Quantifying Model Form Uncertainty in Molecular Dynamics Simulation

Monday, December 16, 2013 - 2:00pm - 2:30pm
Lind 305
Yan Wang (Georgia Institute of Technology)
Molecular dynamics (MD) simulation has been widely used in atomistic modeling of material structure and behavior. As with all modeling and simulation methods, results from MD are susceptible to a variety of uncertainties. A major source of model form and parameter uncertainties in MD is the interatomic potential function. In this study, the effect of parameter uncertainty from interatomic potential functions on MD is investigated and quantified using polynomial chaos expansion, which allows for the efficient calculation of output probability distributions without extensive simulation evaluations. A generalized hidden Markov model based on a generalized interval Bayes’ rule is used for cross-scale model validation where the systematic error in experimental measurement data is incorporated to improve the robustness of assessment.