A parallel unidirectional coupled DEM-PBM model for the efficient simulation of computationally intensive particulate process systems

Sampat, Chaitanya; Bettencourt, Franklin E.; Baranwal, Yukteshwar; Paraskevakos, Ioannis; Chaturbedi, Anik; Karkala, Subhodh; Jha, Shantenu; Ramachandran, Rohit; Ierapetritou, Marianthi G.

doi:10.1016/j.compchemeng.2018.08.006

Cited by 9 publications

(2 citation statements)

References 40 publications

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“…In addition, the new approach captures the first two moments of system with high accuracy which play important role in identifying the total number of particles and total particle volume in the system. Furthermore, the results obtained through this proposed HPM methodology hold considerable promise for integration with micro-scale approaches, such as the discrete element method (DEM) and computational fluid dynamics (CFD), when modelling multiscale industrial processes [58][59][60][61][62]. Finally, it can be concluded that the proposed approach is a very effective and efficient method to approximate the series solution of nonlinear collisional fragmentation equations.…”

Section: (D) Polymerization Kernel With An Exponential Initial Distri...mentioning

confidence: 82%

Homotopy perturbation method and its convergence analysis for nonlinear collisional fragmentation equations

Yadav,

Das,

Singh

et al. 2023

Proc. R. Soc. A.

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The exploration of collisional fragmentation pheno-mena remains largely unexplored, yet it holds considerable importance in numerous engineering and physical processes. Given the nonlinear nature of the governing equation, only a limited number of analytical solutions for the number density function corresponding to empirical kernels are available in the literature. This article introduces a semi-analytical approach using the homotopy perturbation method to obtain series solutions for the nonlinear collisional fragmentation equation. The method presented here can be readily adapted to solve both linear and nonlinear integral equations, eliminating the need for domain discretization. To gain deeper insights intothe accuracy of the proposed method, a convergence analysis is conducted. This analysis employs the concept of contractive mapping within the Banach space, a well-established technique universally acknowledged for ensuring convergence. Various collisional kernels (product and polymerization kernels), breakage distribution functions (binary and multiple breakage) and various initial particle distributions are considered to obtain the new series solutions. The obtained results are successfully compared against finite volume method [26] solutions in terms of number density functions and their moments. The error between the exact and obtained series solutions is shown in plots and tables to confirm the applicability and accuracy of the proposed method.

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Section: (D) Polymerization Kernel With An Exponential Initial Distri...mentioning

confidence: 82%

Homotopy perturbation method and its convergence analysis for nonlinear collisional fragmentation equations

Yadav,

Das,

Singh

et al. 2023

Proc. R. Soc. A.

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show abstract

“…The DEM was applied for a wide range of tasks in different areas, 2 starting from the standard problems of granular mechanics, like investigation of mixing behavior, 3 ending with modeling of agglomeration of enzymes, 4 or sintering of ceramics 5 . There exist various extensions of the DEM, such as the multisphere approach, the bonded particle method (BPM) 6–8 or the DEM coupling to computational fluid dynamics, 9,10 population balance models, 11,12 or finite element method 13 …”

Section: Introductionmentioning

confidence: 99%

Parallel CPU–GPU computing technique for discrete element method

Skorych

Dosta

2022

Concurrency and Computation

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The efficiency of the simulations with the discrete element method (DEM) is significantly improved using a novel computational strategy. The new method is developed with a focus on platforms equipped with multi-core central processing units (CPU) and general-purpose graphics processing units (GPU). The DEM calculations are performed in parallel on the CPU and on the GPU using pre-calculated Verlet lists with a posteriori analysis of their consistency. The operations related to the search for possible contacts are performed on the CPU, whereas the processing of interactions, and integration of motion, are executed on the GPU. Performance analysis done for various types of tasks has shown that the new method allows to significantly decrease the average computational time and to utilize available computational resources more efficiently compared to the sequential CPU-GPU execution mode. Furthermore, due to more efficient calculations, the overall energy requirement for the proposed strategy does not exceed the demand for conventional sequential CPU-GPU computations.

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A Computationally Efficient Surrogate-Based Reduction of a Multiscale Comill Process Model

2019

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A parallel unidirectional coupled DEM-PBM model for the efficient simulation of computationally intensive particulate process systems

Cited by 9 publications

References 40 publications

Homotopy perturbation method and its convergence analysis for nonlinear collisional fragmentation equations

Homotopy perturbation method and its convergence analysis for nonlinear collisional fragmentation equations

Parallel CPU–GPU computing technique for discrete element method

A Computationally Efficient Surrogate-Based Reduction of a Multiscale Comill Process Model

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