An integrated performance measure approach for system reliability analysis

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Authors
Wang, Zequn
Wang, Pingfeng
Advisors
Issue Date
2015-02
Type
Article
Keywords
Polynomial chaos expansion , Design optimization , Bounds
Research Projects
Organizational Units
Journal Issue
Citation
Wang Zequn, Wang Pingfeng. An Integrated Performance Measure Approach for System Reliability Analysis J. Mech. Des. 137(2), 021406 (2015) (11 pages); Paper No: MD-14-1187
Abstract

This paper presents a new adaptive sampling approach based on a novel integrated performance measure approach, referred to as "iPMA," for system reliability assessment with multiple dependent failure events. The developed approach employs Gaussian process (GP) regression to construct surrogate models for each component failure event, thereby enables system reliability estimations directly using Monte Carlo simulation (MCS) based on surrogate models. To adaptively improve the accuracy of the surrogate models for approximating system reliability, an iPM, which envelopes all component level failure events, is developed to identify the most useful sample points iteratively. The developed iPM possesses three important properties. First, it represents exact system level joint failure events. Second, the iPM is mathematically a smooth function " almost everywhere." Third, weights used to reflect the importance of multiple component failure modes can be adaptively learned in the iPM. With the weights updating process, priorities can be adaptively placed on critical failure events during the updating process of surrogate models. Based on the developed iPM with these three properties, the maximum confidence enhancement (MCE) based sequential sampling rule can be adopted to identify the most useful sample points and improve the accuracy of surrogate models iteratively for system reliability approximation. Two case studies are used to demonstrate the effectiveness of system reliability assessment using the developed iPMA methodology.

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Publisher
American Society of Mechanical Engineers
Journal
Book Title
Series
Journal of Mechanical Design;v.137:no.2
PubMed ID
DOI
ISSN
1050-0472
EISSN