A gas pressure gradient dependent subgrid drift velocity model for drag prediction in fluidized gas-particle flows
A gas pressure gradient dependent subgrid drift velocity model for drag prediction in fluidized gas-particle flows
复制标题
用于流化气体颗粒流阻力预测的气压梯度相关亚网格漂移速度模型
DOI：
10.1002/aic.16884
复制
发表时间：
2019
期刊：
影响因子：
3.7
通讯作者：
Q. Zhou
中科院分区：
文献类型：
--
作者：
M. Jiang;X. Chen;Q. Zhou
由于亚网格漂移速度与过滤阻力之间具有线性相关性，因此，对漂移速度进行建模将是粗网格模拟中获得过滤阻力的另一种方法。这项工作的目的是使用一种新的有效标志-过滤气体压力梯度来提高漂移速度模型的预测能力，该指标通过动量平衡分析来识别。基于对三维无界流态化系统的细网格双流体模型模拟结果的条件平均，构造了新的模型。给出了模型的先验估计，并与文献中提出的具有动态调整技术的最佳Smagorinsky模型进行了比较。结果表明，提出的模型具有令人满意的性能。更重要的是，与Smagorinsky模型相比，所提出的模型对各种物理条件下的情况具有更好的适应性。
Due to the linear correlation between the subgrid drift velocity and the filtered drag force, modeling the drift velocity would be an alternative way to obtain the filtered drag force for coarse‐grid simulations. This work aims to improve the predictability of models for the drift velocity using a new effective marker, the filtered gas pressure gradient, which is identified by momentum balance analysis. New models are constructed based on conditional averaging of the results obtained from fine‐grid two‐fluid model simulations of three‐dimensional unbounded fluidized systems. A priori assessment is presented with the comparison between the proposed models and the best available Smagorinsky‐type model with dynamic adjustment technique proposed in the literature. Results show that the proposed models give satisfactory performance. More important, the proposed models are demonstrated to have a better adaptability for cases under various physical conditions than the Smagorinsky‐type model.