|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Computational Methods and Experimental Approaches for Uncertainty Quantification and Propagation, Model Validation, and Stochastic Predictions
||Uncertainty Quantification, Molecular Dynamics, and the Glass-Transition Temperature of Aerospace Polymers
||Andrew Dienstfrey, Paul Patrone
|On-Site Speaker (Planned)
Computer simulations are increasingly being used to inform decision making in both industrial and public policy settings. While this strategy saves time, money, and allows for efficient exploration of alternative scenarios, such use of models and simulations requires that their outputs be carefully assessed for their assumptions and accuracy so as to promote stability and confidence in the decision making process. Uncertainty quantification (UQ) is the field of study providing the foundation for such assessment techniques in scientific computing. In this talk I will present recent results in development of uncertainty quantification applied to estimates of the glass-transition temperature derived from molecular dynamics simulations of aerospace polymers. Elements of this uncertainty analysis---non-linear regression, and analysis of mixed effects---will be familiar to statisticians working in measurement sciences. However, the application of these tools to molecular dynamics "measurements" represents a new avenue for their use.