A Computational Study of the Buffered Failure Probability in Reliability-Based Design Optimization

The buffered failure probability is an alternative measure of reliability that offers several theoretical, practical, and computational advantages over the traditional failure probability. It is handled with relative ease in design optimization problems, accounts for the degree of violation of a performance threshold, and is more conservative than the failure probability. This paper examines the difference between the buffered failure probability and the failure probability in several examples and find that the buffered failure probability typically overestimates the failure probability of a structure with a factor of three. We examine the use of the buffered failure probability in reliability-based optimal design and present three algorithms for the solution of the resulting optimization problems. Computational results on six engineering design examples indicate that the problems are solvable in few seconds using standard optimization solvers.