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Prediction of Low Temperature Hot Corrosion Rate in Film Cooled Coal Fired Gas Turbines

[+] Author Affiliations
Vaidyanathan Krishnan, Sanjeev Bharani, J. S. Kapat, Y. H. Sohn, V. H. Desai

University of Central Florida, Orlando, FL

Paper No. IMECE2003-41541, pp. 45-54; 10 pages
doi:10.1115/IMECE2003-41541
From:
  • ASME 2003 International Mechanical Engineering Congress and Exposition
  • Heat Transfer, Volume 2
  • 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

The concept of coal based gas turbine power plants has drawn considerable interest in recent years. Coal or syngas based power plants like IGCC have shown significant potential for meeting the ever-increasing power demands as well as stricter environmental regulations. The trouble free operational life of such power plants is limited by a major factor namely hot corrosion of the turbine components. Hitherto, the mechanism of hot corrosion has been investigated in a simpler context, which is not directly applicable to gas turbines in the presence of film cooling techniques. The present paper is an attempt to model hot corrosion in the presence of film cooling relevant to gas turbines, using a simple resistance model and the inherent analogy between heat and mass transfer. This paper considers film cooling air temperatures in the range of 450°C to 550°C, and a free stream gas temperature of 1425°C, with 0.5% sulfur in the fuel. For lower cooling air temperatures (less than 500°C), film cooling air suppresses corrosion, whereas for higher cooling air temperature corrosion rate is more in the presence of film cooling. With film cooling, there is a sharp peak in corrosion rate close to the cooling hole (within 10 slot widths). Due to the possibility that the base superalloy may be exposed in this region, designers should consider the high corrosion rate seriously. However, the present model is limited in its prediction because of its simplicity. Further improvement of the model is essential for optimization purposes.

Copyright © 2003 by ASME

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