Uncertainty Quantification with Thoughts on Multiscale Materials Applications
Laura P. Swiler, Distinguished Member of Technical Staff
Optimization and Uncertainty Quantification Department
Sandia National Laboratories
The talk will emphasize benefits, challenges, and appropriate use cases for various uncertianty quanification (UQ) approaches. Particular topics presented will include polynomial chaos expansions, dimension reduction and active subspace approaches, multi-level Monte Carlo methods, Bayesian calibration, and coupled methods as well as applications to materials problems and multi-scale materials applications.
Dr. Laura P. Swiler is a Distinguished Member of the Technical Staff in the Optimization and Uncertainty Quantification Department at Sandia National Laboratories. She has twenty-two years of experience in reliability and risk assessment. Laura started her career at Sandia working in reliability analysis, for weapons applications and nuclear waste repository assessment. For the past fourteen years, Laura has focused on sensitivity analysis, model validation, and uncertainty quantification. Some of Laura’s research interests include: sensitivity analysis for high-dimensional inputs, model validation incorporating both experimental and simulation uncertainty, use of surrogate or meta-models for optimization and extrapolation, calibration of model parameters in the presence of both experimental and model uncertainty, and use of non-probabilistic techniques to model epistemic uncertainty.