The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review
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...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-07-01
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| Series: | Ecotoxicology and Environmental Safety |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651323005705 |
| _version_ | 1797806398504960000 |
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| author | Shuai Yuan Hussein Ajam Zainab Ali Bu Sinnah Farag M.A. Altalbawy Sabah Auda Abdul Ameer Ahmed Husain Zuhair I. Al Mashhadani Ahmed Alkhayyat Ali Alsalamy Riham Ali Zubaid Yan Cao |
| author_facet | Shuai Yuan Hussein Ajam Zainab Ali Bu Sinnah Farag M.A. Altalbawy Sabah Auda Abdul Ameer Ahmed Husain Zuhair I. Al Mashhadani Ahmed Alkhayyat Ali Alsalamy Riham Ali Zubaid Yan Cao |
| author_sort | Shuai Yuan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T06:06:42Z |
| format | Article |
| id | doaj.art-c59283032b6643208df3743ec5d44ce1 |
| institution | Directory Open Access Journal |
| issn | 0147-6513 |
| language | English |
| last_indexed | 2024-03-13T06:06:42Z |
| publishDate | 2023-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj.art-c59283032b6643208df3743ec5d44ce12023-06-12T04:08:56ZengElsevierEcotoxicology and Environmental Safety0147-65132023-07-01260115066The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic reviewShuai Yuan0Hussein Ajam1Zainab Ali Bu Sinnah2Farag M.A. Altalbawy3Sabah Auda Abdul Ameer4Ahmed Husain5Zuhair I. Al Mashhadani6Ahmed Alkhayyat7Ali Alsalamy8Riham Ali Zubaid9Yan Cao10Information Engineering College, Yantai Institute of Technology, Yantai, Shandong 264005, China; Corresponding author.Department of Intelligent Medical Systems, Al Mustaqbal University College, Babylon 51001, IraqMathematics Department, University Colleges at Nairiyah, University of Hafr Al Batin, Saudi ArabiaNational Institute of Laser Enhanced Sciences (NILES), University of Cairo, Giza 12613, Egypt; Department of Chemistry, University College of Duba, University of Tabuk, Tabuk, Saudi ArabiaAhl Al Bayt University, Kerbala, IraqDepartment of Medical Instrumentation, Al-farahidi University, Baghdad, IraqAl-Nisour University College, Baghdad, IraqScientific Research Centre of the Islamic University, The Islamic University, Najaf, IraqCollege of Technical Engineering, Imam Ja’afar Al-Sadiq University, Al-Muthanna 66002, IraqMazaya University College, IraqSchool of Computer Science and Engineering, Xi’an Technological University, Xi’an 710021, ChinaMembrane-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.http://www.sciencedirect.com/science/article/pii/S0147651323005705Membrane processesArtificial intelligence, CFDOptimizationModel prediction |
| spellingShingle | Shuai Yuan Hussein Ajam Zainab Ali Bu Sinnah Farag M.A. Altalbawy Sabah Auda Abdul Ameer Ahmed Husain Zuhair I. Al Mashhadani Ahmed Alkhayyat Ali Alsalamy Riham Ali Zubaid Yan Cao 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 Membrane processes Artificial intelligence, CFD Optimization Model prediction |
| title | The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review |
| title_full | The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review |
| title_fullStr | The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review |
| title_full_unstemmed | The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review |
| title_short | The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review |
| title_sort | roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes a systematic review |
| topic | Membrane processes Artificial intelligence, CFD Optimization Model prediction |
| url | http://www.sciencedirect.com/science/article/pii/S0147651323005705 |
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