AK-SYS-t: New Time-Dependent Reliability Method Based on Kriging Metamodeling
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 4
Abstract
Computing the cumulative failure probability for a given period of time is the main goal of a time-dependent reliability analysis. Estimating this probability is challenging for problems with nonmonotonic performance functions, especially when they are costly to evaluate and have high dimensionality. Discretizing the time interval is one main step in most of the time-dependent reliability methods. Hence, the problem can be converted into a serially connected system reliability problem. Therefore, efficient system reliability methods can be used for time-dependent reliability analysis. AK-SYS (Active learning and Kriging-based SYStem reliability method) is a Kriging-based method for system reliability assessment, including an active learning procedure for the enrichment process. In this paper, we exploit the efficiency of AK-SYS to propose a new time-dependent reliability method that is called AK-SYS-t. Two examples are used to compare the efficiency of the proposed method with competing methods, and a third example is used to highlight the opportunities offered by this method for fatigue reliability analysis. In the end, a crude approach is also proposed to provide the full curve of the cumulative failure probability.
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Data Availability Statement
Due to the fact that this study is a shared work between different partners, the codes and algorithms generated during this study are proprietary or confidential in nature and may only be provided with restrictions.
Acknowledgments
This research has been performed under the INFRASTAR program that has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie Grant Agreement No. 676139. To perform numerical simulations and programming, we have used Open TURNS (Baudin et al. 2015). Also, we would like to show our gratitude to the Reliability and Uncertainty group in PHIMECA Engineering for their invaluable help.
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© 2021 American Society of Civil Engineers.
History
Received: Dec 18, 2020
Accepted: Apr 23, 2021
Published online: Jul 16, 2021
Published in print: Dec 1, 2021
Discussion open until: Dec 16, 2021
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