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A Review of Multiphase Flow and Heat Transfer With Artificial Neural Networks

[+] Author Affiliations
Mihir Sen, K. T. Yang

University of Notre Dame, Notre Dame, IN

Paper No. IMECE2003-41761, pp. 79-86; 8 pages
doi:10.1115/IMECE2003-41761
From:
  • ASME 2003 International Mechanical Engineering Congress and Exposition
  • Heat Transfer, Volume 4
  • Washington, DC, USA, November 15–21, 2003
  • Conference Sponsors: Heat Transfer Division
  • ISBN: 0-7918-3718-1 | eISBN: 0-7918-4663-6, 0-7918-4664-4, 0-7918-4665-2
  • Copyright © 2003 by ASME

abstract

Artificial neural networks (ANNs) are useful for the prediction and control of complex systems in which it is difficult or impossible to do so from first principles. This is particularly true for many thermal systems due to the presence of complex fluid mechanics like turbulence or two-phase flows, lack of knowledge of exact material properties, complex geometries, etc. The applications of ANNs to thermal systems in general has been reviewed before by the present authors (Sen and Yang, 1999). As a continuation of this, there is a growing body of recent work related to multiphase flow and heat transfer which is the subject of this review. There are several areas of applications in multiphase flow and heat transfer to which ANN techniques have been applied. Roughly speaking they may be classified in the following manner: two-phase flow in pipes including flow regime identification in pipes and heat transfer in two-phase flows; multiphase flows and heat transfer in columns, towers, packed beds and other fluid-particle systems; heat transfer in evaporators; boiling heat transfer in liquid mixtures; heat transfer in manufacturing processes; and thermal processing of food. There is a detailed list of references that can be used for further information.

Copyright © 2003 by ASME

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