For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo simulation is widely considered to be among the most robust and most generally applicable. The absence of systematic errors and the fact that its error analysis is well-understood are properties that many competing methods lack. A drawback is the often large number of runs needed, particularly in complex models, where each run may entail a finite element analysis or other time consuming procedure. Variance reduction methods may be applied to reduce simulation cost. Reliability Methods for Finite Element Models describes methods to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely-present monotonicity in limit state equations or other prior information. This publication focuses on problems where a highly accurate estimate of the failure probability is required, but an explicit expression for the limit state equation is unavailable and the limit state equation can only be evaluated without loss of accuracy via finite element analysis or some other time consuming process.
Proceedings of the 6th International Conference on Intelligent Traffic and Transportation (ICITT), incorporating the 6th International Conference on Communication and Network Technology (ICCNT), 25 - 27 September 2022, Paris
