| Citation: | WEI Juan, ZHANG Jianguo, QIU Taoet al. Structural reliability algorithm based on improved dynamic Kriging model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2): 373-380. doi: 10.13700/j.bh.1001-5965.2018.0301(in Chinese)
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For complex aerospace machinery products, the limit state functions are often implicit and highly nonlinear, and the reliability calculation usually requires time-consuming finite element analysis. In this paper, the particle swarm optimization-simulated annealing (PSOSA) algorithm is applied to the optimization of the correlation parameters of the dynamic Kriging model, which improves the prediction accuracy. At the same time, with the dynamic update mechanism, sample points are gradually added to reduce the number of function callsas much as possible, thereby improving the calculation efficiency. The algorithm is applied to the structural reliability analysis. The Monte Carlo method, response surface and other classic algorithms are compared, and the results of the proposed algorithm are closer to those of Monte Carlo method, and the calculation time is greatly shortened, which shows that the efficiency and accuracy of the algorithm are improved significantly.
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