Parallelization, Acceleration, and Advancement of Dissipative Particle Dynamics (DPD) Methods
Authors: Timothy I. Mattox (Engility Corporation), James P. Larentzos (Engility Corporation), Christopher P. Stone (Computational Science and Engineering, LLC), Sean Ziegeler (Engility Corporation), John K. Brennan (U.S. Army Research Laboratory), Martin Lísal (Institute of Chemical Process Fundamentals of the Academy of Sciences of the Czech Republic and J. E. Purkyne University)
Best Poster Finalist
Abstract: Our group has developed micro- and mesoscale modeling capabilities necessary to represent salient physical and chemical features of material microstructure. We built novel simulation tools that incorporate coarse-grain (CG) models upscaled from quantum-based models, which are then coupled with continuum level approaches. We further developed a suite of discrete-particle modeling tools, based upon the Dissipative Particle Dynamics (DPD) method, for simulation of materials at isothermal, isobaric, isoenergetic, and isoenthalpic conditions. In addition to the ability to simulate at those various conditions, our method has a particularly unique capability to model chemical reactivity within the CG particles of the DPD simulation. We recently integrated these methods into LAMMPS, enabling the utilization of HPC resources to model many DoD-relevant materials at previously impractical time and spatial scales for unprecedented simulations of phenomena not previously possible. Our poster presents the parallelization, acceleration, and advancement of these DPD methods within the LAMMPS code.
Two-page extended abstract: pdf