CFD‐PBM numerical simulation is a powerful tool in the research of droplet swarm behavior. In this work, an artificial neural network (ANN) based droplet breakage frequency function is established based on the directly measured data from our previous studies. Then, the weights and biases of ANN are embedded into the CFD‐PBM code in the form of matrices and vectors. For the first time, a CFD‐PBM‐ANN simulation framework is established. Simulation results are in good agreement with the experimental data under different operation conditions. The cumulative droplet size distribution decreases with the increase of interfacial tension and pulse intensity. It is also found by the simulation that the droplet breakage frequency is relatively high at the edge of disc and doughnut plate, which is accordant with the distribution of turbulent energy dissipation and velocity gradient.

中文翻译：

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用于模拟脉冲柱中液-液两相流的 CFD-PBM-ANN 框架


CFD-PBM数值模拟是研究液滴群行为的有力工具。在这项工作中，基于我们之前研究的直接测量数据建立了基于人工神经网络（ANN）的液滴破损频率函数。然后，ANN 的权重和偏差以矩阵和向量的形式嵌入到 CFD-PBM 代码中。首次建立了CFD-PBM-ANN仿真框架。不同运行条件下的仿真结果与实验数据吻合较好。累积液滴尺寸分布随着界面张力和脉冲强度的增加而减小。模拟还发现，圆盘和环形板边缘处的液滴破碎频率较高，这与湍流能量耗散和速度梯度的分布相符。