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DOE OSTI · 3003145

Uncertainty Quantification for Smooth Functional Data with Application to Material Properties

Williams, Brian J. [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000234654972)·Holland, Troy Michael [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000252558597)·Phillips, Matthew Ryan [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)]
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Abstract

This document outlines a method for processing functional output (i.e., curves) for the ultimate purpose of sampling curves under specified input conditions for use in modeling and simulation uncertainty quantification (UQ) studies. A set of benchmark curves sufficiently representative of the relevant scenario(s) being simulated are provided to the process and formatted as described in Section 1. Principal Component Analysis (PCA) is utilized to discover the components of uncertainty in the benchmark curves and is outlined in Section 2. Section 3 describes the application of uncertainty quantification to the PCA results for the purpose of sampling curves to be used in UQ analysis. Section 4 applies these techniques to an example benchmark dataset. Concluding remarks are provided in the final section.

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36 MATERIALS SCIENCE42 ENGINEERING97 MATHEMATICS AND COMPUTINGfunctional data analysisprincipal component analysisprincipal component regressionstress-strain

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Williams, Brian J. [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000234654972), Holland, Troy Michael [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000252558597), Phillips, Matthew Ryan [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)]. 2025-10-14. Uncertainty Quantification for Smooth Functional Data with Application to Material Properties. https://doi.org/10.2172/3003145

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