We are investigating and promoting applications of uncertainty quantification to problems in computational material science. Detailed investigation of promising use cases will lead to creation of guidance and best practices in the use of numerical simulation to inform decision making in the materials development cycle.
Industry and other stakeholders increasingly rely upon simulations to inform their decisions. To make this strategy routine and reliable these simulation results must be accompanied by quantitative statements of their quality. Uncertainty quantification refers to the growing suite of tools situated at the crossroads of statistics, mathematics, numerical analysis, and computational physics that are designed to accomplish this task.
Our work aims to develop technical tools for uncertainty quantification as well as build a larger community of practice within computational materials science. Representative examples are:
Uncertainty Quantification in Molecular Dynamics Simulations
We are developing applications of uncertainty quantification to molecular dynamics simulations of polymer systems of interest to the aerospace industry. This project is currently researching tools to assess the uncertainty of computationally derived measurements of the glass-transition temperature, yield-strain, and radial distribution functions for molecular systems.
Uncertainty Quantification for Finite Element Simulations
The finite element method is a simulation workhorse used throughout industry to solve problems in computational fluid mechanics, structural analysis, electromagnetics, and acoustics to name only a few. We are developing uncertainty quantification analysis techniques based on design of experiments to assess quantitative agreement of finite element solutions of specific, well-characterized benchmark problems. Uncertainty in solutions are characterized with respect to: software platform, element type, degrees of freedom, and element aspect ratio.
Short courses and Conference Presentations