IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v124y2014icp223-230.html
   My bibliography  Save this article

Experimental assessment of a fully predictive CFD approach, for flow of cooling air in an electric generator

Author

Listed:
  • Moradnia, Pirooz
  • Chernoray, Valery
  • Nilsson, Håkan

Abstract

A fully predictive computational fluid dynamics approach is assessed for the flow of cooling air in an axially cooled electric generator. The flow is driven solely by the rotation of the rotor, as in the real application. A part of the space outside the generator is included in the computational domain to allow for the flow of air into and out of the machine. This yields a flow prediction that is determined without the input of any experimental data. Two different choices of ‘surrounding’ outer boundary conditions are studied, and the mesh sensitivity is discussed.

Suggested Citation

  • Moradnia, Pirooz & Chernoray, Valery & Nilsson, Håkan, 2014. "Experimental assessment of a fully predictive CFD approach, for flow of cooling air in an electric generator," Applied Energy, Elsevier, vol. 124(C), pages 223-230.
    • Handle: RePEc:eee:appene:v:124:y:2014:i:c:p:223-230
    DOI: 10.1016/j.apenergy.2014.02.064
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261914002098
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2014.02.064?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.

    References listed on IDEAS

    as
    1. Moradnia, Pirooz & Golubev, Maxim & Chernoray, Valery & Nilsson, Håkan, 2014. "Flow of cooling air in an electric generator model – An experimental and numerical study," Applied Energy, Elsevier, vol. 114(C), pages 644-653.
    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. Yu, Yan S.W. & Sun, Daming & Zhang, Jie & Xu, Ya & Qi, Yun, 2017. "Study on a Pi-type mean flow acoustic engine capable of wind energy harvesting using a CFD model," Applied Energy, Elsevier, vol. 189(C), pages 602-612.
    2. Yan Wang & Qing Gao & Tianshi Zhang & Guohua Wang & Zhipeng Jiang & Yunxia Li, 2017. "Advances in Integrated Vehicle Thermal Management and Numerical Simulation," Energies, MDPI, vol. 10(10), pages 1-30, October.

    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.

      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:appene:v:124:y:2014:i:c:p:223-230. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

      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.