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The development and application of digital twins in aircraft engine maintenance represents a paradigm shift towards more efficient, accurate and predictive maintenance strategies. This study introduces an end-to-end process using a turbine blade as a case study to demonstrate the potential of digital twin technology in maintenance practice. High-resolution cameras are used in a generic environment to digitally capture the geometries of turbine blades to simulate the conditions of shop visits. These blades, taken from a test rig, have geometries that include manufacturing faults, providing a viable basis for the digitalization process. The resulting models are used for Computational Fluid Dynamics (CFD) as well as Computational Structural Mechanics (CSM) simulations. By comparing the captured geometries with optimal design models, the methodology enables the precise identification of deviations. Additional integration of CFD simulations into the 0-D thermodynamic analysis, allowing the aerodynamic effects of blade degradation and damage to be evaluated in the context of overall engine operation. The research identifies critical bottlenecks, particularly in the conversion of the captured geometries into CAD models and their integration into CFD and CSM analysis, and investigates solutions to these challenges.
Reitenbach et al. (Fri,) studied this question.