18 December 2019

14:15 - 14:30

Gathering and welcome

14:30 - 15:00

Martin Berzins (University of Utah): Applying MPM to Continuum Multi-scale. Modeling of Batteries: Fundamentals and Applications
The practical and theoretical aspects of the application of the Material Point.
Method to modeling aspects of the performance of batteries is considered.
After a discussion of the background and the physical models. The MPM approach is applied to models of deformation of silicon anodes and at the same time its fundamental properties considered with regard to timestepping, stability and energy conservation. The approach will be shown to provide accurate models of the massive deformation of silicon anodes during lithiation.

15:00 - 15:30

Charles Augarde (Durham University): Developments in implicit MPMs.
The Material Point Method is most commonly used in an explicit framework and applied to time-dependent problems. An implicit framework allows one to model large deformation, quasi-static problems making using existing finite element components such as constitutive models, and as such it is particularly of use for geotechnical problems. There are other advantages but it is less well-known and understood. This brief talk will cover recent selected developments in implicit MPMs from the computational mechanics research cluster at Durham University's Department of Engineering.

15:30 - 16:00

Anna Pandolfi (Politecnico di Milano): Meshfree schemes for advection-diffusion problems derived from Optimal Transportation Theory: I will present a particle method for advection-diffusion problems based on the Optimal Transport Method (OTM), where the density of the diffusive species is approximated by Dirac measures. In alternative to traditional schemes formulated in linear spaces, relying on the optimal transport theory the method hybridizes elements of a Galerkin approximation with those of an updated Lagrangian approach. The time discretization of the diffusive step is based on the Jordan-Kinderlehrer-Otto (JKO) variational principle. The JKO functional characterizes the evolution of the density as a competition between the Wasserstein distance (which penalizes departures from the initial conditions) and entropy (which tends to spread the density