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.

中文翻译：

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基于气体压力梯度的亚网格漂移速度模型，用于预测流化气体颗粒流中的阻力

由于子网格漂移速度与滤波后的阻力之间存在线性关系，因此对漂移速度进行建模将是获得用于粗网格模拟的滤波后的阻力的另一种方法。这项工作旨在使用新的有效标记（滤波后的气压梯度）来提高漂移速度模型的可预测性，该指标通过动量平衡分析来识别。新模型的建立是基于对三维无界流化系统的细网格双流体模型仿真结果的条件平均。通过对文献中提出的动态调整技术，将提出的模型与现有的最佳Smagorinsky型模型进行比较，从而进行先验评估。结果表明，所提出的模型具有令人满意的性能。更重要，