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Hydrothermal analysis of turbulent boehmite alumina nanofluid flow with different nanoparticle shapes in a minichannel heat exchanger using two-phase mixture model

Author

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  • Alsarraf, Jalal
  • Moradikazerouni, Alireza
  • Shahsavar, Amin
  • Afrand, Masoud
  • Salehipour, Hamzeh
  • Tran, Minh Duc

Abstract

Exploring the effect of nanoparticle shape on the fluid flow characteristics of boehmite alumina nanofluid in a horizontal double-pipe minichannel heat exchanger is the goal of this study. The proposed boehmite alumina nanofluid could consist of dispersed cylindrical, brick, blade, platelet, and spherical shape nanoparticles in a mixture of water/ethylene glycol. In this study, the water and nanofluid pass through the annulus and tube side of the heat exchanger, respectively. To accurately simulate the behavior of nanofluid, the two phase mixture model is utilized in the simulation. In this investigation, the effect of different Reynolds numbers, nanoparticle concentrations and shapes versus important hydrothermal properties are investigated. The results show that, the spherical and platelet shape lead to the highest and lowest performance index of heat exchanger, respectively. Moreover, it is found that the rates of heat transfer, overall heat transfer coefficient, pressure drop, and pumping power increases with increase in Reynolds number and nanoparticle concentration, while the opposite trend is observed for performance index of the heat exchanger. For instance, at the Reynolds number of 20000, by boosting the nanoparticle concentration from 0.5 to 2%, the performance index for nanofluid containing platelet shape and spherical shape nanoparticles reduces by 130.63 and 3.88%, respectively.

Suggested Citation

  • Alsarraf, Jalal & Moradikazerouni, Alireza & Shahsavar, Amin & Afrand, Masoud & Salehipour, Hamzeh & Tran, Minh Duc, 2019. "Hydrothermal analysis of turbulent boehmite alumina nanofluid flow with different nanoparticle shapes in a minichannel heat exchanger using two-phase mixture model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 275-288.
  • Handle: RePEc:eee:phsmap:v:520:y:2019:i:c:p:275-288
    DOI: 10.1016/j.physa.2019.01.021
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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. 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.
    3. 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.
    4. Alipour, Pedram & Toghraie, Davood & Karimipour, Arash & Hajian, Mehdi, 2019. "Modeling different structures in perturbed Poiseuille flow in a nanochannel by using of molecular dynamics simulation: Study the equilibrium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 13-30.
    5. Goodarzi, Marjan & D’Orazio, Annunziata & Keshavarzi, Ahmad & Mousavi, Sayedali & Karimipour, Arash, 2018. "Develop the nano scale method of lattice Boltzmann to predict the fluid flow and heat transfer of air in the inclined lid driven cavity with a large heat source inside, Two case studies: Pure natural ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 210-233.
    6. Ahmadi Balootaki, Azam & Karimipour, Arash & Toghraie, Davood, 2018. "Nano scale lattice Boltzmann method to simulate the mixed convection heat transfer of air in a lid-driven cavity with an endothermic obstacle inside," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 681-701.
    7. 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.
    8. Mamourian, Mojtaba & Milani Shirvan, Kamel & Mirzakhanlari, Soroush, 2016. "Two phase simulation and sensitivity analysis of effective parameters on turbulent combined heat transfer and pressure drop in a solar heat exchanger filled with nanofluid by Response Surface Methodol," Energy, Elsevier, vol. 109(C), pages 49-61.
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    5. Sarafraz, M.M. & Tlili, I. & Tian, Zhe & Bakouri, Mohsen & Safaei, Mohammad Reza, 2019. "Smart optimization of a thermosyphon heat pipe for an evacuated tube solar collector using response surface methodology (RSM)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    6. Ruiqing Du & Dandan Jiang & Yong Wang, 2020. "Numerical Investigation of the Effect of Nanoparticle Diameter and Sphericity on the Thermal Performance of Geothermal Heat Exchanger Using Nanofluid as Heat Transfer Fluid," Energies, MDPI, vol. 13(7), pages 1-18, April.
    7. Shafee, Ahmad & Arabkoohsar, A. & Sheikholeslami, M. & Jafaryar, M. & Ayani, M. & Nguyen-Thoi, Trung & Basha, D. Baba & Tlili, I. & Li, Zhixiong, 2020. "Numerical simulation for turbulent flow in a tube with combined swirl flow device considering nanofluid exergy loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    8. Sumera Dero & Azizah Mohd Rohni & Azizan Saaban & Ilyas Khan, 2019. "Dual Solutions and Stability Analysis of Micropolar Nanofluid Flow with Slip Effect on Stretching/Shrinking Surfaces," Energies, MDPI, vol. 12(23), pages 1-20, November.
    9. Khan, Kashif Ali & Seadawy, Aly R. & Raza, Nauman, 2022. "The homotopy simulation of MHD time dependent three dimensional shear thinning fluid flow over a stretching plate," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    10. Moghadam, Iman Panahi & Afrand, Masoud & Hamad, Samir M. & Barzinjy, Azeez A. & Talebizadehsardari, Pouyan, 2020. "Curve-fitting on experimental data for predicting the thermal-conductivity of a new generated hybrid nanofluid of graphene oxide-titanium oxide/water," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).

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