Failure Sampling with Optimized Ensemble Approach for Structural Reliability Analysis of Complex Problems
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 1
Abstract
Failure sampling is a structural reliability method based on modified conditional expectation suitable for complex problems for which reliability index–based approaches are inapplicable and simulation is needed. Such problems tend to have nonsmooth limit-state boundaries or are otherwise highly nonlinear. Previous studies recommended implementation of failure sampling with an extrapolation technique using Johnson’s distribution or the generalized lambda distribution. However, what implementation method works best is problem-dependent. The uncertainty of which approach provides best results for a particular problem limits the potential effectiveness of the method. In this study, a solution is proposed to this issue that eliminates this uncertainty. The proposed approach is an optimized ensemble that forms a uniquely weighted solution by utilizing the predictive capability of multiple curves to maximize accuracy for any particular problem. It was found that the proposed approach produces solutions superior to the methods of implementing failure sampling previously presented in the literature.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7 • Issue 1 • March 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: May 22, 2020
Accepted: Aug 14, 2020
Published online: Oct 31, 2020
Published in print: Mar 1, 2021
Discussion open until: Mar 31, 2021
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