期刊
PROBABILISTIC ENGINEERING MECHANICS
卷 41, 期 -, 页码 89-103出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.probengmech.2015.06.006
关键词
MCMC; Subset Simulation; Reliability analysis; High dimensions; Conditional sampling; Adaptive scaling
资金
- Institute for Advanced Study of the Technische Universitat Munchen - German Excellence Initiative
Subset Simulation is an adaptive simulation method that efficiently solves structural reliability problems with many random variables. The method requires sampling from conditional distributions, which is achieved through Markov Chain Monte Carlo (MCMC) algorithms. This paper discusses different MCMC algorithms proposed for Subset Simulation and introduces a novel approach for MCMC sampling in the standard normal space. Two variants of the algorithm are proposed: a basic variant, which is simpler than existing algorithms with equal accuracy and efficiency, and a more efficient variant with adaptive scaling, It is demonstrated that the proposed algorithm improves the accuracy of Subset Simulation, without the need for additional model evaluations. (C) 2015 Elsevier Ltd. All rights reserved.
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