Speaker
Description
Friction and lubrication are inherent multiscale problems, particularly when the gap between contacting bodies is on the order of molecular interaction length scales, such as in the boundary lubrication regime. Modelling lubrication across scales beyond purely sequential approaches has so far remained elusive. In this talk, I will present a reformulation of the classical lubrication equations that principally allows straightforward coupling between continuum and molecular models. Concurrency is achieved by informing a surrogate model for the constitutive behavior of highly confined fluids on-the-fly using molecular dynamics (MD) simulations. An active learning scheme based on Gaussian process regression allows data-efficient interpolation of microscopic stresses obtained from MD in possibly high-dimensional parameter spaces. The proposed method is validated for simple fluids before application to more realistic lubricant models.
