A Comprehensive Computational Framework for Damage Assessment of Turbine Blades Considering Multidamage Mechanism and Service History

Abstract

The increasing diversity of missions complicates damage accumulation in gas turbine engines, presenting challenges for predictive maintenance. This study proposes a comprehensive framework that correlates engine operating history with cumulative blade damage. A data-driven reduced-order model, based on system identification theory, establishes a mapping between engine flight history and the local temperature and stress states of the blade. Additionally, a multimechanism damage analysis method addresses the geometric complexities and thermal-mechanical coupling of turbine blades. The framework investigates the impact of engine service conditions on service damage to high-pressure turbine blades, defining load severity based on damage. The load severity of the mission was defined based on damage. Compared to traditional methods, the framework effectively identifies load severity and the proportion of different damage mechanisms. Load severities calculated for four missions ranged from 0.22 to 2.97. This damage assessment framework has significant potential for maintenance and research in gas turbine engines and other hot-section components.