Journal of Dispersion Science and Technology, ( ISI ), Volume (37), No (9), Year (2016-9) , Pages (1277-1286)

Title : ( Heat Transfer Coefficient Prediction of Metal Oxides Based Water Nanofluids Under Laminar Flow Regime Using Adaptive Neuro-Fuzzy Inference System )

Authors: Sajad Rashidi , farzin farshad , Ahmad Amiri , Mehdi Shanbedi , Masoud Rahimipanah , Maryam Savari , zohreh taghizadeh tabari , Saeed Zeinali Heris ,
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In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al2O3, and TiO2) are loaded into the TO. To measure the thermal performance of nanoparticles-based TO nanofluids at laminar flow and constant heat flux boundary condition, an experimental setup was applied. The obtained data clearly demonstrate the positive effect of all nanoparticles on the heat transfer rate of TO. As the most important factor, heat transfer coefficient of above-mentioned two phase systems is increased with increasing both volume concentration and flow rate. Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied for modelling the effect of critical parameters on the heat transfer coefficient of nanoparticles-TO based nanofluid numerically. The results compared with experimental ones for training and test data. Results suggest that the developed model is enough valid and promising for predicting the extant of heat transfer coefficient. R2 and MSE values for all data were 0.990208751 and 108.1150734, respectively. Based on the results, it is obvious that our proposed modelling by ANFIS is efficient and valid, which can be expanded for more general states.

Keywords

, ANFIS, heat transfer, metal oxide nanoparticles,
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@article{paperid:1052621,
author = {Rashidi, Sajad and Farshad, Farzin and Ahmad Amiri and Shanbedi, Mehdi and Rahimipanah, Masoud and Maryam Savari and Taghizadeh Tabari, Zohreh and Zeinali Heris, Saeed},
title = {Heat Transfer Coefficient Prediction of Metal Oxides Based Water Nanofluids Under Laminar Flow Regime Using Adaptive Neuro-Fuzzy Inference System},
journal = {Journal of Dispersion Science and Technology},
year = {2016},
volume = {37},
number = {9},
month = {September},
issn = {0193-2691},
pages = {1277--1286},
numpages = {9},
keywords = {ANFIS; heat transfer; metal oxide nanoparticles; nanofluid},
}

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%0 Journal Article
%T Heat Transfer Coefficient Prediction of Metal Oxides Based Water Nanofluids Under Laminar Flow Regime Using Adaptive Neuro-Fuzzy Inference System
%A Rashidi, Sajad
%A Farshad, Farzin
%A Ahmad Amiri
%A Shanbedi, Mehdi
%A Rahimipanah, Masoud
%A Maryam Savari
%A Taghizadeh Tabari, Zohreh
%A Zeinali Heris, Saeed
%J Journal of Dispersion Science and Technology
%@ 0193-2691
%D 2016

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