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RESEARCH PAPER · Chinese Journal of Chemical Engineering · 2023

A data-driven model of drop size prediction based on artificial neural networks using small-scale data sets

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

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A data-driven model of drop size prediction based on artificial neural networks using small-scale data setsOriginalA CFD‐PBM‐ANN framework to simulate the liquid–liquid two‐phase flow in a pulsed column10Application of wavelet neural network with chaos theory for enhanced forecasting of pressure drop signals in vapor−liquid−solid fluidized bed evaporator6Thorough assessment of a crucial element pertaining to the distribution and average dimensions of droplet sizes in a solvent extraction column12CFD-PBM Coupled with Dynamic Interfacial Tension Model for Simulating Liquid–Liquid Two-Phase Flow and Interphase Mass Transfer in a Pulsed Column4Cyclic softening characteristics and cumulative strain prediction in aeolian sand-loess mixtures: Experimental and modeling insights2Prediction of drop size distribution and mean drop size in an L-shaped pulsed packed column using artificial neural network (ANN) model and semi-empirical correlation5Artificial Intelligence Modeling, RSM regression, and correlation analysis to predict of dispersed phase hold-up in the new agitated extraction column with randomly packing8Flooding characteristics in updated design of a stirred extractor with random packing and correlation analysis under combination of multilayer perceptron and cascade feedforward methods2Utilizing RSM and ANN modeling techniques to forecast the average droplet size and amount of dispersed phase in the Scheibel contactor through research2An ANN-based fluid particle breakage model for accelerating PBM simulation0Dynamic 1-D-PBM simulation of droplet size evolution with directly-measured kernel functions in pulsed extraction column2Analysis of river flow transfer characteristics under the influence of asymmetric diversion structures0Progress in pulsed extraction column for spent nuclear fuel reprocessing0Analysis of the Coupled Variations of Holdup and Droplet Diameter Based on Machine Learning Methods0Data-efficient artificial neural network modeling for corrosion rate prediction of inert anodes in aluminum electrolysis0

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

    AIChE Journal · 2024-09-25

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

    Read original paper ↗ ·

  2. Application of wavelet neural network with chaos theory for enhanced forecasting of pressure drop signals in vapor−liquid−solid fluidized bed evaporator

    Chinese Journal of Chemical Engineering · 2024-11-23

    Yangshuhan Xu, Ting Zhang, Zhimin Mu, Yongli Ma, Mingyan Liu

    Read original paper ↗ ·

  3. Thorough assessment of a crucial element pertaining to the distribution and average dimensions of droplet sizes in a solvent extraction column

    Separation Science and Technology · 2024-12-28

    Mehdi Asadollahzadeh, Rezvan Torkaman

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  4. CFD-PBM Coupled with Dynamic Interfacial Tension Model for Simulating Liquid–Liquid Two-Phase Flow and Interphase Mass Transfer in a Pulsed Column

    Industrial & Engineering Chemistry Research · 2025-02-26

    Bo Wang, Han Guo Zhou, Xiong Bill Yu, Qiang Zheng, Shan Jing, Wenjie Lan, Shaowei Li

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  5. Cyclic softening characteristics and cumulative strain prediction in aeolian sand-loess mixtures: Experimental and modeling insights

    Materials Today Communications · 2025-04-21

    Yixu Hu, Xuesong Mao, Qian Wu, Peichen Cai, Baolong Zhang, Lunkun Chen

    Read original paper ↗ ·

  6. Prediction of drop size distribution and mean drop size in an L-shaped pulsed packed column using artificial neural network (ANN) model and semi-empirical correlation

    Scientific Reports · 2025-07-17

    Ali Ravandeh, Sajad Khooshechin

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  7. Artificial Intelligence Modeling, RSM regression, and correlation analysis to predict of dispersed phase hold-up in the new agitated extraction column with randomly packing

    Chemical Engineering Science · 2025-08-12

    Khayyam Mehrabi, Hossein Bahmanyar, Mehdi Asadollahzadeh, Rezvan Torkaman, Meisam Torab‐Mostaedi

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  8. Flooding characteristics in updated design of a stirred extractor with random packing and correlation analysis under combination of multilayer perceptron and cascade feedforward methods

    Chemical Engineering Science · 2025-12-24

    Khayyam Mehrabi, Hossein Bahmanyar, Mehdi Asadollahzadeh, Rezvan Torkaman, Meisam Torab‐Mostaedi

    Read original paper ↗ ·

  9. Utilizing RSM and ANN modeling techniques to forecast the average droplet size and amount of dispersed phase in the Scheibel contactor through research

    Separation Science and Technology · 2025-12-28

    Khayyam Mehrabi, Hossein Bahmanyar, Mehdi Asadollahzadeh, Rezvan Torkaman, Meisam Torab‐Mostaedi

    Read original paper ↗ ·

  10. An ANN-based fluid particle breakage model for accelerating PBM simulation

    Chemical Engineering Science · 2026-02-05

    Shenggao Gong, Chaoqun Yao, Ningning Gao

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  11. Dynamic 1-D-PBM simulation of droplet size evolution with directly-measured kernel functions in pulsed extraction column

    Chemical Engineering Science · 2026-03-03

    Bo Wang, He Zhang, He Zhang, Yadong Xiao, Chen Meng, Tianci Li, Xiang Li, Tianci Li, Tianci Li, Yu Wang, Zeqian Cui, Haotian Ma, Guozhi Lv, Yan Liu, Zhihe Dou, Tingan Zhang, Han Guo Zhou, Shaowei Li, Shan Jing

    Read original paper ↗ ·

  12. Analysis of river flow transfer characteristics under the influence of asymmetric diversion structures

    Journal of Physics Conference Series · 2026-05-01

    Zhengyu Dong, Gefei Jin, Tianguo Lv

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  13. Progress in pulsed extraction column for spent nuclear fuel reprocessing

    Energy · 2026-06-09

    Xiucheng Yu, Zonghui Lu, Qi Liu, Zilong Song, Ting Yu, Ming Qu, Hui He, Lejin Xu

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  14. Analysis of the Coupled Variations of Holdup and Droplet Diameter Based on Machine Learning Methods

    Chemical Engineering & Technology · 2026-07-01

    Xingchen Ji, Lei Jin, Yu Zhou, Meng Zhang, Caishan Jiao, Tingting Liu, Qiang Zhao, Yang Gao

    Read original paper ↗ ·

  15. Data-efficient artificial neural network modeling for corrosion rate prediction of inert anodes in aluminum electrolysis

    Applied Surface Science · 2026-08-27

    Yu Wang, Luodan Xiang, Bo Wang, Yan Liu, Ting-an Zhang

    Read original paper ↗ ·
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