Journal
STRUCTURAL SAFETY
Volume 33, Issue 6, Pages 343-353Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.strusafe.2011.06.001
Keywords
Reliability; Subset simulation; Support Vector Machine; Active learning
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Funding
- French National Agency of Research (ANR)
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Estimating small probabilities of failure remains quite a challenging task in structural reliability when models are computationally demanding. FORM/SORM are very suitable solutions when applicable but, due to their inherent assumptions, they sometimes lead to incorrect results for problems involving for instance multiple design points and/or nonsmooth failure domains. Recourse to simulation methods could therefore be the only viable solution for these kinds of problems. However, a major shortcoming of simulation methods is that they require a large number of calls to the structural model, which may be prohibitive for industrial applications. This paper presents a new approach for estimating small failure probabilities by considering subset simulation proposed by S.-K. Au and J. Beck from the point of view of Support Vector Machine (SVM) classification. This approach referred as (2)SMART (Two SMART') is detailed and its efficiency, accuracy and robustness are assessed on three representative examples. A specific attention is paid to series system reliability and problems involving moderately large numbers of random variables. (C) 2011 Elsevier Ltd. All rights reserved.
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