摘要
提出一种结合计算流体力学(CFD)和BP(Back Propagation)人工神经网络的多尺度计算方法,计算规整填料塔上的流体力学行为。根据最小特征单元实际尺寸建立小尺度三维CFD模型,研究了填料塔单气相和气液两相流体流动分布方式,弥补了在研究塔壁单元和层间转换单元产生压降方面的缺陷。建立了结点网络模型,计算全塔的流体分布等宏观信息。以CFD计算收集到的数据集训练了2组神经网络模型,分别以结点流量为输入计算干塔压降和持液量。计算结果与相关实验数据比较,干塔压降计算模型的平均相对偏差为8.63%,最大相对偏差为14.02%。持液量计算模型的平均相对偏差约为9.63%,最大相对偏差为13.97%。这表明该训练好的人工神经网络模型具备较好的预测能力,结果较为可信。
A multi-scale calculation method combining computational fluid dynamics(CFD)and back propagation neural network(BPNN)was proposed to calculate the hydrodynamic behavior of structured packing column.According to the actual size of the representative elementary units,a small-scale 3D CFD model was established,and the flow distribution of single gas phase and gas-liquid two-phase fluid in the packing column was studied,which made up for the defects in the pressure drop of the column wall unit and the interlayer conversion unit.A node network model was established to calculate the macroscopic information such as the fluid distribution of the whole column.Two neural network models were trained with the data set collected by CFD calculation,and the dry pressure drop and liquid holdup were calculated respectively with the node flow as input neuron.Compared with the relevant experimental data,the average relative deviation of the prediction model for dry pressure drop was 8.63%and the maximum relative deviation was 14.2%.The average relative deviation and maximum relative deviation of the predic tion model for liquid holdup were 9.63%and 13.97%,respectively.The trained artificial neural network model was proved to be prospective to determinate dry pressure drops and liquid holdup of structured packing columns.
作者
李邢
曾爱武
LI Xing;ZENG Aiwu(School of Chemical Engineering and Technology,Tianjin University,Tianjin 300072,China;State Key Laboratory of Chemical Engineering,Tianjin 300354,China)
出处
《化学工业与工程》
北大核心
2025年第1期130-137,共8页
Chemical Industry and Engineering
关键词
规整填料
计算流体力学
BP神经网络
干塔压降
持液量
structured packing columns
computational fluid dynamic
back propagation neural network
dry pressure drops
liquid holdup
