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基于粒子群-AK-MCS法的结构可靠性分析

Structural reliability analysis based on particle swarm optimization AK-MCS method
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摘要 Kriging代理模型由于其良好的非线性拟合能力,在可靠性分析领域得到了广泛的应用。为提高Kriging模型的建模效率,本文提出一种混合粒子群算法的AK-MCS法,该方法在保证模型精度的前提下减少了构建代理模型时的迭代次数,且提高了模型的全局寻优能力。以一10杆桁架结构为研究对象,通过建立结构控制位移与杆件截面面积和集中荷载之间的代理模型,快速求解桁架结构的失效概率。研究表明,本文方法有效提高了Kriging模型建模效率和建模精度,在计算复杂工程结构时具有一定的可行性。 A Kriging surrogate model has been widely used in reliability analysis due to its favourable nonlinear fitting ability.In order to improve the modeling efficiency of a Kriging model,a hybrid particle swarm optimization AK-MCS method is proposed in this paper.The method reduces the number of iterations of the surrogate model construction and improves the global optimization capability of the model while ensuring the model accuracy.Taking a 10-bar truss structure as the research object,the failure probability of the truss structure was determined quickly by establishing the proxy model between the control displacement of the structure,the section area of the rod and the concentrated load.The results show that the proposed method can effectively improve the modeling efficiency and accuracy of a Kriging model,and is feasible in the calculation of complex engineering structures.
作者 姜封国 于正 白丽丽 周玉明 JIANG Feng-guo;YU Zheng;BAI Li-li;ZHOU Yu-ming(School of Civil Engineering,Heilongjiang University of Science and Technology,Harbin 150027,China;College of Aerospace and Civil Engineering,Harbin Engineering University,Harbin 150001,China)
出处 《计算力学学报》 CAS CSCD 北大核心 2023年第6期872-878,共7页 Chinese Journal of Computational Mechanics
基金 国家自然科学基金面上项目(11872157) 黑龙江省省属本科高校基本科研业务费项目(2020-KYYWF-0707) 黑龙江省自然科学基金(LH2022E108)资助。
关键词 代理模型 失效概率 粒子群 桁架结构 可靠性分析 surrogate model failure probability particle swarm optimization trusswork reliability analysis
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