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Entropy generation of boehmite alumina nanofluid flow through a minichannel heat exchanger considering nanoparticle shape effect

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  • Al-Rashed, Abdullah A.A.A.
  • Ranjbarzadeh, Ramin
  • Aghakhani, Saeed
  • Soltanimehr, Mehdi
  • Afrand, Masoud
  • Nguyen, Truong Khang

Abstract

This paper aims to study the effect of nanoparticle shape on the entropy generation characteristics of boehmite alumina nanofluid flowing through a horizontal double-pipe minichannel heat exchanger. Boehmite alumina (γ-AlOOH) nanoparticles of different shapes (cylindrical, brick, blade, platelet, and spherical) are dispersed in a mixture of water/ethylene glycol as the nanofluid. The nanofluid and water flow in the tube side and annulus side of the heat exchanger, respectively. The effects of the Reynolds number and nanoparticle concentration on the frictional entropy generation rate, thermal entropy generation rate, total entropy generation rate and Bejan number are numerically analyzed for different nanoparticle shapes. The obtained results demonstrated that the nanofluids containing platelet shape and spherical shape nanoparticles have the highest and lowest rates of thermal, frictional, and total entropy generation, respectively. Additionally, it was found that the rates of thermal, frictional, and total entropy generation increase with an increase in the Reynolds number, while the opposite is true for the Bejan number. Furthermore, it was inferred from the obtained results that the increase of nanoparticle concentration results in higher frictional and total entropy generation rates and lower Bejan number.

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  • Al-Rashed, Abdullah A.A.A. & Ranjbarzadeh, Ramin & Aghakhani, Saeed & Soltanimehr, Mehdi & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Entropy generation of boehmite alumina nanofluid flow through a minichannel heat exchanger considering nanoparticle shape effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 724-736.
    • Handle: RePEc:eee:phsmap:v:521:y:2019:i:c:p:724-736
    DOI: 10.1016/j.physa.2019.01.106
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    1. Karimipour, Arash & Hemmat Esfe, Mohammad & Safaei, Mohammad Reza & Toghraie Semiromi, Davood & Jafari, Saeed & Kazi, S.N., 2014. "Mixed convection of copper–water nanofluid in a shallow inclined lid driven cavity using the lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 150-168.
    2. Hemmat Esfe, Mohammad & Rostamian, Hossein & Esfandeh, Saeed & Afrand, Masoud, 2018. "Modeling and prediction of rheological behavior of Al2O3-MWCNT/5W50 hybrid nano-lubricant by artificial neural network using experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 625-634.
    3. Safaei, Mohammad Reza & Karimipour, Arash & Abdollahi, Ali & Nguyen, Truong Khang, 2018. "The investigation of thermal radiation and free convection heat transfer mechanisms of nanofluid inside a shallow cavity by lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 515-535.
    4. Hemmat Esfe, Mohammad & Kamyab, Mohammad Hassan & Afrand, Masoud & Amiri, Mahmoud Kiannejad, 2018. "Using artificial neural network for investigating of concurrent effects of multi-walled carbon nanotubes and alumina nanoparticles on the viscosity of 10W-40 engine oil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 610-624.
    5. Karimipour, Arash & D’Orazio, Annunziata & Goodarzi, Marjan, 2018. "Develop the lattice Boltzmann method to simulate the slip velocity and temperature domain of buoyancy forces of FMWCNT nanoparticles in water through a micro flow imposed to the specified heat flux," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 729-745.
    6. Nafchi, Peyman Mirzakhani & Karimipour, Arash & Afrand, Masoud, 2019. "The evaluation on a new non-Newtonian hybrid mixture composed of TiO2/ZnO/EG to present a statistical approach of power law for its rheological and thermal properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 1-18.
    7. Hemmat Esfe, Mohammad & Reiszadeh, Mahdi & Esfandeh, Saeed & Afrand, Masoud, 2018. "Optimization of MWCNTs (10%) – Al2O3 (90%)/5W50 nanofluid viscosity using experimental data and artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 731-744.
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