IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i7p1660-d1621170.html
   My bibliography  Save this article

Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects

Author

Listed:
  • Ahmed Zeeshan

    (Department of Mathematics & Statistics, Faculty of Sciences, International Islamic University Islamabad, H-10, Islamabad 44000, Pakistan
    Department of Mathematics, College of Science, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea)

  • Majeed Ahmad Yousif

    (Department of Mathematics, College of Education, University of Zakho, Zakho 42002, Iraq)

  • Muhammad Imran Khan

    (Department of Mathematics & Statistics, Faculty of Sciences, International Islamic University Islamabad, H-10, Islamabad 44000, Pakistan)

  • Muhammad Amer Latif

    (Department of Mathematics, Faculty of Sciences, King Faisal University, Hofuf 31982, Saudi Arabia)

  • Syed Shahzad Ali

    (Department of Mathematics & Statistics, Faculty of Sciences, International Islamic University Islamabad, H-10, Islamabad 44000, Pakistan)

  • Pshtiwan Othman Mohammed

    (Department of Mathematics, College of Education, University of Sulaimani, Sulaimani 46001, Iraq)

Abstract

Highlighting the importance of artificial intelligence and machine learning approaches in engineering and fluid mechanics problems, especially in heat transfer applications is main goal of the presented article. With the advancement in Artificial Intelligence (AI) and Machine Learning (ML) techniques, the computational efficiency and accuracy of numerical results are enhanced. The theme of the study is to use machine learning techniques to examine the thermal analysis of MHD boundary layer flow of Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder embedded in a porous medium with heat source/sink and viscous dissipation effects. The considered base fluid is water ( H 2 O ) and hybrid nanoparticles titanium oxide ( T i O 2 ) and Copper oxide ( C u O ). The governing flow equations are nonlinear PDEs. Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. Artificial Neural Networks (ANNs) simulation approach is used to trained the networks to predict the solution behavior. Thermal boundary layer improves with the enhancement in the value of R d . The accuracy and reliability of ANNs predicted solution is addressed with computation of correlation index and residual analysis. The RMSE is evaluated [0.04892, 0.0007597, 0.0007596, 0.01546, 0.008871, 0.01686] for various scenarios. It is observed that when concentration of hybrid nanoparticles increases then thermal characteristics of the Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder.

Suggested Citation

  • Ahmed Zeeshan & Majeed Ahmad Yousif & Muhammad Imran Khan & Muhammad Amer Latif & Syed Shahzad Ali & Pshtiwan Othman Mohammed, 2025. "Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects," Energies, MDPI, vol. 18(7), pages 1-40, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1660-:d:1621170
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/7/1660/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/7/1660/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Muhammad Imran Khan & Ahmad Zeeshan & Rahmat Ellahi & Muhammad Mubashir Bhatti, 2024. "Advanced Computational Framework to Analyze the Stability of Non-Newtonian Fluid Flow through a Wedge with Non-Linear Thermal Radiation and Chemical Reactions," Mathematics, MDPI, vol. 12(10), pages 1-24, May.
    2. Hina Firdous & Syed Tauseef Saeed & Hijaz Ahmad & Sameh Askar, 2021. "Using Non-Fourier’s Heat Flux and Non-Fick’s Mass Flux Theory in the Radiative and Chemically Reactive Flow of Powell–Eyring Fluid," Energies, MDPI, vol. 14(21), pages 1-16, October.
    3. Meng Yang & Munawwar Ali Abbas & Wissam Sadiq Khudair, 2021. "Energy and Temperature-Dependent Viscosity Analysis on Magnetized Eyring-Powell Fluid Oscillatory Flow in a Porous Channel," Energies, MDPI, vol. 14(23), pages 1-13, November.
    Full references (including those not matched with items on IDEAS)

    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. Hassan, Waqar Ul & Shabbir, Khurram & Zeeshan, Ahmed & Ellahi, Rahmat, 2025. "Regression analysis for thermal transport of fractional-order magnetohydrodynamic Maxwell fluid flow under the influence of chemical reaction using integrated machine learning approach," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).

    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:jeners:v:18:y:2025:i:7:p:1660-:d:1621170. 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.