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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用于模拟脉冲塔中液-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。仿真结果与不同工况下的实验数据吻合较好。累积液滴粒径分布随界面张力和脉冲强度的增加而减小。仿真还发现，圆盘和甜甜圈板边缘的液滴破碎频率相对较高，这与湍流能量耗散和速度梯度的分布一致。