A Hybrid Algorithm Combining Kriging Model and Importance Sampling for Structural Reliability Analysis

DOI

10.2991/acaai-18.2018.48How to use a DOI?

Keywords

probability of failure; Kriging model; Importance Sampling; augmented failure probability; correction term

Abstract

One primary goal of structural reliability analysis aims at computing the probability of failure of a component or system with respect to some prescribed performance functions. In modern engineering, most performance functions usually resort to running an expensive-to-evaluate computational model, which leads to the infeasibility of simulation involving 103~6 runs. Surrogate models, such as response surfaces approach or Kriging are introduced as a substitute for the original model to cope with the computational cost. However, the analysis based only on the surrogate model fails to quantify the error made by this substitution. In addition, the existing variance technique in simulation is still less efficient in terms of complex computational model. Therefore, a hybrid algorithm combing Kriging surrogate model and importance sampling for structural reliability analysis is proposed to calculate the failure probability. The applications in several reliability problems proves the approach efficient, robust and accurate.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Juan Wang
AU  - Yizhong Ma
PY  - 2018/03
DA  - 2018/03
TI  - A Hybrid Algorithm Combining Kriging Model and Importance Sampling for Structural Reliability Analysis
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 205
EP  - 208
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.48
DO  - 10.2991/acaai-18.2018.48
ID  - Wang2018/03
ER  -