Abstract
In traditional molecular dynamics (MD) simulations, atoms and coarse-grained particles are modeled as point masses interacting via isotropic potentials. For studies where particle shape plays a vital role, more complex models are required. In this paper we describe a spectrum of approaches for modeling aspherical particles, all of which are now available (some recently) as options within the LAMMPS MD package. Broadly these include two classes of models. In the first, individual particles are aspherical, either via a pairwise anisotropic potential which implicitly assigns a simple geometric shape to each particle, or in a more general way where particles store internal state which can explicitly define a complex geometric shape. In the second class of models, individual particles are simple points or spheres, but rigid body constraints are used to create composite aspherical particles in a variety of complex shapes. We discuss parallel algorithms and associated data structures for both kinds of models, which enable dynamics simulations of aspherical particle systems across a wide range of length and time scales. We also highlight parallel performance and scalability and give a few illustrative examples of aspherical models in different contexts.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 12-24 |
| Number of pages | 13 |
| Journal | Computer Physics Communications |
| Volume | 243 |
| DOIs | |
| State | Published - Oct 2019 |
Funding
We thank Paul Langston for helpful discussion on implementing his aspherical discrete element models. We thank Gary Grest, Dan Bolintineanu, and Ishan Srivastava (Sandia) for careful comments on the manuscript and Dan for producing sub-figures (h, i) of Fig. 1. Likewise we thank Christoph Kloss (DCS Computing) for providing one of the (i) sub-figures in Fig. 1. T.D.N. thanks support from the Vietnam National Foundation for Science and Technology Development (NAFOSTED) under Grant No. 103.01-2015.52. S.J.P acknowledges the Nanoparticle Flow Consortium (NPFC), USA for support. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. This research used resources of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy under Contract DE-AC05-00OR22725. T.D.N. thanks support from the Vietnam National Foundation for Science and Technology Development (NAFOSTED) under Grant No. 103.01-2015.52 . S.J.P acknowledges the Nanoparticle Flow Consortium (NPFC), USA for support. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. This research used resources of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which is supported by the Office of Science of the Department of Energy under Contract DE-AC05-00OR22725 .
Keywords
- Aspherical models
- Discrete element models
- LAMMPS
- Molecular dynamics
- Parallel algorithms
- Rigid body dynamics
ASJC Scopus subject areas
- Hardware and Architecture
- General Physics and Astronomy