A Simulation Method for Layered Filling of Grain Piles Based on the Discrete Element Method

• Published in: Applied sciences 2023-10, Vol.13 (20), p.11347
• Main Authors: Yang, Kaimin, Du, Xinming, Mao, Yudong, Li, Xin, Liu, Jiying, Wang, Yuancheng
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Costs; DEM; Energy; Force and energy; Grain; Investigations; layered filling; Methods; Porosity; progressive filling; Simulation; Simulation methods; Ventilation
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app132011347

The Discrete Element Method (DEM) has been widely employed to investigate the behavior of particle systems at a macroscopic scale. However, effectively simulating the gradual filling of bulk cereal grains within silos using the DEM remains a formidable challenge due to time constraints. Thus, there is a critical need to develop a simplified model capable of substantially reducing the computational time required for simulating cereal grain accumulation. This study introduces a Layered Filling Method (LFM) designed to expedite the computational process for cereal grain piles within silos. By utilizing particle kinetic energy as a specific criterion, this model identifies particles as stable situations when their kinetic energy drops below a designated threshold. Throughout the filling process, lower particles that were judged to satisfy the condition of stability are isolated, forming sub-heaps that are exempt from persistent detection. The whole particle heap is subsequently segregated into multiple sub-piles and a main pile till the process’s culmination, and these divisions are merged back together. In order to validate the model’s feasibility and accuracy, a comparative analysis was performed on the characteristics of the porosity and airflow patterns of grain piles generated using the LFM and the progressive filling method (PFM), respectively. The research results indicate that there is a marginally higher porosity value in the grain pile simulated by the LFM in comparison to the PFM. However, the average relative error remains below 5.00%. Both the LFM and PFM exhibit a similar spiral upward trend in the simulated airflow paths. Notably, the LFM demonstrates a substantial reduction in the time required to construct grain piles.