|Title||Modeling uncertainties in molecular dynamics simulations using a stochastic reduced-order basis|
|Publication Type||Journal Article|
|Year of Publication||2019|
|Authors||H Wang, J Guilleminot, and C Soize|
|Journal||Computer Methods in Applied Mechanics and Engineering|
|Pagination||37 - 55|
A methodology enabling the robust treatment of model-form uncertainties in molecular dynamics simulations is proposed. The approach consists in properly randomizing a reduced-order basis, obtained by the method of snapshots in the configuration space. A multi-step strategy to identify the hyperparameters in the stochastic reduced-order basis is further introduced. The relevance of the framework is finally demonstrated by characterizing various types of modeling errors associated with molecular dynamics simulations on a graphene sheet. In particular, the ability of the framework to represent uncertainties raised by model reduction and interatomic potential selection is assessed.
|Short Title||Computer Methods in Applied Mechanics and Engineering|