing. The present invention takes improving the stiffness of the motor housing as the optimization design goal, the vibration deformation amount of the motor as the design variable, and the mass of the motor housing as the constraint function. The main optimization scheme is to use the shape optimization method to find the optimal rib distribution in the motor housing and compare the vibration and noise waveforms of the motor before and after optimization.

The invention belongs to the technical field of product design, and discloses a shell shape optimization method and device suitable for falling. The method comprises the following steps: establishing a finite element model of a product shell; determining a loading load according to the characteristics of the product; applying the loading load to the finite element model under a plurality of falling working conditions, and performing multi-working-condition falling simulation; calculating a comprehensive strain value of the to-be-optimized region based on the strain value of each damage point obtained by multi-working-condition drop simulation; and optimizing the morphology of the to-be-optimized region by taking the minimum comprehensive strain value as a target. According to the method provided by the embodiment of the invention, the shell morphology of the product is optimized by comprehensively considering multiple falling working conditions and multiple damage points, and the optimized shell structure can meet the requirements of multiple falling working conditions.

This invention belongs to the field of vehicle shape optimization design and discloses a method, system, device, and medium for global optimization design of vehicle aerodynamic shape. The method includes: constructing a parametric model of the vehicle based on free deformation technology; dividing the parametric model into regions and arranging control points in each candidate deformation region; analyzing the drag reduction rate of each candidate deformation region under typical deformation modes to obtain an initial design space; reducing the dimensionality of the design variables in the initial design space using principal component analysis to obtain a dimensionality-reduced design space; constructing a Kriging surrogate model and performing global optimization on the Kriging surrogate model using a genetic algorithm to obtain a preferred region; and applying adjoint optimization to the preferred region to obtain the globally optimal shape design scheme. The technical solution of this invention achieves intelligent and efficient global optimization of complex shapes under given constraints.

Simulation methods and systems are described for topology and shape optimization of a geometrical representation of a physical object being modeled. An initial geometry of the physical object is represented. Equation data representing physical properties for portions of an initial geometry are defined. User inputs are received through a GUI for optimization settings and user selections of portions of the geometry being optimized. For topology optimization, various material properties and solver settings may be defined. For shape optimization, various solver settings and optimization objective may be defined. A discretized model is generated of the physical object. Solutions of the topology or shape optimization are generated and updated values are determined. Iterative operations are then performed for solving the topology or shape optimization objective expressions. The solutions are stored and graphical representations of the solutions may be generated.

The application belongs to the field of composite manufacturing process simulation and optimization design, and particularly relates to a kind of initial shape optimization cutting method of fabric preform based on finite element simulation, parameterized simulation and evaluation model of fabric shape control loading, and the maximum value of the absolute value of the fiber main direction compression strain is output;The polar coordinates of the control points in the simulation and evaluation model are initialized, and the value range of the polar coordinates is determined;Then, based on the design target, set the optimization target, constraint condition of the simulation and evaluation model in Isight software, and select the optimization algorithm to run calculation until the optimal solution is obtained. The optimal solution of the fabric shape corresponding to the minimum fabric forming defect characterization quantity can be obtained through numerical simulation calculation, which avoids repeated trial and error based on a large number of fabric forming physical tests, and can effectively save the process design time and cost;With the fabric shape as the optimization design variable, the material usage can be saved by setting the maximum area constraint of the fabric.

The invention discloses a shape optimization method of a pipeline support structure based on isogeometric analysis, and belongs to the technical field of pipeline shape optimization. The problem that an existing pipeline support structure is poor in vibration reduction performance is solved. The method specifically comprises the following steps: step 1, identifying edge information of a pipeline support from an image containing the pipeline support, extracting a contour line from the edge information, and extracting a contour point from the contour line as a control point; parameterization description is carried out on the coordinates of the control points, and a two-dimensional plane parameterization model of the pipeline support is obtained; 2, taking the abscissa of a control point in the two-dimensional plane parameterized model as a design variable, and establishing a target function according to the design variable; step 3, establishing a shape optimization mathematical model based on the objective function and the system balance equation; and 4, solving the shape optimization mathematical model, and completing the shape optimization of the pipeline support structure according to the abscissa optimization result of each control point. The method can be applied to shape optimization of the pipeline support structure.

The application provides a multi-objective power supply planning method based on Pareto front shape optimization and a related device, including obtaining a multi-objective power supply planning model of a project to be planned, and extracting investment decision variables and operation variables from the multi-objective power supply planning model; continuously optimizing solutions composed of the investment decision variables and the operation variables by using a genetic algorithm until the optimization is stopped after a stop condition is met, and a solution set is obtained; selecting a compromise solution meeting a requirement based on a Pareto front shape of the solution set, so as to determine a final multi-objective power supply planning scheme. The application optimizes the investment decision variables and the operation variables by using the genetic algorithm, minimizes conflict relationships between different objectives, selects a balanced compromise solution, and finally determines the multi-objective power supply planning scheme. The method not only considers uniformity and convergence of the Pareto front, but also particularly focuses on influences of the power supply planning on conflict relationships of operation objectives, and improves accuracy and reliability of decision-making.

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

The invention discloses a structural design method, device and system, relates to the technical field of structural design and is used for designing a characteristic reinforcing structure of a vehicle. The method comprises the steps of obtaining a finite element model of a vehicle and a vehicle body topology model of the vehicle, and based on a preset topology optimization target, performing topology optimization on the vehicle body topology model by using the finite element model so as to adjust density distribution of each section structure in the vehicle body topology model, and obtaining an initial characteristic reinforcing structure of the vehicle, and then, based on a preset shape optimization target, free shape optimization is carried out on the initial characteristic reinforcing structure so as to adjust the shape distribution of each section of reinforcing piece in the initial characteristic reinforcing structure, and a target characteristic reinforcing structure of the vehicle is obtained. According to the method, topological optimization, free shape optimization and preset optimization indexes can be combined to determine the characteristic reinforcing structure meeting the specific characteristic requirements of the vehicle, and the characteristic reinforcing structure has better material distribution and structural shape, so that the performance of the vehicle on specified characteristics can be improved.

