IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v198y2025ics0960077925005685.html

Biological waste to energy conversion and hydrogen production utilizing statistical analysis of motile number for radiation absorption on bio-convective MHD flow of Williamson nanofluid

Author

Listed:
  • Mishra, S.R.
  • Ontela, Surender
  • Baithalu, Rupa
  • Panda, Subhajit

Abstract

The non-Newtonian behavior distinguished by the Williamson nanofluid is enriched with the Brownian motion of the nanoparticles that enhance thermal conductivity and radiation absorption. Moreover, bio-convection is useful in enhanced nutrient transport due to the motility of microorganisms, which is vital for microbial energy conversion processes. The current study aims to investigate the magneto-driven bio-convective transport of non-Newtonian Williamson nanofluid that is useful in converting organic waste to energy and hydrogen production processes. The inclusion of inertial drag, magnetic field, and higher-order chemical reaction provides a broad model for the thermal and solutal transport phenomena. The role of drag, representing resistance to flow through a permeable medium, magnetization that induces Lorentz forces, is presented to optimize the fluid motion and heat transfer. The utilization of chemical reactions within the system is to simulate hydrogen production through thermochemical processes. The modelled problem is in dimensional form and appropriate similarity transformations are adopted for the reformulation of the model into dimensionless. Further, a traditional numerical scheme i.e. shooting-based Runge-Kutta fourth-order is proposed for the solution of the transformed phenomena. More appropriately, a statistical method likely “response surface methodology” (RSM) is utilized to assess the influence of motile numbers with the variation of numerous factors. Finally, the result demonstrates that the bio-convection, MHD flow, and nanofluid properties significantly enhance waste-to-energy conversion and hydrogen production.

Suggested Citation

  • Mishra, S.R. & Ontela, Surender & Baithalu, Rupa & Panda, Subhajit, 2025. "Biological waste to energy conversion and hydrogen production utilizing statistical analysis of motile number for radiation absorption on bio-convective MHD flow of Williamson nanofluid," Chaos, Solitons & Fractals, Elsevier, vol. 198(C).
  • Handle: RePEc:eee:chsofr:v:198:y:2025:i:c:s0960077925005685
    DOI: 10.1016/j.chaos.2025.116555
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077925005685
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2025.116555?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. J. Bouslimi & M. Omri & R. A. Mohamed & K. H. Mahmoud & S. M. Abo-Dahab & M. S. Soliman, 2021. "MHD Williamson Nanofluid Flow over a Stretching Sheet through a Porous Medium under Effects of Joule Heating, Nonlinear Thermal Radiation, Heat Generation/Absorption, and Chemical Reaction," Advances in Mathematical Physics, Hindawi, vol. 2021, pages 1-16, July.
    2. J. Bouslimi & M. Omri & R. A. Mohamed & K. H. Mahmoud & S. M. Abo-Dahab & M. S. Soliman, 2021. "MHD Williamson Nanofluid Flow over a Stretching Sheet through a Porous Medium under Effects of Joule Heating, Nonlinear Thermal Radiation, Heat Generation/Absorption, and Chemical Reaction," Advances in Mathematical Physics, John Wiley & Sons, vol. 2021(1).
    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. Afridi, Muhammad Idrees & Almohsen, Bandar & Habib, Shazia & Khan, Zeeshan & Razzaq, Raheela, 2025. "Artificial neural network analysis of MHD Maxwell nanofluid flow over a porous medium in presence of Joule heating and nonlinear radiation effects," Chaos, Solitons & Fractals, Elsevier, vol. 192(C).
    2. Hillary Muzara & Stanford Shateyi, 2023. "Magnetohydrodynamics Williamson Nanofluid Flow over an Exponentially Stretching Surface with a Chemical Reaction and Thermal Radiation," Mathematics, MDPI, vol. 11(12), pages 1-18, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:chsofr:v:198:y:2025:i:c:s0960077925005685. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.