Informing Missing Physics with Model Form Error and Model Selection

January 26, 2024

DATE: Friday, January 26, 2024
TIME: 3:30 PM
LOCATION: Virtual Zoom Seminar
SPEAKER:

Kathryn Maupin, Senior Member of Technical Staff, Sandia National Laboratories

ABSTRACT:

Despite continuing advances in statistical inversion and modeling, model inadequacy due to model form error remains a concern in all areas of mathematical modeling.Much like physical models, calibrating a discrepancy model requires careful consideration regarding formulation, parameter estimation, and uncertainty quantification, each of which is often problem-specific. At the intersection of model form error quantification and model selection lies a systematic methodology for identifying and characterizing model form error as a means of identifying missing physics or unknown phenomena, which has the potential to inform model development and experimental design. One such methodology is presented. *Sandia National Laboratories is a multi mission laboratory managed and operated by National Technology Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S.Department of Energy’s National Nuclear Security Administration under contractDE-NA0003525.

Bio: Kathryn Maupin is a Senior Member of the Technical Staff at Sandia National Laboratories. Her research focuses on model form error quantification and multi-objective surrogate modeling. Broader research interests include Bayesian methods, model validation, sensitivity analysis, and uncertainty quantification. Kathryn joined Sandia as a postdoc in 2016 and converted to a staff position in 2018. She received her Ph.D. in Computational Sciences,Engineering and Mathematics and her M.S. in Computational and Applied Mathematics from the University of Texas at Austin after completing her B.A. in Applied Mathematics at the University of