Meta-Analysis of Thermal Barrier Coating Lifetimes in High-Water Vapor Environments: Implications for High-Hydrogen Gas Turbines

Abstract Thermal barrier coatings (TBC) are used to protect hot-section components, including combustor liners, turbine blades and vanes, and shrouds in gas turbine hot sections. Because improvements in combined-cycle gas turbine efficiency largely depend on the ability to increase operating temperatures, TBC failure mechanisms in high-temperature, cycling environments have been well researched. However, the advent of high hydrogen fueled gas turbine operation will add new challenges for TBCs, particularly through increased water vapor concentration in the combustion product gases. Although previous studies have suggested that water vapor has a detrimental effect on TBC lifetime, there has been no systematic analysis of this effect and many of the controlling factors, including TBC composition, thickness, application method, etc., have not been fully characterized. In this study, data were collected for furnace cycle testing (FCT) of TBCs in environments with various levels of moisture to better understand how the presence of water vapor couples with processing and environmental variables to affect TBC lifetime. Data were extracted from 45 studies and analyzed using two methods. First, traditional regression analysis was used to understand the level of coupling between factors. Second, an artificial neural network (ANN) framework was used to augment the traditional regression analysis to identify key sensitivities. The regression analysis did not fit the data well, with an adjusted R2 less than 0.1. Conversely, the ANN generally succeeded at predicting TBC lifetime close to the median with an adjusted R2 of 0.682 for the validation set and seemed to indicate coupling between water vapor and bond coat processing strategies. Better knowledge of the impact of water vapor on TBC or the interaction between water vapor and certain TBC processing parameters may lead to alternative maintenance cycles and thus potential for increased budget considerations at gas turbine power plants.

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Publication Details

Journal
Journal of Engineering for Gas Turbines and Power
Published
2025-08-30
DOI
https://doi.org/10.1115/1.4069579
Primary Topic
Rocket and propulsion systems research
Type
article
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article

Meta-Analysis of Thermal Barrier Coating Lifetimes in High-Water Vapor Environments: Implications for High-Hydrogen Gas Turbines

Michael Gagliano, David R. Noble, Jacqueline O’Connor, C.W. Clark et al.
Journal of Engineering for Gas Turbines and Power
Rocket and propulsion systems research
article

Meta-Analysis of Thermal Barrier Coating Lifetimes in High-Water Vapor Environments: Implications for High-Hydrogen Gas Turbines

Michael Gagliano, David R. Noble, Jacqueline O’Connor, C.W. Clark, Alex Bridges, Paige Doerr
article en

Abstract

Abstract Thermal barrier coatings (TBC) are used to protect hot-section components, including combustor liners, turbine blades and vanes, and shrouds in gas turbine hot sections. Because improvements in combined-cycle gas turbine efficiency largely depend on the ability to increase operating temperatures, TBC failure mechanisms in high-temperature, cycling environments have been well researched. However, the advent of high hydrogen fueled gas turbine operation will add new challenges for TBCs, particularly through increased water vapor concentration in the combustion product gases. Although previous studies have suggested that water vapor has a detrimental effect on TBC lifetime, there has been no systematic analysis of this effect and many of the controlling factors, including TBC composition, thickness, application method, etc., have not been fully characterized. In this study, data were collected for furnace cycle testing (FCT) of TBCs in environments with various levels of moisture to better understand how the presence of water vapor couples with processing and environmental variables to affect TBC lifetime. Data were extracted from 45 studies and analyzed using two methods. First, traditional regression analysis was used to understand the level of coupling between factors. Second, an artificial neural network (ANN) framework was used to augment the traditional regression analysis to identify key sensitivities. The regression analysis did not fit the data well, with an adjusted R2 less than 0.1. Conversely, the ANN generally succeeded at predicting TBC lifetime close to the median with an adjusted R2 of 0.682 for the validation set and seemed to indicate coupling between water vapor and bond coat processing strategies. Better knowledge of the impact of water vapor on TBC or the interaction between water vapor and certain TBC processing parameters may lead to alternative maintenance cycles and thus potential for increased budget considerations at gas turbine power plants.

Journal of Engineering for Gas Turbines and PowerVol. 148(1)
Pennsylvania State University (US), Electric Power Research Institute (US)
Openalex Percentile: Top 69%
Rocket and propulsion systems research
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