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Heat Transfer Analysis of a Gas Turbine and Improving Predictability Using Prototype Test Data

[+] Author Affiliations
T. Vishnu Vardhan Reddy

GE Oil & Gas, Bangalore, India

Roberto De Prosperis

GE Oil & Gas, Firenze, Italy

Paper No. GTINDIA2013-3701, pp. V001T04A010; 10 pages
  • ASME 2013 Gas Turbine India Conference
  • ASME 2013 Gas Turbine India Conference
  • Bangalore, Karnataka, India, December 5–6, 2013
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5616-1
  • Copyright © 2013 by ASME


Gas turbines are extremely complex & expensive machines that are subjected to various operating and environmental conditions. Increased customer attention towards higher efficiency is driving the industry to move to higher firing temperatures, which imparts higher thermal & mechanical loads on engine components. This in turn demands higher reliability levels for the engine components to ensure availability and safety of the machine. An effective modeling approach, which can accurately predict the thermal behavior of various components of a gas turbine, can be used to understand the critical regions, locate probable areas of failure, and to improve the overall design.

This paper presents a methodology to perform steady state thermal analysis of gas turbine flange to flange components (excluding the main flow path,) using a 2D FE model. A brief overview of the in-house tools and the modeling approach adopted to capture the complex physics using these tools are discussed. The results from this FE analysis are rigorously validated with data collected from various test campaigns of GE industrial Frame5 gas turbines. Several sensitivity studies were performed to study the impact of the uncertainties and to improve the thermal predictions compared to measurements. Studies using CFD tools and hand calculations were also performed to validate assumptions. This approach gives a thorough understanding of how a vast thermal model of gas turbine is developed and validated using test data, resulting in the improvement of thermal predictions of critical components.

Copyright © 2013 by ASME



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