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Stochastic structural optimization using particle swarm optimization, surrogate models and Bayesian statistics 总被引:4,自引:4,他引:0
This paper focuses on a method to solve structural optimization problems using particle swarm optimization (PSO), surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method (RSM) and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem. 相似文献
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从联结翼多学科优化要求出发,重点对并行子空间设计算法进行了改进.采用Pareto遗传算法作为系统级搜索策略,结构子学科优化则采用模拟退火算法.并在此基础上应用了旨在提高优化计算效率的响应面方法.实现了基于改进型并行子空间设计算法对气动、结构及隐身多目标函数间的折中与优化. 相似文献
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The reliability based optimization (RBO) issue of composite laminates trader fundamental frequency constraint is studied. Considering the tmcertainties of material properties, the frequency constraint reliability of the structure is evaluated by the combination of response surface method (RSM) and finite element method. An optimization algorithm is developed based on the mechanism of laminate frequency characteristics, to optimize the laminate in terms of the ply amount and orientation angles. Numerical examples of composite laminates and cylindrical shell illustrate the advantages of the present optimization algorithm on the efficiency and applicability respects. The optimal solutions of RBO are obviously different from the deterministic optimization results, and the necessity of considering material property uncertainties in the composite structural frequency constraint optimization is revealed. 相似文献
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