IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v254y2015icp392-407.html
   My bibliography  Save this article

Towards computationally-efficient modeling of transport phenomena in three-dimensional monolithic channels

Author

Listed:
  • Sharma, A.K.
  • Birgersson, E.
  • Vynnycky, M.

Abstract

In general, three-dimensional (3D) non-isothermal models for monolithic channels that seek to capture the local transport phenomena are computationally expensive. In this regard, we present a reduced model for a monolithic channel that reduces the computational cost, whilst preserving the 3D geometry and all of the essential physics – this is accomplished by exploiting the inherent slenderness of the monolith channel, coupled with scaling arguments, leading-order asymptotics and a fast space-marcher. The model takes into account conservation of mass, momentum, species and energy coupled with chemical kinetics, and is demonstrated for a three-way reaction mechanism for treatment of automotive exhaust. The results of the reduced model are verified against those of the full model and validated with axial temperature distributions for an experimental square channel. Overall, memory requirements and computing time are reduced by around 2–3 orders of magnitude as compared to the full set of equations. Finally, we discuss the suitability of the reduced model for reactor-scale modeling and extensions for transient simulations and other slender chemical engineering systems.

Suggested Citation

  • Sharma, A.K. & Birgersson, E. & Vynnycky, M., 2015. "Towards computationally-efficient modeling of transport phenomena in three-dimensional monolithic channels," Applied Mathematics and Computation, Elsevier, vol. 254(C), pages 392-407.
  • Handle: RePEc:eee:apmaco:v:254:y:2015:i:c:p:392-407
    DOI: 10.1016/j.amc.2015.01.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300315000569
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2015.01.042?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 search for a different version of it.

    Citations

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


    Cited by:

    1. Kannan, Vishvak & Xue, Hansong & Raman, K. Ashoke & Chen, Jiasheng & Fisher, Adrian & Birgersson, Erik, 2020. "Quantifying operating uncertainties of a PEMFC – Monte Carlo-machine learning based approach," Renewable Energy, Elsevier, vol. 158(C), pages 343-359.
    2. Inbamrung, Piyanut & Sornchamni, Thana & Prapainainar, Chaiwat & Tungkamani, Sabaithip & Narataruksa, Phavanee & Jovanovic, Goran N., 2018. "Modeling of a square channel monolith reactor for methane steam reforming," Energy, Elsevier, vol. 152(C), pages 383-400.
    3. Sharma, A.K. & Birgersson, E., 2016. "Validity and scalability of an asymptotically reduced single-channel model for full-size catalytic monolith converters," Applied Mathematics and Computation, Elsevier, vol. 281(C), pages 186-198.

    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:apmaco:v:254:y:2015:i:c:p:392-407. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.