Modeling uncertainties in molecular dynamics simulations using a stochastic reduced-order basis

HR Wang and J Guilleminot and C Soize, COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 354, 37-55 (2019).

DOI: 10.1016/j.cma.2019.05.020

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. (C) 2019 Elsevier B.V. All rights reserved.

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