Failure Sampling with Optimized Ensemble Approach for the Structural Reliability Analysis of Complex Problems
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 non-smooth 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.
Civil Engineering | Structural Engineering
Eamon, C., Patki, K., and Alsendi, A. 2021. “Failure sampling with optimized ensemble approach for the structural reliability analysis of complex problems.” J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng. 7 (1): 04020050. https://doi.org/10.1061/AJRUA6.0001100.
This is the Final Draft version, submitted to ASCE after peer review and prior to copyediting or other ASCE production activities, of an article appearing in the Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/full/10.1061/AJRUA6.0001100.