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A Significant Solar Energy Note on Powell-Eyring Nanofluid with Thermal Jump Conditions: Implementing Cattaneo-Christov Heat Flux Model

Author

Listed:
  • Nidal H. Abu-Hamdeh

    (Center of Research Excellence in Renewable Energy and Power Systems, and Department of Mechanical Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Radi A. Alsulami

    (Mechanical Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah 21511, Saudi Arabia)

  • Muhyaddin J. H. Rawa

    (Center of Research Excellence in Renewable Energy and Power Systems, Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Mashhour A. Alazwari

    (Mechanical Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah 21511, Saudi Arabia)

  • Marjan Goodarzi

    (Mechanical Engineering Department, Lamar University, Beaumont, TX 77706, USA
    Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 21521, Jeddah, Saudi Arabia)

  • Mohammad Reza Safaei

    (Department of Mechanical Engineering, Florida International University, Miami, FL 33174, USA
    Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan)

Abstract

PTSCs (parabolic trough solar collectors) are widely employed in solar-thermal applications to attain high temperatures. The purpose of this study is to determine how much entropy is created when Powell-Eyring nanofluid (P-ENF) flows across porous media on a horizontal plane under thermal jump circumstances. The flow in PTSC was generated by nonlinear surface stretching, thermal radiation, and Cattaneo-Christov heat flux, which was utilized to compute heat flux in the thermal boundary layer. Using a similarity transformation approach, partial differential equations were converted into ordinary differential equations with boundary constraints. Then, the boundary restrictions and partial differential equations were merged to form a single set of nonlinear ordinary differential equations. To obtain approximate solutions to ordinary differential equations, the Keller-Box approach is utilized. Nanofluids derived from silver- and copper-based engine oil (EO) has been employed as working fluids. The researchers observed that changing the permeability parameter reduced the Nusselt number while increasing the skin frictional coefficient. Total entropy variation was also calculated using the Brinkman number for flow rates with Reynolds number and viscosity changes. The key result is that thermal efficiency is inversely proportional to particular entropy production. For example, using Cu-EO nanofluid instead of Ag-EO nanofluid increased the heat transport rate efficiency to 15–36%.

Suggested Citation

  • Nidal H. Abu-Hamdeh & Radi A. Alsulami & Muhyaddin J. H. Rawa & Mashhour A. Alazwari & Marjan Goodarzi & Mohammad Reza Safaei, 2021. "A Significant Solar Energy Note on Powell-Eyring Nanofluid with Thermal Jump Conditions: Implementing Cattaneo-Christov Heat Flux Model," Mathematics, MDPI, vol. 9(21), pages 1-16, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:21:p:2669-:d:661658
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    References listed on IDEAS

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    1. Iqbal, Z. & Azhar, Ehtsham & Maraj, E.N., 2021. "Performance of nano-powders SiO2 and SiC in the flow of engine oil over a rotating disk influenced by thermal jump conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Mwesigye, Aggrey & Yılmaz, İbrahim Halil & Meyer, Josua P., 2018. "Numerical analysis of the thermal and thermodynamic performance of a parabolic trough solar collector using SWCNTs-Therminol®VP-1 nanofluid," Renewable Energy, Elsevier, vol. 119(C), pages 844-862.
    3. Hachicha, Ahmed Amine & Said, Zafar & Rahman, S.M.A. & Al-Sarairah, Eman, 2020. "On the thermal and thermodynamic analysis of parabolic trough collector technology using industrial-grade MWCNT based nanofluid," Renewable Energy, Elsevier, vol. 161(C), pages 1303-1317.
    4. Ebrahimi-Moghadam, Amir & Mohseni-Gharyehsafa, Behnam & Farzaneh-Gord, Mahmood, 2018. "Using artificial neural network and quadratic algorithm for minimizing entropy generation of Al2O3-EG/W nanofluid flow inside parabolic trough solar collector," Renewable Energy, Elsevier, vol. 129(PA), pages 473-485.
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    2. Taqi A. M. Shatnawi & Nadeem Abbas & Wasfi Shatanawi, 2022. "Mathematical Analysis of Unsteady Stagnation Point Flow of Radiative Casson Hybrid Nanofluid Flow over a Vertical Riga Sheet," Mathematics, MDPI, vol. 10(19), pages 1-17, September.

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