IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i12p2044-d837586.html
   My bibliography  Save this article

Conjugate Natural Convection of a Hybrid Nanofluid in a Cavity Filled with Porous and Non-Newtonian Layers: The Impact of the Power Law Index

Author

Listed:
  • Mohamed Omri

    (Deanship of Scientific Research, King Abdulaziz University, Jedda 21589, Saudi Arabia)

  • Muhammad Jamal

    (Department of Mathematics & Statistics, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistan)

  • Shafqat Hussain

    (Department of Mathematics, Capital University of Science and Technology, Islamabad 44000, Pakistan
    Institut für Angewandte Mathematik (LS III), Technische Universität, 44227 Dortmund, Germany)

  • Lioua Kolsi

    (Department of Mechanical Engineering, College of Engineering, Ha’il University, Ha’il 81451, Saudi Arabia)

  • Chemseddine Maatki

    (Mechanical Engineering Department, College of Engineering, Al Imam Mohammad Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia)

Abstract

This study deals with the effect of the power law index on the convective heat transfer of hybrid nanofluids in a square cavity divided into three layers. The effect of a solid fluid layer is also given attention. A two-dimensional system of partial differential equations is discretized by using the generalized finite element method (FEM). A FEM having cubic polynomials (P3) is employed to approximate the temperature and velocity components, whereas the pressure is approached using quadratic finite element functions. The discretized set of equations have been solved using Newton’s method. The numerical code which is used in this study has been validated by comparing with experimental findings. Mathematical simulations are performed for different sets of parameters, including the Rayleigh number (between 10 3 and 10 6 ), the power law index (between 0.6 to 1.8 ), Darcy number (between 10 − 6 to 10 − 2 ), undulation (between 1 and 5) and the thermal conductivity ratio (between 0.1 and 10). The results infer that a remarkable penetration of streamlines is figured out towards the porous hybrid layer as the power law index is increased. The average N u increases with increasing R a , and the maximum value is noted at R a = 10 6 . There is no much alteration observed for isotherms at the solid layer by increasing D a . The average N u decreases by increasing the undulations. The rate of heat transfer is enhanced at the heated boundary and solid fluid interface of the cavity by raising the ratio of thermal conductivity.

