Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions

Many engineering applications are characterized by implicit response functions that are expensive to evaluate and sometimes nonlinear in their behavior, making reliability analysis difficult. This paper develops an efficient reliability analysis method that accurately characterizes the limit state throughout the random variable space. The method begins with a Gaussian process model built from a very small number of samples, and then adaptively chooses where to generate subsequent samples to ensure that the model is accurate in the vicinity of the limit state. The resulting Gaussian process model is then sampled using multimodal adaptive importance sampling to calculate the probability of exceeding (or failing…

• NS
  National Science Foundation
• VU
  Vanderbilt University
• NN
  National Nuclear Security Administration
• DO
  Division of Graduate Education
• SN
  Sandia National Laboratories