Rahimpour Neshat, Bahmanyar Hossein, Hemmati Alireza, Asadollahzadeh Mehdi
Surface Phenomena and Liquid-Liquid Extraction Research Lab, School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran.
School of Chemical Petroleum and Gas Engineering, Iran University of Science and Technology (IUST), P.O. Box: 16765-163, Tehran, Iran.
Sci Rep. 2024 Feb 8;14(1):3273. doi: 10.1038/s41598-024-52542-1.
A new type of Tenova pulsed extraction column was introduced in 2017. It is the newest generation of pulsed columns. Due to the internal equipment of this column and the lack of moving parts and the simplicity and speed of repairs and maintenance, it has been the focus of researchers in recent years. No correlations for predicting the mean drop size and drop size distribution of the Tenova column have been reported. The Sauter mean drop diameter and drop size distribution are investigated for a Tenova pulsed column with a diameter and an active height of 7.4 and 73 cm, respectively. Three standard chemical systems of isobutyl acetate-water, isobutanol-water, and toluene-water have been used. The effects of pulse intensity, dispersed and continuous phase flow rates have been taken into account. In each experiment, 200-300 drops have been analyzed in a total of 10,000 drops. The investigation covered a spectrum of physical properties, notably surface tension (within a range of 1.75-36 mN/m). Operating conditions including pulse intensity (in the range of 0.2-2 cm/s) and the flow rate of continuous and dispersed phases (in the range of 8-30 L/h) have been investigated. Methods based on artificial intelligence (AI) such as multilayer perceptron neural networks and gene expression programming were combined with a dimensional analysis approach to provide a new approach to estimating the mean drop diameter (d). Experimental results have been compared with the equations found by other researchers in similar columns. The variation of drop size distribution has also been experimentally obtained.Methods based on artificial intelligence (AI) such as multilayer perceptron neural networks and gene expression programming were combined with a dimensional analysis approach to provide a new approach to estimating the mean drop diameter (d). Experimental results have been compared with the equations found by other researchers in similar columns. The variation of drop size distribution has also been experimentally obtained.
一种新型的特诺瓦脉冲萃取柱于2017年推出。它是脉冲柱的最新一代。由于该柱的内部设备、缺少活动部件以及维修和维护的简便性和快速性，它近年来一直是研究人员关注的焦点。目前尚未有关于预测特诺瓦柱平均液滴尺寸和液滴尺寸分布的关联式报道。对直径和有效高度分别为7.4 cm和73 cm的特诺瓦脉冲柱的索特平均液滴直径和液滴尺寸分布进行了研究。使用了乙酸异丁酯 - 水、异丁醇 - 水和甲苯 - 水三种标准化学体系。考虑了脉冲强度、分散相和连续相流速的影响。在每个实验中，总共10000个液滴中分析了200 - 300个液滴。该研究涵盖了一系列物理性质，特别是表面张力（在1.75 - 36 mN/m范围内）。研究了包括脉冲强度（在0.2 - 2 cm/s范围内）以及连续相和分散相流速（在8 - 30 L/h范围内）的操作条件。基于人工智能（AI）的方法，如多层感知器神经网络和基因表达编程，与量纲分析方法相结合，提供了一种估计平均液滴直径（d）的新方法。实验结果已与其他研究人员在类似柱中得到的方程进行了比较。还通过实验获得了液滴尺寸分布的变化情况。基于人工智能（AI）的方法，如多层感知器神经网络和基因表达编程，与量纲分析方法相结合，提供了一种估计平均液滴直径（d）的新方法。实验结果已与其他研究人员在类似柱中得到的方程进行了比较。还通过实验获得了液滴尺寸分布的变化情况。
