Structural adaptive optimization design method, device, equipment and medium

Abstract

This application relates to structural self-adaptive optimization design method, device, equipment and medium. The method includes using the Latin hypercube experimental design method to generate an initial sampling point and performing finite element analysis; according to the design variables, a radial basis function is used to construct a surrogate model; The multi-objective genetic algorithm performs multi-objective non-exact search on the multi-objective optimization problem of the surrogate model; performs parallel sampling on each search sample point obtained; calls the finite element analysis simulation model to evaluate the response value of the newly added sampling point, and adds the newly added sampling point and its finite element analysis results are added to the complete set of samples to update the proxy model; adaptively adjust the proportion of development points and exploration points in parallel sampling; Sorting, selecting the previous elite sample point with a higher dominance level as the new sample point elite pool; if the new sample point elite pool meets the requirements, the final optimal design result is output. High processing efficiency.

Description

technical field [0001] The present application relates to the technical field of structural optimization design, in particular to a structure adaptive optimal design method, device, equipment and medium. Background technique [0002] With the gradual improvement of numerical calculation theory and the development of computing power, high-fidelity subject simulation models have been widely used in modern engineering design problems, especially in structural design optimization problems. High-fidelity subject simulation models (such as finite element analysis models and computational fluid dynamics models) can capture complex physical processes of real-world phenomena with high precision, improving the reliability of design results. However, the use of high-fidelity disciplinary simulation models in engineering design problems inevitably brings a huge computational cost, especially in engineering optimization design problems with expensive disciplinary simulation models. [0...

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Problems solved by technology

However, in the process of realizing the present invention, the inventors found that in the aforementioned traditional structural design optimization methods, there is a technical problem of low structural design optimization processing efficiency

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