Original paper
mfEGRA: Multifidelity efficient global reliability analysis through active learning for failure boundary location
Abstract
This paper develops mfEGRA, a multifidelity active learning method using data-driven adaptively refined surrogates for failure boundary location in reliability analysis. This work addresses the issue of prohibitive cost of reliability analysis using Monte Carlo sampling for expensive-to-evaluate high-fidelity models by using cheaper-to-evaluate approximations of the high-fidelity model. The method builds on the Efficient Global Reliability...
Paper Details
Title
mfEGRA: Multifidelity efficient global reliability analysis through active learning for failure boundary location
Published Date
Apr 23, 2021
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