A parallel unidirectional coupled DEM-PBM model for the efficient simulation of computationally intensive particulate process systems
Autor: | Franklin E. Bettencourt, Rohit Ramachandran, Ioannis Paraskevakos, Anik Chaturbedi, Chaitanya Sampat, Marianthi G. Ierapetritou, Shantenu Jha, Yukteshwar Baranwal, Subhodh Karkala |
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Rok vydání: | 2018 |
Předmět: |
Coupling
Population balance model General Chemical Engineering Process (computing) 02 engineering and technology 021001 nanoscience & nanotechnology Collision Discrete element method Computer Science Applications Computational science Kernel (linear algebra) 020401 chemical engineering 0204 chemical engineering 0210 nano-technology Process systems Scaling |
Zdroj: | Computers & Chemical Engineering. 119:128-142 |
ISSN: | 0098-1354 |
DOI: | 10.1016/j.compchemeng.2018.08.006 |
Popis: | The accurate modeling of the physics underlying particulate processes is complicated and requires significant computational capabilities to solve using particle-based models. In this work, a unidirectional multi-scale approach was used to model the high shear wet granulation process. A multi-dimensional population balance model (PBM) was developed with a mechanistic kernel, which in turn obtained collision data from the discrete element modeling (DEM) simulation. The PBM was parallelized using a hybrid OpenMP+MPI approach. The DEM simulations were performed using LIGGGHTS, which was parallelized using MPI. Speedups of approximately 14 were obtained for the PBM simulations and approximately 12 for the DEM simulations. The uni-directional coupling of DEM to PBM was performed using middle-ware components (RADICAL-Pilot) that did not require modifications of the DEM or PBM codes, yet supported flexible execution on high-performance platforms. Results demonstrate scaling from 1 to 128 cores for the PBM and up to 256 cores for the DEM. The proposed method, implementations and middle-ware enable the modeling of high shear wet granulation process faster than existing approaches in literature. |
Databáze: | OpenAIRE |
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