Volume 2A: Turbomachinery 2015
DOI: 10.1115/gt2015-43515
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Capabilities of Thermal Wall Functions to Predict Heat Transfer on the NGVs of a Gas Turbine With Multiple Can Combustors

Abstract: Modern gas turbine combustion systems are characterised by enhanced air/fuel mixing and this results in more diffused and redistributed hot streaks leading to higher thermal loads established on the vane surface and endwalls. Thus, a detailed aero-thermal characterization of the near-wall region has become crucial both for the analysis of turbine performances and for the subsequent design of special features, such as the use of advanced materials and/or novel efficient cooling concepts. In order to investigate… Show more

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Cited by 6 publications
(2 citation statements)
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“…The steady simulations used the mixing length approach (which allows the tuning of two parameters, namely the free stream turbulence level and the free stream mixing length) as a turbulence model which was calibrated against experimental measurements for this study. Heat transfer prediction capabilities and temperature wall functions were implemented by Mazzoni [41].…”
Section: Experimental Facilitymentioning
confidence: 99%
“…The steady simulations used the mixing length approach (which allows the tuning of two parameters, namely the free stream turbulence level and the free stream mixing length) as a turbulence model which was calibrated against experimental measurements for this study. Heat transfer prediction capabilities and temperature wall functions were implemented by Mazzoni [41].…”
Section: Experimental Facilitymentioning
confidence: 99%
“…The heat transfer prediction capabilities and different temperature wall functions, which were validated against experimental measurements conducted on the same cascade used in this work, were added by Mazzoni et al (2015). Heat transfer coefficient distributions are obtained by comparing the difference in wall heat flux of two iso-thermal simulations (with differing wall temperatures).…”
Section: Flow Solvermentioning
confidence: 99%