• DocumentCode
    2412097
  • Title

    Application of artificial neural networks modelling to spray impingement heat transfer

  • Author

    Awais, M.M. ; Aamir, M.A. ; Aamir, A.

  • Author_Institution
    Dept. of Comput. Sci., LUMS, Lahore, Pakistan
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    282
  • Lastpage
    291
  • Abstract
    Artificial neural networks (ANN) models were developed and applied to water spray cooling heat flux predictions. The model was applied to all the three regimes of heat transfer, namely nucleate boiling (where surface temperature is less than the one at critical heat flux), transition (where the surface temperature is less than the Leidenfrost temperature) and the film boiling (where the wall temperature is greater than the Leidenfrost temperature). The ANN model is well trained and proves to be an alternative numerical modelling technique to computational fluid dynamics (CFD) with numerical predictions comparable to the CFD predictions, but in real time mode.
  • Keywords
    cooling; digital simulation; heat transfer; neural nets; sprays; temperature control; Leidenfrost temperature; computational fluid dynamics; heat flux predictions; heat transfer; modelling; neural networks; nucleate boiling; water spray cooling; Artificial neural networks; Computational fluid dynamics; Computational modeling; Cooling; Heat transfer; Numerical models; Predictive models; Spraying; Temperature; Water heating;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century. Proceedings. IEEE International
  • Print_ISBN
    0-7803-7406-1
  • Type

    conf

  • DOI
    10.1109/INMIC.2001.995352
  • Filename
    995352