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DOE OSTI · 1813660

Nonlocal Operator Learning with Uncertainty Quantification

Abstract

The goal of this work is to develop a Bayesian framework to characterize the uncertainty of material response when using a nonlocal, homogenized model to describe wave propagation through heterogeneous, disordered materials. Our approach is based on an operator regression technique combined with Bayesian optimization, through which the nonlocal kernel for a specific disordered microstructure is investigated.

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BibTeXRIS

Fan, Yiming. 2021-08-17. Nonlocal Operator Learning with Uncertainty Quantification. https://doi.org/10.2172/1813660

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36 MATERIALS SCIENCE↗