The application discloses a kind of optimization method of battery pack fixing point quantity and position, comprising: the finite element model of body-in-white and battery pack is built;According to the finite element model of body-in-white, the basic stiffness of body-in-white is analyzed;In the finite element model of body-in-white, battery pack fixing point is arranged in high-density mode;Different stiffness index constraints are set, a group of parameter optimization is run, the optimal key fixing point quantity and optimal initial position are determined;According to the optimization result of optimal key fixing point quantity and optimal initial position, non-key fixing point is deleted, the position variable of key fixing point is set, and the shape optimization of the position of key fixing point is carried out.The optimization method of battery pack fixing point quantity and position of the application finds out the optimal quantity and position of battery pack fixing point for the performance target of battery pack, automatically realizes optimization to the quantity and position of battery pack fixing point, and reduces the workload of manual.

The invention discloses a real-time ball target detection method and system based on artificial intelligence. The method comprises the steps of initial detection of a ball target, bounding box zooming, ball adaptive matching degree enhancement, ball credibility index enhancement, ball motion orbit diameter repair, motion orbit diameter smoothing and output of a real-time detection result. The invention belongs to the field of target detection, and particularly relates to a real-time ball target detection method and system based on artificial intelligence. According to the scheme, scaling factors are dynamically adjusted based on credible indexes, direction sensitive scaling is introduced, and insufficient scaling in the high-speed motion direction is avoided; reducing matching failures during rate mutation based on dynamic scaling distance enhancement; shape misjudgment caused by insufficient pixels is reduced based on micro weighted shape optimization; introducing previous three frames of historical credible exponential attenuation items, and filtering instantaneous noise by using historical trajectory continuity; and focusing candidate matching based on the survivability and carrying out rate enhancement fusion, thereby improving the ball target detection effect.

The invention relates to a discrete element stratigraphic model mesoscopic parameter calibration method and system, a medium and equipment, and the method comprises the following steps: employing an intrinsic specific energy calculation method to calculate an average cutting force, and obtaining first data; calculating an average cutting force by adopting a discrete element simulation method to obtain second data; performing error calculation based on the first data and the second data to obtain an error result; and according to an error result, adjusting the initial value of each mesoscopic parameter until an error range is met, and completing parameter calibration. According to the method, the stratum mesoscopic parameters required by the discrete element rock breaking model can be efficiently deduced and obtained according to the cutting force, accurate stratum parameters are provided for subsequent influence factor analysis, tooth profile optimization and other simulation, and the model accuracy is guaranteed.

The application discloses a kind of suitable for six-roller cold continuous rolling mill non-oriented silicon steel transverse thickness difference control method, belong to cold-rolled plate rolling technical field.The method includes: design optimization six-roller cold continuous rolling mill S1-S3 rack's edge drop control work roll new roll shape curve;Build cold continuous rolling mill finite element simulation model and verify;Through finite element model simulation analysis edge drop control work roll shape under the influence law of rolling process parameters to transverse thickness difference;With the shape control characteristics of edge drop control work roll shape, propose six-roller cold continuous rolling mill work roll and intermediate roll bending force control strategy.The application can effectively reduce non-oriented silicon steel transverse thickness difference by work roll shape optimization and bending force collaborative control, improve cold-rolled silicon steel product quality and production stability, suitable for six-roller cold continuous rolling mill non-oriented silicon steel batch production.

The application relates to an acoustic metamaterial with a frequency-doubling filtering characteristic and a shape optimization method thereof, the optimization method comprising the following steps: constructing a two-dimensional finite element simulation model, the two-dimensional finite element simulation model comprising a main plate, a thin adhesive layer and an acoustic metamaterial, the acoustic metamaterial having an initial structure, the initial structure being periodically arranged by an initial unit cell structure, and a free-shape boundary being arranged in the initial structure; constructing an optimization model according to a target that a fundamental frequency is a passband and a frequency double is a stopband; adjusting the free-shape boundary on the basis of the initial structure by using a moving asymptote method; and calculating to obtain an optimal structure of the acoustic metamaterial. Compared with the prior art, the application not only ensures that the optimization target can be achieved, but also reduces the complexity of the structure, facilitates processing and manufacturing, and the designed acoustic metamaterial has the frequency-doubling filtering characteristic, and can effectively filter the inevitable system nonlinearity in nonlinear ultrasonic Lamb wave detection.

The invention relates to the technical field of new energy vehicles, in particular to a design method and system for an energy system bracket structure of a new energy vehicle. According to the scheme, firstly, a CAE finite element model is created according to an initial CAD geometric model of a bracket structure, topological optimization analysis based on machine learning is carried out to determine a reinforcing rib structure of the CAD geometric model, and a new CAD geometric model is formed; then, a refined CAE finite element model is created, and size and shape optimization analysis based on machine learning is carried out, so that size and shape optimization of the bracket structure is achieved; and finally, according to the optimized bracket structure, reconstructing a CAE finite element model and then performing safety working condition checking, when checking succeeds, determining that the size and shape optimization scheme is an optimal combination scheme, and if checking fails, performing size and shape optimization analysis again until requirements are met. By adopting the scheme provided by the invention, an optimization result can be obtained more accurately and quickly, and the mass of the structure can be reduced quickly and accurately to the greatest extent.