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PMID: 37262969 Published · ppublish English Systematic Review Journal Article

The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review.

Ecotoxicology and environmental safety ·Vol. 260 ·2023-07-15 ·页码 115066

Yuan S, Ajam H, Sinnah ZAB, Altalbawy FMA, Abdul Ameer SA, Husain A, Al Mashhadani ZI, Alkhayyat A, Alsalamy A, Zubaid RA, Cao Y

Abstract

Membrane-based separation processes has been recently of significant global interest compared to other conventional separation approaches due to possessing undeniable advantages like superior performance, environmentally-benign nature and simplicity of application. Computational simulation of fluids has shown its undeniable role in modeling and simulation of numerous physical/chemical phenomena including chemical engineering, chemical reaction, aerodynamics, drug delivery and plasma physics. Definition of fluids can be occurred using the Navier-Stokes equations, but solving the equations remains an important challenge. In membrane-based separation processes, true perception of fluid's manner through disparate membrane modules is an important concern, which has been significantly limited applying numerical/computational procedures such s computational fluid dynamics (CFD). Despite this noteworthy advantage, the optimization of membrane processes using CFD is time-consuming and expensive. Therefore, combination of artificial intelligence (AI) and CFD can result in the creation of a promising hybrid model to accurately predict the model results and appropriately optimize membrane processes and phase separation. This paper aims to provide a comprehensive overview about the advantages of commonly-employed ML-based techniques in combination with the CFD to intelligently increase the optimization accuracy and predict mass transfer and the unfavorable events (i.e., fouling) in various membrane processes. To reach this objective, four principal strategies of AI including SL, USL, SSL and ANN were explained and their advantages/disadvantages were discussed. Then after, prevalent ML-based algorithm for membrane-based separation processes. Finally, the application potential of AI techniques in different membrane processes (i.e., fouling control, desalination and wastewater treatment) were presented.

Keywords
Artificial intelligence CFD Membrane processes Model prediction Optimization
MeSH 主题词
Artificial Intelligence Computer Simulation Algorithms Water Purification/methods Hydrodynamics
作者与单位
共 11 位作者,点击展开单位 / ORCID
Yuan Shuai
Information Engineering College, Yantai Institute of Technology, Yantai, Shandong 264005, China. Electronic address: [email protected].
Ajam Hussein
Department of Intelligent Medical Systems, Al Mustaqbal University College, Babylon 51001, Iraq.
Sinnah Zainab Ali Bu
Mathematics Department, University Colleges at Nairiyah, University of Hafr Al Batin, Saudi Arabia.
Altalbawy Farag M A
National Institute of Laser Enhanced Sciences (NILES), University of Cairo, Giza 12613, Egypt; Department of Chemistry, University College of Duba, University of Tabuk, Tabuk, Saudi Arabia.
Abdul Ameer Sabah Auda
Ahl Al Bayt University, Kerbala, Iraq.
Husain Ahmed
Department of Medical Instrumentation, Al-farahidi University, Baghdad, Iraq.
Al Mashhadani Zuhair I
Al-Nisour University College, Baghdad, Iraq.
Alkhayyat Ahmed
Scientific Research Centre of the Islamic University, The Islamic University, Najaf, Iraq.
Alsalamy Ali
College of Technical Engineering, Imam Ja'afar Al-Sadiq University, Al-Muthanna 66002, Iraq.
Zubaid Riham Ali
Mazaya University College, Iraq.
Cao Yan
School of Computer Science and Engineering, Xi'an Technological University, Xi'an 710021, China.
Article Info
Journal
Ecotoxicology and environmental safety
Abbr.
Ecotoxicol Environ Saf
ISSN
1090-2414
Corresponding email
Published
2023-07-15
电子出版
2023-00-30
页码
115066
Language
English
Country/Region
Netherlands
NLM ID
7805381
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