A CFD-PBM-ANN framework to simulate the liquid–liquid two-phase flow in a pulsed column

IF 3.5 3区工程技术 Q2 ENGINEERING, CHEMICAL

AIChE Journal Pub Date : 2024-09-25 DOI:10.1002/aic.18612

Bo Wang, Siyuan Ma, Han Zhou, Qiang Zheng, Wenjie Lan, Shan Jing, Shaowei Li

引用次数: 0

Abstract

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.

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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，我们根据以往研究中的直接测量数据，建立了基于人工神经网络（ANN）的液滴破碎频率函数。然后，以矩阵和矢量的形式将 ANN 的权值和偏置嵌入 CFD-PBM 代码中。首次建立了 CFD-PBM-ANN 仿真框架。模拟结果与不同运行条件下的实验数据非常吻合。累积液滴粒度分布随着界面张力和脉冲强度的增加而减小。模拟还发现，圆盘和圆环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相一致。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

AIChE Journal 工程技术-工程：化工

CiteScore

7.10

自引率

10.80%

发文量

411

审稿时长

3.6 months

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