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A parallel unidirectional coupled DEM-PBM model for the efficient simulation of computationally intensive particulate process systems
Computers & Chemical Engineering ( IF 3.9 ) Pub Date : 2018-08-30 , DOI: 10.1016/j.compchemeng.2018.08.006
Chaitanya Sampat , Franklin Bettencourt , Yukteshwar Baranwal , Ioannis Paraskevakos , Anik Chaturbedi , Subhodh Karkala , Shantenu Jha , Rohit Ramachandran , Marianthi Ierapetritou

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.



中文翻译:

并行单向耦合DEM-PBM模型,用于高效计算密集型颗粒处理系统

颗粒过程的物理基础的精确建模非常复杂,需要大量的计算能力才能使用基于粒子的模型来求解。在这项工作中,单向多尺度方法用于模拟高剪切湿法制粒过程。使用机械内核开发了多维人口平衡模型(PBM),该模型又从离散元素建模(DEM)仿真中获得了碰撞数据。使用混合OpenMP + MPI方法并行化PBM。DEM模拟是使用LIGGGHTS进行的,而LIGGGHTS使用MPI进行了并行化。对于PBM仿真,获得了大约14的加速,对于DEM仿真,获得了大约12的加速。DEM与PBM的单向耦合是使用中间件组件(RADICAL-Pilot)执行的,该中间件组件无需修改DEM或PBM代码,但支持在高性能平台上灵活执行。结果表明,PBM可从1扩展到128内核,DEM则可扩展到256内核。所提出的方法,实施方式和中间件能够比文献中的现有方法更快地对高剪切湿法造粒过程进行建模。

更新日期:2018-08-30
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