An Integrated Design Method for Composite Material Pipe Winding Parameters Based on Proxy Model and Multi-Objective Optimization

By adopting a design method based on surrogate models and multi-objective optimization, the problems of low computational efficiency and multi-objective conflict in the design of composite pipe winding parameters are solved, achieving efficient and scientific winding parameter optimization and providing excellent design solutions among multiple performance parameters.

CN122133458APending Publication Date: 2026-06-02SHAANXI UNIV OF SCI & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHAANXI UNIV OF SCI & TECH
Filing Date
2026-02-06
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing technologies suffer from low computational efficiency, difficulty in handling multi-objective conflicts, and lack of objective decision support in the design of composite material pipe winding parameters, resulting in long design cycles and unreasonable solutions.

Method used

A design method based on surrogate model and multi-objective optimization is adopted. Through parametric finite element modeling, Kriging surrogate model and NSGA-II algorithm, combined with entropy weight-TOPSIS decision, automated winding parameter optimization is achieved.

Benefits of technology

It significantly improves design efficiency, shortens the cycle to hours, provides high-precision and reliable multi-objective optimization solutions, eliminates human subjective factors, and ensures the scientific nature and reliability of the solution.

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Abstract

This invention belongs to the field of composite material structure optimization design technology, and discloses an integrated design method for composite material pipe winding parameters based on surrogate models and multi-objective optimization. The steps include: First, through parametric modeling and automated finite element simulation, a rapid mapping from design variables to performance responses is achieved; second, samples are generated based on optimal Latin hypercube sampling, and a high-precision Kriging surrogate model is constructed to replace time-consuming high-fidelity simulation; third, using the surrogate model as an evaluation tool, the NSGA-II multi-objective genetic algorithm is used for optimization, obtaining a series of Pareto optimal solution sets that achieve the best trade-off among multiple performance objectives; finally, the entropy weight method is used to objectively calculate the weights of each performance index, and the TOPSIS method is combined to make a comprehensive decision on the Pareto solution set, selecting the final optimal parameter combination. This achieves efficient, high-precision, and automated multi-objective optimization design of composite material pipe winding parameters, and ensures the comprehensive optimality and objectivity of the design scheme.
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