Abstract
Second-order reliability methods are commonly used for the computation of reliability, defined as the probability of satisfying an intended function in the presence of uncertainties. These methods can achieve highly accurate reliability predictions owing to a second-order approximation of the limit-state function around the Most Probable Point of failure. Although numerous formulations have been developed, the lack of full-scale comparative studies has led to a dubiety regarding the selection of a suitable method for a specific reliability analysis problem. In this study, the performance of commonly used second-order reliability methods is assessed based on the problem scale, curvatures at the Most Probable Point of failure, first-order reliability index, and limit-state contour. The assessment is based on three performance metrics: capability, accuracy, and robustness. The capability is a measure of the ability of a method to compute feasible probabilities, i.e., probabilities between 0 and 1. The accuracy and robustness are quantified based on the mean and standard deviation of relative errors with respect to exact reliabilities, respectively. This study not only provides a review of classical and novel second-order reliability methods but also gives an insight on the selection of an appropriate reliability method for a given engineering application.
Recommended Citation
Z. Hu et al., "Second-order Reliability Methods: A Review and Comparative Study," Structural and Multidisciplinary Optimization, vol. 64, no. 6, pp. 3233 - 3263, Springer, Dec 2021.
The definitive version is available at https://doi.org/10.1007/s00158-021-03013-y
Department(s)
Mechanical and Aerospace Engineering
Publication Status
Open Access
Keywords and Phrases
Accuracy; Capability; First-order reliability method; Performance metrics; Robustness; Second-order reliability method
International Standard Serial Number (ISSN)
1615-1488; 1615-147X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Dec 2021
Comments
Scania, Grant None