Physics-Based Online Assessment of Surface Roughness Severity for High-Pressure Turbines

Abstract

Surface roughness is a critical indicator of the health of turbine blades, due to its implications on blade surface heat transfer and structural integrity. The present work proposes a physics-based online assessment framework for industrial gas turbine engines (GTE), in order to assess the blade surface roughness in a high-pressure turbine without engine shutdown. The framework consolidates gas path analysis (GPA) based performance monitoring models and meanline turbomachinery analysis using a novel GPA-meanline matching process. This extracts meaningful performance deviation trends from GPA, while resolving the uncertainties associated with the measurements and modeling. To relate efficiency loss to surface roughness severity, a meanline-based system-identification process has been developed to establish the meanline representation of the turbine stage and to incorporate an empirical surface roughness loss correlation system. The roughness loss correlations have been evaluated against recent transonic test data in the literature. A modification to the compressibility correction factor has been made according to the evaluation outcome, which yielded improved loss predictions compared to the experimental measurements.The successful application of the framework on three-year operational data of a cogenerative GTE validated the framework's potential as an effective online surface roughness monitoring tool. The estimated surface roughness index achieved magnitudelevel and trend agreement with the measurements reported in the literature.iii "No, in all these things we are more than conquerors through him who loved us." -Romans 8:37, ESV iv Acknowledgements I wish to thank my supervisor, Professor Jie Liu, for providing me the opportunity to work on this research project. This work could not have been accomplished without his encouragement and sound advice. I would also like to gratefully acknowledge my supervisor from my fourth-year capstone project, Professor Steen A. Sjolander, for introducing me to the field of turbomachinery. I am also truly grateful for his intermittent, but invaluable, guidance and encouragement over the course of this work.