应用计算流体动力学的生物固体中不同尺寸范围颗粒物质的分散模拟

Praneeth Nimmatoori, Ashok Kumar
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引用次数: 2

摘要

本文提出了一种利用计算流体动力学(CFD)-FLUENT的方法来模拟应用于农田的生物固体释放的颗粒物质的分散,并预测不同粒径范围内的颗粒浓度。离散相模型(拉格朗日-欧拉方法)与四种湍流模型:标准kε (kε)、可实现kε (Rkε)、标准kω (kω)和剪切应力输运k-ω (SST)相结合,用于预测农田下风距离的颗粒物粒径浓度。在这种建模方法中,颗粒被模拟为离散相,空气被模拟为连续相。将预测的颗粒物浓度与相应的实地观测结果进行统计比较,以评估湍流模型的性能。统计分析表明,在4种湍流模型中,采用Rkε的离散相模型对低(u < 2 m/s)和中(2 < u < 5 m/s)风速下的颗粒物浓度预测效果最好。对于高风速(u > 5 m/s), Rkε、kω和海表温度表现出相似的特征。基于Rkε的离散相模型表现良好,对粒径(μm)为0.23、0.3、0.4、0.5、0.65、0.8、1、1.6、2、3、4和5时的最佳浓度进行了模拟。当粒径为7.5和10时,Rkε、kε、kω和SST的性能相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dispersion Modeling of Particulate Matter in Different Size Ranges Releasing from a Biosolids Applied Agricultural Field Using Computational Fluid Dynamics
This paper proposes a methodology using computational fluid dynamics (CFD)-FLUENT to simulate the dispersion of particulate matter releasing from a biosolid applied agricultural field and predict the particulate concentrations for different ranges of particle sizes. The discrete phase model (Lagrangian-Eulerian approach) was used in combination with each of the four turbulence models: Standard kε (kε), Realizable kε (Rkε), Standard kω (kω), and Shear-stress transport k-ω (SST) to predict particulate matter size concentrations for distances downwind of the agricultural field. In this modeling approach, particulates were simulated as discrete phase and air as continuous phase. The predicted particulate matter concentrations were compared statistically with their corresponding field study observations to evaluate the performance of turbulence models. The statistical analysis concluded that among four turbulence models, the discrete phase model when used with Rkε performed the best in predicting particulate matter concentrations for low (u < 2 m/s) and medium (2 < u < 5 m/s) wind speeds. For high (u > 5 m/s) wind speeds, Rkε, kω, and SST showed similar performances. The discrete phase model using Rkε performed very well and modeled the best concentrations for the particle sizes (μm): 0.23, 0.3, 0.4, 0.5, 0.65, 0.8, 1, 1.6, 2, 3, 4, and 5. For particle sizes: 7.5 and 10, the performances of Rkε, kε, kω, and SST were similar.
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