Abstract
This article presents the application of high performance computing for efficient simulations of granular media in silos. Granular media are extensively used in industry, where storage and proper treatment pose several challenges to the scientific community. A relevant problem concerns the study of granular media stored in a silo. Determining the behavior of the media during load and discharge stages is critical. Knowing how the stored particles interact with each other and how they interact with the storage structure can lead to understanding and preventing undesirable effects (e.g., the collapse of the structure) during the silo operation. Charge and discharge processes of granular media in silos are frequently studied using computer simulations. High performance computing comes to help researchers to perform granular media simulations for systems with a large number of particles, in order to model realistic situations in reasonable computing times. This article describes the application of a parallel/distributed high performance computing approach for studying the mechanisms that control the charging and discharging process of silos, in which grains pass through a bottleneck. Simulations are performed applying the Discrete Element Method, and the experimental evaluation is performed over the high performance computing infrastructure of the National Supercomputing Center in Uruguay. The analysis includes large realistic scenarios considering the physical properties of different grains, involving up to 450,000 particles. The proposed implementation allowed to reduce the execution time of simulations up to 42%, demonstrating the capabilities of the proposed parallel/distributed computing approach to scale to solve large problem instances properly.
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Da Silva, M., Nesmachnow, S., Iturriaga, S., Usera, G. (2021). High Performance Computing Simulations of Granular Media in Silos. In: Nesmachnow, S., Castro, H., Tchernykh, A. (eds) High Performance Computing. CARLA 2020. Communications in Computer and Information Science, vol 1327. Springer, Cham. https://doi.org/10.1007/978-3-030-68035-0_3
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