Recent Extensions of Dissipative Particle Dynamics Methods and Application to Hierarchical Multiscale Simulation

The concept of multiscale-modeling in support of next-generation materials design impact many classes of microstructure-dependent materials, including biomolecules, polymers, energy-storage materials and energetic materials. In recent years, our group has developed micro- and mesoscale modeling capabilities necessary to represent salient physical and chemical features of material microstructure. In particular, we have built a suite of discrete-particle modeling tools, based upon the DPD method 12, for various conditions, including isothermal, isobaric, isoenergetic, and isoenthalpic conditions. A particularly unique aspect of this simulation capability is a microscale description of chemical reactivity 3. In the first part of this talk, we discuss the suite of DPD variants that have been recently integrated into the massively-parallel LAMMPS software package for use on HPC platforms.

In the second part of this talk, we present work on a challenge in continuum-scale modeling: the direct incorporation of complex physical processes in the constitutive evaluation. We use an adaptive hierarchical multi-scale (HMS) framework running in parallel on a heterogeneous computational environment to couple a fine-scale, particle-based model computing the equation of state (EOS) to the constitutive response in a finite-element multi-physics simulation. The EOS is obtained from high-fidelity materials simulations performed via dissipative particle dynamics methods. This HMS framework is progress towards an innovation infrastructure that will be of great utility for systems in which essential aspects of the material response are too complex to capture by closed form material models. The design, implementation, and performance of the HMS framework are discussed. The LAMMPS-python interface is critical to this design, and its usage is discussed. Also presented is a proof-of-concept Taylor anvil impact test of non-reacting 1,3,5-trinitroperhydro-1,3,5-triazine (RDX).

1 M. Lísal, J.K. Brennan, and J.B. Avalos, J. Chem. Phys., 135, 204105 (2011).

2 J.P. Larentzos, J.K. Brennan, J.D. Moore, M. Lísal, and W.D. Mattson, Comput. Phys. Commun., 185, 1987-1998 (2014).

3 J.K. Brennan, M. Lísal, J.D. Moore, S. Izvekov, I.V. Schweigert, and J.P. Larentzos, J. Phys. Chem. Lett., 5, 2144 (2014).