Experimental Investigation of Thermal Conductivity of Alumina (Al2O3)-Multi-Walled Carbon Nanotubes (MWCNT) in Water-Ethylene Glycol Hybrid Nanofluid

Author:

Dunga Asirinaidu1,Koona Ramji1,Naidu S. V.2

Affiliation:

1. Department of Mechanical Engineering, Andhra University, Visakhapatnam 530003, India

2. Department of Chemical Engineering, Andhra University, Visakhapatnam 530003, India

Abstract

Thermal conductivity and stability of hybrid nanofluid containing Al2O3 and MWCNT nanoparticles (90:10 weight% or 87:13 volume%) in the base fluid of Water and Ethylene Glycol (EG) mixture (80:20 volume%) had been experimentally investigated. Nanofluid was prepared using the two-step method, i.e., by dispersion the nanoparticles into base fluid using ultra-sonication. The stability of nanofluids was determined by UV-VIS-NIR spectroscopy by measuring maximum absorbance (along with the corresponding wavelength) for all samples. CTAB surfactant of 1/10th weight of nanoparticle was used to prevent agglomeration. The nanofluid absorbance was observed after 1, 10, 20 and 30 days of storage. Nanofluid having a concentration of 0.028%, was found to be stable up to 20 days. Higher concentrations or longer duration made the nanofluid unstable within 20 days. Thermal conductivity measurements were conducted in the temperature range T = 25 °C–50 °C (6 levels) and volume concentration φ = 0.004%–0.028% (8 levels). Scherrer’s equation was applied to XRD data to compute the average crystalline size of Al2O3 nanoparticles as 43 nm. FESEM showed good morphology of nanoparticles. EDX stoichiometric analysis confirmed that the nanofluid contained only Al, O, C elements. Experimental results showed that thermal conductivity increases with an increase in volume concentration and temperature. Maximum thermal conductivity of 0.5416 W/mK (8.47% increase over base fluid) was observed at T = 50 °C and φ = 0.028%. Maxwell, Weber, Hashin-Shtrikman, Bruggeman’s theoretical models and their experimental data showed a significant deviation. Hence regression equations that are suitable for these data were developed for better prediction purposes.

Publisher

American Scientific Publishers

Subject

Fluid Flow and Transfer Processes,Mechanical Engineering

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