Suggested Citation

  • Mohamed Omri & Muhammad Jamal & Shafqat Hussain & Lioua Kolsi & Chemseddine Maatki, 2022. "Conjugate Natural Convection of a Hybrid Nanofluid in a Cavity Filled with Porous and Non-Newtonian Layers: The Impact of the Power Law Index," Mathematics, MDPI, vol. 10(12), pages 1-20, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:2044-:d:837586
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/12/2044/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/12/2044/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khodabandeh, Erfan & Safaei, Mohammad Reza & Akbari, Soheil & Akbari, Omid Ali & Alrashed, Abdullah A.A.A., 2018. "Application of nanofluid to improve the thermal performance of horizontal spiral coil utilized in solar ponds: Geometric study," Renewable Energy, Elsevier, vol. 122(C), pages 1-16.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Goutam Saha & Ahmed A.Y. Al-Waaly & Manosh C. Paul & Suvash C. Saha, 2023. "Heat Transfer in Cavities: Configurative Systematic Review," Energies, MDPI, vol. 16(5), pages 1-53, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bahrami, Mehrdad & Akbari, Mohammad & Bagherzadeh, Seyed Amin & Karimipour, Arash & Afrand, Masoud & Goodarzi, Marjan, 2019. "Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 159-168.
    2. Mahyari, Amirhossein Ansari & Karimipour, Arash & Afrand, Masoud, 2019. "Effects of dispersed added Graphene Oxide-Silicon Carbide nanoparticles to present a statistical formulation for the mixture thermal properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 98-112.
    3. Karimipour, Arash & Bagherzadeh, Seyed Amin & Taghipour, Abdolmajid & Abdollahi, Ali & Safaei, Mohammad Reza, 2019. "A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 89-97.
    4. Chen, Zhanxiu & Zheng, Dan & Wang, Jin & Chen, Lei & Sundén, Bengt, 2020. "Experimental investigation on heat transfer characteristics of various nanofluids in an indoor electric heater," Renewable Energy, Elsevier, vol. 147(P1), pages 1011-1018.
    5. Toghyani, S. & Afshari, E. & Baniasadi, E. & Shadloo, M.S., 2019. "Energy and exergy analyses of a nanofluid based solar cooling and hydrogen production combined system," Renewable Energy, Elsevier, vol. 141(C), pages 1013-1025.
    6. Yıldırım, Erdal & Yurddaş, Ali, 2021. "Assessments of thermal performance of hybrid and mono nanofluid U-tube solar collector system," Renewable Energy, Elsevier, vol. 171(C), pages 1079-1096.
    7. Peng, Yeping & Khaled, Usama & Al-Rashed, Abdullah A.A.A. & Meer, Rashid & Goodarzi, Marjan & Sarafraz, M.M., 2020. "Potential application of Response Surface Methodology (RSM) for the prediction and optimization of thermal conductivity of aqueous CuO (II) nanofluid: A statistical approach and experimental validatio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    8. Bretado-de los Rios, Mariana S. & Rivera-Solorio, Carlos I. & Nigam, K.D.P., 2021. "An overview of sustainability of heat exchangers and solar thermal applications with nanofluids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    9. Abu Shadate Faisal Mahamude & Muhamad Kamal Kamarulzaman & Wan Sharuzi Wan Harun & Kumaran Kadirgama & Devarajan Ramasamy & Kaniz Farhana & Rosli Abu Bakar & Talal Yusaf & Sivarao Subramanion & Belal , 2022. "A Comprehensive Review on Efficiency Enhancement of Solar Collectors Using Hybrid Nanofluids," Energies, MDPI, vol. 15(4), pages 1-26, February.
    10. Ahmed Elkhatat & Shaheen A. Al-Muhtaseb, 2023. "Combined “Renewable Energy–Thermal Energy Storage (RE–TES)” Systems: A Review," Energies, MDPI, vol. 16(11), pages 1-46, June.
    11. 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.
    12. Abu-Hamdeh, Nidal H. & Oztop, Hakan F. & Alnefaie, Khalid A. & Wae-hayee, Makatar, 2020. "Hydrothermal irreversibility analysis based on multi-criteria assessment in a modified spiral piping system utilized in solar ponds," Renewable Energy, Elsevier, vol. 162(C), pages 355-370.
    13. Santosh, R. & Kumaresan, G. & Pon Pavithiran, C.K. & Mathu, P. & Velraj, R., 2023. "Effect of geometric variation and solar flux distribution on performance enhancement of absorber tube thermal characteristics for compound parabolic collectors," Renewable Energy, Elsevier, vol. 210(C), pages 671-686.
    14. Dabiri, Soroush & Hashemi, Mohammadreza & Rahimi, Mohammadfazel & Bahiraei, Mehdi & Khodabandeh, Erfan, 2018. "Design of an innovative distributor to improve flow uniformity using cylindrical obstacles in header of a fuel cell," Energy, Elsevier, vol. 152(C), pages 719-731.
    15. Bagherzadeh, Seyed Amin & D’Orazio, Annunziata & Karimipour, Arash & Goodarzi, Marjan & Bach, Quang-Vu, 2019. "A novel sensitivity analysis model of EANN for F-MWCNTs–Fe3O4/EG nanofluid thermal conductivity: Outputs predicted analytically instead of numerically to more accuracy and less costs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 406-415.
    16. Abu-Hamdeh, Nidal H. & Bantan, Rashad A.R. & Khoshvaght-Aliabadi, Morteza & Alimoradi, Ashkan, 2020. "Effects of ribs on thermal performance of curved absorber tube used in cylindrical solar collectors," Renewable Energy, Elsevier, vol. 161(C), pages 1260-1275.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:2044-:d:837586. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.