Reliability Assessment Based on the Concept of Failure Surface Frontier Available to Purchase

This work proposes a novel concept of failure surface frontier (FSF), which is a hyper-surface consisting of the set of the non-dominated failure points on the limit states of a given failure region. FSF better represents the limit state functions for reliability assessment than conventional linear or quadratic approximations on the most probable point (MPP). Assumptions, definitions, and benefits of FSF are discussed first in detail. Then, a discriminative sampling based algorithm was proposed to identify FSF, from which reliability is assessed. Test results on well known problems show that reliability can be accurately estimated with high efficiency. The algorithm is also effective for problems of multiple failure regions, multiple most probable points (MPP), or failure regions of extremely small probability.