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Structural and Multidisciplinary Optimization

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01.07.2015 | RESEARCH PAPER

An important boundary sampling method for reliability-based design optimization using kriging model

verfasst von: Zhenzhong Chen, Siping Peng, Xiaoke Li, Haobo Qiu, Huadi Xiong, Liang Gao, Peigen Li

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 1/2015

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Abstract

Reliability-based design optimization (RBDO) combined with metamodel is a powerful tool to deal with variation of system output induced by uncertainties during practical engineering design. In this paper, the importance boundary sampling (IBS) method is proposed to enhance the efficiency of Kriging-model-based RBDO. Rather than fitting all the parts of the limit state constraints precisely within the design region, the proposed IBS mainly selects sample points on the critical parts of the limit state constraints. Two importance coefficients are proposed to identify these critical boundary parts: the first importance coefficient is determined by the objective function value; and the second one is calculated using the joint probability density value of the design variables. The sampling and optimization processes are conducted alternately to select the sample points more rationally. The computation capability of the proposed method is demonstrated using several mathematical RBDO problems and a box girder design application. The comparison results show that the proposed IBS method is very efficient.

Vorheriger Artikel Differential geometry tools for multidisciplinary design optimization, part II: application to QSD

Nächster Artikel Structural topology optimization for maximum linear buckling loads by using a moving iso-surface threshold method

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Titel: An important boundary sampling method for reliability-based design optimization using kriging model
verfasst von: Zhenzhong Chen
Siping Peng
Xiaoke Li
Haobo Qiu
Huadi Xiong
Liang Gao
Peigen Li
Publikationsdatum: 01.07.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 1/2015
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-014-1173-0

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