Convective heat transfer and pressure drop of aqua based TiO2 nanofluids at different diameters of nanoparticles: Data analysis and modeling with artificial neural network

被引：45

作者：

Hemmat Esfe, Mohammad ^{[1
]}

Nadooshan, Afshin Ahmadi ^{[2
]}

Arshi, Ali ^{[3
]}

Alirezaie, Ali ^{[4
]}

机构：

[1] Islamic Azad Univ, Khomeinishahr Branch, Dept Mech Engn, Esfahan, Iran

[2] Shahrekord Univ, Fac Engn, Shahrekord, Iran

[3] Islamic Azad Univ, Qaemshahr Branch, Dept Text Engn, Qaemshahr, Iran

[4] Semnan Univ, Fac Mech Engn, Semnan, Iran

来源：

PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES | 2018年 / 97卷

关键词：

Artificial neural network; TiO2-water; Nanofluid; Pressure drop; Heat transfer; Nusselt number; Nanoparticle diameter; THERMAL-CONDUCTIVITY; MIXED CONVECTION; HYBRID NANOFLUID; NATURAL-CONVECTION; ETHYLENE-GLYCOL; MULTIOBJECTIVE OPTIMIZATION; WATER NANOFLUID; VISCOSITY; PERFORMANCE; FLOW;

D O I：

10.1016/j.physe.2017.10.002

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

In this study, experimental data related to the Nusselt number and pressure drop of aqueous nanofluids of Titania is modeled and estimated by using ANN with 2 hidden layers and 8 neurons in each layer. Also in this study the effect of various effective variables in the Nusselt number and pressure drop is surveyed. This study indicated that the neural network modeling has been able to model experimental data with great accuracy. The modeling regression coefficient for the data of Nusselt number and relative pressure drop is 99.94% and 99.97% respectively. Besides, it represented that the increment of the Reynolds number and concentration made the increment of Nusselt number and pressure drop of aqueous nanofluid.

引用

页码：155 / 161

页数：7

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