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A new multiple-time-step three-dimensional discrete element modeling of aerosol acoustic agglomeration
Powder Technology ( IF 4.5 ) Pub Date : 2018-01-01 , DOI: 10.1016/j.powtec.2017.10.036
Guangxue Zhang , Lili Zhang , Jinqing Wang , Zuohe Chi , Eric Hu

Abstract An acoustic agglomeration process, in which high-intensity sound is used to agglomerate particles in aerosols, can be simulated using the discrete element model (DEM). However, the conventional DEM is very time-consuming due to the large difference between the various time scales involved in the modeling. In this paper, a multiple-time-step algorithm is used to speed up the 3D DEM simulation of aerosol acoustic agglomeration, which reduces the computational time by more than one order of magnitude, comparing with the conventional DEM. When the computational domain contains N particles, the computational complexity of the improved DEM simulation is of the order of O ( N ), by restricting the acoustic wake effect in certain ranges and performing contact detection based on a search grid. The DEM simulation model has been validated by: 1) the analytical solution for the oscillation motion of an isolated particle in a sound field, 2) the experimental result of the agglomeration trajectories of two particles under the mutual effect of acoustic wakes, and 3) the experimental results of acoustic agglomeration of coal-fired fly ash particles. It is found that the agglomeration efficiency obtained from DEM simulation is in good agreement with the experimental results at moderate sound pressure levels, while the simulation overestimates the agglomeration efficiency at a high sound pressure level of 149 dB, due to the breakage of aggregates in the experiment.

中文翻译:

一种新的多时间步长的气溶胶声团聚三维离散元建模

摘要 使用离散元模型 (DEM) 可以模拟使用高强度声音将气溶胶中的颗粒聚集在一起的声聚集过程。然而,由于建模所涉及的各种时间尺度之间的差异很大,传统的 DEM 非常耗时。本文采用多时间步长算法来加速气溶胶声团聚的3D DEM模拟,与传统的DEM相比,计算时间减少了一个数量级以上。当计算域包含 N 个粒子时,通过将声学尾流效应限制在一定范围内并基于搜索网格进行接触检测,改进的 DEM 模拟的计算复杂度为 O ( N ) 量级。DEM 仿真模型已通过以下方式验证:1) 孤立粒子在声场中的振荡运动解析解, 2) 声尾流相互作用下两个粒子的团聚轨迹实验结果, 3) 煤的声团聚实验结果——发射飞灰颗粒。发现 DEM 模拟得到的团聚效率与中等声压级下的实验结果非常吻合,而模拟高估了 149 dB 高声压级下的团聚效率,这是由于团聚体在实验。3) 燃煤粉煤灰颗粒声团聚实验结果。发现 DEM 模拟得到的团聚效率与中等声压级下的实验结果非常吻合,而模拟高估了 149 dB 高声压级下的团聚效率,这是由于团聚体在实验。3) 燃煤粉煤灰颗粒声团聚实验结果。发现 DEM 模拟得到的团聚效率与中等声压级下的实验结果非常吻合,而模拟高估了 149 dB 高声压级下的团聚效率,这是由于团聚体在实验。
更新日期:2018-01-01
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