Eduardo Corona, Assistant Professor of Mathematics, New York Institute of Technology

Fast computational frameworks for particulate media simulation

Granular media and “wet” particle suspensions are two important models of soft matter. They are crucial to the study of soil mechanics, biological media self-assembly and smart material design. In this talk, we present general computational frameworks for the simulation of dense particulate soft matter in 3D featuring boundary integral formulations for long-range particle interactions, singular integral evaluation schemes and optimization-based collision resolution.

As algorithmic and learning frameworks continue to improve, addressing large data-set storage and management problems is imperative. Large-scale simulations can quickly generate a lot of data: particle positions, velocities and pairwise contact forces for one run can easily require GBs to TBs of memory. We present a streaming data compression scheme based on the tensor train decomposition that allows us to build a compressed version of the full data-set that can be quickly accessed and operated with in limited computing environments.