International Journal of Thermal Sciences, ( ISI ), Volume (186), Year (2023-4) , Pages (108141-20)

Title : ( Multi-objective optimization of a tubular heat exchanger enhanced with delta winglet vortex generator and nanofluid using a hybrid CFD-SVR method )

Authors: Seyed Mahdi Ekrani , Shayan Ganjezadeh , Javad Abolfazli Esfahani ,

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Abstract

The present study improves the thermal-hydraulic performance of a circular tube equipped with a delta winglet vortex generator by providing a numerical model, investigating the effect of two additional parameters, and developing a support vector regression (SVR) for prediction and optimization. The additional parameters are the angle of attack and SiO2 concentration, while the data on the variation of thermohydraulic parameters with pitch and blockage is already available in the literature. The boundary layer disruption and swirling flow caused by the delta winglet result in heat transfer enhancement. The presence of such inserts also increases the pressure drop in the heat exchanger. The nanofluid further enhances heat transfer by boosting the thermophysical properties of the fluid. The hybrid method, CFD-SVR, is carried out for turbulent water flow at Reynolds numbers ranging from 4200 to 16200. The delta winglets are in pair arrangement with ten angles of attack from 25∘ to 70∘ with 5∘ increments. The addition of SiO2 with volumetric concentrations varies from φ = 0 to 0.5% has been explored. The diameter of the tube (D) is 50 mm, while the pitch ratio (P/D) and blockage ratio (B/D) vary from 1 to 3 and 0.1 to 0.2, respectively. Finally, the data of this study and the previously published experimental data were fed into an SVR to find the best possible arrangement of delta winglet for a tubular heat exchanger. The highest achieved thermal enhancement factor (TEF) was found to be 2.18 with α = 25◦, PR = 0.83, BR = 0.13, and φ = 0.5% at the least Re number.

Keywords

, ubular heat exchanger Heat transfer enhancement Delta winglet vortex generator Nanofluid Hybrid CFD, SVR method Artificial neural network
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@article{paperid:1093751,
author = {Ekrani, Seyed Mahdi and Ganjezadeh, Shayan and Abolfazli Esfahani, Javad},
title = {Multi-objective optimization of a tubular heat exchanger enhanced with delta winglet vortex generator and nanofluid using a hybrid CFD-SVR method},
journal = {International Journal of Thermal Sciences},
year = {2023},
volume = {186},
month = {April},
issn = {1290-0729},
pages = {108141--20},
numpages = {-108121},
keywords = {ubular heat exchanger Heat transfer enhancement Delta winglet vortex generator Nanofluid Hybrid CFD-SVR method Artificial neural network},
}

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%0 Journal Article
%T Multi-objective optimization of a tubular heat exchanger enhanced with delta winglet vortex generator and nanofluid using a hybrid CFD-SVR method
%A Ekrani, Seyed Mahdi
%A Ganjezadeh, Shayan
%A Abolfazli Esfahani, Javad
%J International Journal of Thermal Sciences
%@ 1290-0729
%D 2023

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