Artificial intelligence in the field of nanofluids: A review on applications and potential future directions

被引：98
作者：
Bahiraei, Mehdi [1 ]
Heshmatian, Saeed [1 ]
Moayedi, Hossein [2 ,3 ]
机构：
[1] Kermanshah Univ Technol, Dept Mech Engn, Kermanshah, Iran
[2] Ton Duc Thang Univ, Dept Management Sci & Technol Dev, Ho Chi Minh City, Vietnam
[3] Ton Duc Thang Univ, Fac Civil Engn, Ho Chi Minh City, Vietnam
来源：
POWDER TECHNOLOGY | 2019年 / 353卷
关键词：
Nanofluids; Artificial intelligence; Neural networks; Optimization algorithms; Fuzzy logic; Genetic algorithm; WATER-BASED NANOFLUIDS; TUBE HEAT-EXCHANGER; GRAPHENE NANOPLATELETS NANOFLUID; ZN FERRITE NANOFLUID; THERMAL-CONDUCTIVITY; NEURAL-NETWORK; MULTIOBJECTIVE OPTIMIZATION; PARTICLE MIGRATION; ENTROPY GENERATION; ENERGY EFFICIENCY;
D O I：
10.1016/j.powtec.2019.05.034
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
Artificial Intelligence (AI) algorithms are becoming beneficial as substitute methods to conventional approaches or as components of incorporated systems. They have been utilized for solving complex applied problems in different fields and are becoming more and more popular at present. AI approaches can learn from patterns; are fault tolerant in the sense that they are capable to handle noisy data; are capable to manage non-linear problems; and once learned can carry out generalization and estimation at great speed. In this survey, for the first time, a comprehensive review of the AI algorithms developed to investigate different issues related to nanofluids is conducted. The contributions presented in this paper reveal the high potential of AI methods as tools for the prediction and optimization in nanofluids. In addition, challenges and directions for future research in the area of employing AI techniques in nanofluids are introduced and discussed. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：276 / 301
页数：26
相关论文
共 141 条
[1]   Experimental investigation and model development for effective viscosity of MgO-ethylene glycol nanofluids by using dimensional analysis, FCM-ANFIS and GA-PNN techniques [J].
Adio, Saheed Adewale ;
Mehrabi, Mehdi ;
Sharifpur, Mohsen ;
Meyer, Josua Petrus .
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2016, 72 :71-83
[2]   Predicting the effects of magnesium oxide nanoparticles and temperature on the thermal conductivity of water using artificial neural network and experimental data [J].
Afrand, Masoud ;
Hemmat Esfe, Mohammad ;
Abedini, Ehsan ;
Teimouri, Hamid .
PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES, 2017, 87 :242-247
[3]   Predicting the viscosity of multi-walled carbon nanotubes/water nanofluid by developing an optimal artificial neural network based on experimental data [J].
Afrand, Masoud ;
Nadooshan, Afshin Ahmadi ;
Hassani, Mohsen ;
Yarmand, Hooman ;
Dahari, M. .
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2016, 77 :49-53
[4]   Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network [J].
Afrand, Masoud ;
Najafabadi, Karim Nazari ;
Sina, Nima ;
Safaei, Mohammad Reza ;
Kherbeet, A. Sh. ;
Wongwises, Somchai ;
Dahari, Mahidzal .
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2016, 76 :209-214
[5]   Experimental study on thermal conductivity of water-based Fe3O4 nanofluid: Development of a new correlation and modeled by artificial neural network [J].
Afrand, Masoud ;
Toghraie, Davood ;
Sina, Nima .
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2016, 75 :262-269
[6]   Prediction of thermal conductivity of various nanofluids using artificial neural network [J].
Ahmadloo, Ebrahim ;
Azizi, Sadra .
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2016, 74 :69-75
[7]   Review of techniques based on artificial neural networks for the electrical characterization of concentrator photovoltaic technology [J].
Almonacid, Florencia ;
Fernandez, Eduardo F. ;
Mellit, Adel ;
Kalogirou, Soteris .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 75 :938-953
[8]   Electro- and thermophysical properties of water-based nanofluids containing copper ferrite nanoparticles coated with silica: Experimental data, modeling through enhanced ANN and curve fitting [J].
Alrashed, Abdullah A. A. A. ;
Karimipour, Arash ;
Bagherzadeh, Seyed Amin ;
Safaei, Mohammad Reza ;
Afrand, Masoud .
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2018, 127 :925-935
[9]   Effects on thermophysical properties of carbon based nanofluids: Experimental data, modelling using regression, ANFIS and ANN [J].
Alrashed, Abdullah A. A. A. ;
Gharibdousti, Maryam Soltanpour ;
Goodarzi, Marjan ;
de Oliveira, Leticia Raquel ;
Safaei, Mohammad Reza ;
Bandarra Filho, Enio Pedone .
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2018, 125 :920-932
[10]   Predicting the effective viscosity of nanofluids for the augmentation of heat transfer in the process industries [J].
Aminian, Ali .
JOURNAL OF MOLECULAR LIQUIDS, 2017, 229 :300-308
12345678910