In this paper, we investigate the effect of particle number, or system size, on three-dimensional (3D) particle dynamic simulation results. Specifically, we simulate conditions with varying e (coefficient of restitution) and φ (solids volume fraction), containing particle numbers ranging from 250 to 300 000. Various algorithmic improvements are implemented in the simulation to efficiently handle these large numbers of particles. We observe, for the first time for 3D simulations, particle-phase microstructure formation at high coefficients of restitution. Furthermore, we show the onset of the particle-phase microstructure formation at various threshold system sizes, depending on the value of e and φ, and relate it to an increase in particle-phase stress. Visual observations are used to conduct a preliminary investigation of the nature of the microstructure formation. Multiple well-defined bands are observed for simulations of at least 100 000 particles.
The general atomic and molecular electronic structure system (GAMESS) is a quantum chemistry package used in the first-principles modeling of complex molecular systems using density functional theory (DFT) as well as a number of other post-Hartree-Fock methods. Both DFT and time-dependent DFT (TDDFT) are of particular interest to the materials modeling community. Millions of CPU hours per year are expended by GAMESS calculations on high-performance computing systems; any substantial reduction in the time-to-solution for these calculations represents a significant saving in CPU hours. As part of this work, three areas for improvement were identified: (1) the exchange-correlation (XC) integration grid, (2) profiling and optimization of the DFT code, and (3) TDDFT parallelization. We summarize the work performed in these task areas and present the resulting performance improvement. These software enhancements are available in 12JAN2009R3 or later versions of GAMESS.
The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) is employed in the first-principles modeling of complex molecular systems by using the density functional theory (DFT) as well as a number of other post-Hartree-Fock (HF) methods. Both DFT and time-dependent DFT (TDDFT) are of particular interest to the Department of Defense (DoD) Computational Biology, Chemistry, and Materials Science (CCM). Millions of CPU hours peryear are expended by GAMESS calculations on DoD high performance computing (HPC) systems. Therefore, any reduction in wall-clock time for these calculations will represent a significant saving in CPU hours. As part of this work, three areas for improvement were identified: 1) replacement of the exchange-correlation (XC) integration grid, 2) TDDFT parallelization, and 3) profiling and optimization of the DFT and TDDFT. We summarize the work performed in these task areas and present the resulting speed-up. Our software enhancements are available to the general public in the 11APR2008R1 version of GAMESS. DoD HPCMP Users Group Conference 2008978-0-7695-3515-9/08 $25.00
One limitation of two-fluid computational fluid dynamics models for gas-particle flow is the inability of these models to properly describe the effects of particle-particle interactions in the case of large St at high solids concentrations. Discrete element methods (DEM) present an opportunity to study such interactions. In gas-particle flows with higher solids loadings, particle-particle interactions give rise to particle clustering and/or microstructure formation. In this paper we show how DEM can be used to determine not only the particle-phase stress (required for gas-particle two-fluid CFD models) in the case of particle clustering, but also how DEM can be used to determine the nature, size and composition of the observed microstructure. Specifically, we investigate, using a computationally efficient DEM simulation, the dependence of particle-phase stress in systems with high solids concentration on the solids coefficient of restitution (0.6 to 0.9) and solids volume fraction (0.05 to 0.3). We investigate both monodisperse and bidisperse particle systems. We show how a widening of the particle size distribution reduces the particle-phase stress and inhibits the formation of particle clusters. We also show in our bidisperse simulations how smaller particles (yet still inertia-dominated) are more evenly distributed throughout the system. Finally, we highlight the dependence of the particle-phase stress on the domain size of the simulation and emphasize that a sufficiently large domain size is necessary to accurately describe the clusters which form at higher particle concentrations.
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