期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 143, 期 -, 页码 -出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.106836
关键词
Dynamical systems; Global structural optimization; Kriging approximation; Markov sampling method; Reliability-based design; Stochastic excitation
资金
- CONICYT (National Commission for Scientific and Technological Research) [1180271]
- CONICYT under CONICYTPFCHA/Doctorado Acuerdo Bilateral DAAD Becas Chile [2018-62180007]
- DAAD under CONICYTPFCHA/Doctorado Acuerdo Bilateral DAAD Becas Chile [2018-62180007]
- PAC (Programa Asistente Cientifico 2017)-UTFSM program
The reliability-based design of structural dynamic systems under stochastic excitation is presented. The design problem is formulated in terms of the global minimization of the system failure probability. The corresponding optimization problem is solved by an effective stochastic simulation scheme based on the transitional Markov chain Monte Carlo method. Although the scheme is quite general, is computationally very demanding due to the large number of reliability analyses required during the design process. To cope with this difficulty, an advanced simulation technique is combined with an adaptive surrogate model for estimating the failure probabilities. In particular, a kriging meta-model is selected in the present formulation. The algorithm generates a set of nearly optimal solutions uniformly distributed over a neighborhood of the optimal solution set. Such set can be used for exploration of the global sensitivity of the system reliability. Several illustrative examples are presented to investigate the applicability and effectiveness of the proposed design scheme. (C) 2020 Elsevier Ltd. All rights reserved.
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