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Preliminary study on the influence of in situ filter size in CFD-DEM transfer kernel

Particuology 2020年第4期18卷 205-209页

作者： William D.Fullmer jordan musser National Energy Technology Laboratory MorgantownWV26507USA Leidos Research Support Team MorgantownWV26507USA

An unknown in coupled Eulerian-Lagrangian models for particle flow,such as CFD-DEM,which has received fairly little attention in the literature to date is the size of the filter width in the transfer *** work provides a preliminary glimpse at how this parameter can influence the solution in cold-flow,unbounded *** to previously published direct numerical simulation data is used to suggest an appropriate range for this parameter.

关键词： CFD-DEM High-resolution Lagrangian-Eulerian kernel

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The divergence of nearby trajectories in soft-sphere DEM

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Particuology 2022年第4期20卷 1-8页

作者： William D.Fullmer Roberto Porcu jordan musser Ann S.Almgren Ishan Srivastava National Energy Technology Laboratory MorgantownWV 26507USA NETL Support Contractor MorgantownWV 26507USA Center for Computational Sciences and Engineering.Lawrence Berkeley National Laboratory BerkeleyCA 94720USA

The n-body instability is investigated with the soft-sphere discrete element *** divergence of nearby trajectories is quantifed by the dynamical memory *** the inverse proportionality between the dynamical memory time and the largest Lyapunov exponent,the soft-sphere discrete ele-ment method results are compared to previous hard-sphere molecular dynamics data for the first *** agreement is observed at low concentrations and the degree of instability is shown to increase asymptotically with increasing spring *** particle concentrations above 30%,the soft-sphere Lya-punov exponents increase faster than the corresponding hard-sphere *** paper concludes with a demonstration of how this case study may be used in conjunction with regression testing and code verification activities.

关键词： Soft-sphere DEM Chaos Lyapunov exponent

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Memory access optimization for particle operations in computational fluid dynamics-discrete element method simulations

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Particuology 2023年第7期78卷 97-110页

作者： Deepthi Vaidhynathan Hariswaran Sitaraman Ray Grout Thomas Hauser Christine M.Hrenya jordan musser Computational Science Center National Renewable Energy LaboratoryUnited States Research Computing University of ColoradoBoulderUnited States Chemical and Biological Engineering University of ColoradoBoulderUnited States Computational Science and Engineering National Energy Technology LaboratoryUnited States

Computational Fluid Dynamics-Discrete Element Method is used to model gas-solid systems in several applications in energy,pharmaceutical and petrochemical *** performance bot-tlenecks often limit the problem sizes that can be simulated at industrial *** data structures used to store several millions of particles in such large-scale simulations have a large memory footprint that does not fit into the processor cache hierarchies on current high-performance-computing platforms,leading to reduced computational *** paper specifically addresses this aspect of memory access bottlenecks in industrial scale *** use of space-flling curves to improve memory access patterns is described and their impact on computational performance is quantified in both shared and distributed memory parallelization *** Morton space flling curve applied to uniform grids and k-dimensional tree partitions are used to reorder the particle data-structure thus improving spatial and temporal locality in *** performance impact of these techniques when applied to two benchmark problems,namely the homogeneous-cooling-system and a fluidized-bed,are *** optimization techniques lead to approximately two-fold performance improvement in particle focused operations such as neighbor-list creation and data-exchange,with~1.5 times overall improvement in a fluidization simulation with 1.27 million particles.

关键词： CFD-DEM Memory access optimization Spatial reordering Performance optimization

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