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Taguchi optimization of automotive radiator cooling with nanofluids

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Abstract

Considering the influences of the heat transfer rate in automotive radiators on several aspects such as engine performance, fuel economy and available space for components, the present study numerically investigates the impacts of different nanofluids on the heat transfer and pressure drop in an automotive radiator. Four different parameters each having four levels are taken into consideration, which are nanoparticle volume fraction (\(\phi =0.1, 0.3, 0.7\), and 1%), Reynolds number (Re \(=\) 9350, 13,800, 18,500 and 23,000), type of base fluid (EG20, EG40, EG60, and water) and type of nanoparticle (\(\hbox {Fe}_{3}\hbox {O}_{4}\), CuO, \(\hbox {Al}_{2}\hbox {O}_{3}\), and \(\hbox {SiO}_{2})\). Taguchi method is employed for reducing the number of parameter combinations from 256 to 16. It is found that the nanofluid utilization improves heat transfer between 3.2 and 45.9% depending on the combination of the investigated parameters. Pressure drop is noticeably increased due to nanofluid utilization. Regarding the Taguchi optimization, using \(\hbox {Fe}_{3}\hbox {O}_{4}\)–water nanofluid with 0.3% volume fraction at Re \(=\) 9350 is the most appropriate option for a high heat transfer with relatively low pressure drop. It is concluded that the radiator size can be reduced by 10.8% by using nanofluids due to the improvement in heat transfer, which consequently allow a larger space to designers for placing other components.

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Abbreviations

A :

Cross-sectional area of the tube (\(\hbox {m}^{2}\))

\(C_\mathrm{f}\) :

Skin friction

\(C_\mathrm{p}\) :

Specific heat capacity (J/kg K)

\(D_\mathrm{h}\) :

Hydraulic diameter of the tube (m)

\(d_\mathrm{p}\) :

Nanoparticle diameter (m)

EG:

Ethylene glycol

h :

Convective heat transfer coefficient (W/m\(^{2}\) K)

k :

Thermal conductivity (W/m K)

\(K_\mathrm{B}\) :

Boltzmann constant (J/K)

l :

Tube length (m)

V :

Average velocity (m/s)

Nu :

Average Nusselt number

P :

Pressure (Pa)

Pr:

Prandtl number (\(\upmu \)C\(_\mathrm{p}/k\))

\(P_\mathrm{t}\) :

Tube periphery (m)

Re :

Reynolds number

W :

Pumping power (W)

\(\eta \) :

Effectiveness value

\(\mu \) :

Viscosity (kg/m s)

\(\rho \) :

Density (\(\hbox {kg}/\hbox {m}^{3}\))

\(\tau \) :

Fluid shear force (N)

\(\varphi \) :

Shape factor

\(\phi \) :

Nanoparticle volume fraction (%)

bf:

Base fluid

p:

Particle

nf:

Nanofluid

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Authors and Affiliations

  1. Mechanical Engineering Department, Kocaeli University, Umuttepe Campus, 41001, Kocaeli, Turkey

    Çağatay Yıldız, Çağatay Kaptan, Müslüm Arıcı & Hasan Karabay

  2. Industrial Engineering Department, Kocaeli University, Umuttepe Campus, 41001, Kocaeli, Turkey

    Kasım Baynal

  3. Management Department, Kyrgyz Turkish Manas University, Djal Campus, 720044, Bishkek, Kyrgyzstan

    Kasım Baynal

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  1. Çağatay Yıldız
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Yıldız, Ç., Kaptan, Ç., Arıcı, M. et al. Taguchi optimization of automotive radiator cooling with nanofluids. Eur. Phys. J. Spec. Top. 231, 2801–2819 (2022). https://doi.org/10.1140/epjs/s11734-022-00597-4

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