Test and Validation of Turbofan Life Cycle Model

During its life, the jet engine's components can deteriorate and this can reduce the performances. It is very difficult to predict with analytic models how many flight hours time a component can bear, that's why it's very common to use safety factors in order to guarantee airworthiness.  As a result, there will be increased costs due to premature maintenance, increased downtime, and potential failure. The aim of Rolls-Royce is to create a digital service twin model capable of predicting the engine condition at the part level at any time during its life cycle. To support this work, this thesis aims to conduct a sensitivity study of a turbo engine lifecycle model and quantify the impact of model uncertainties on engine simulated performance as well as on component deterioration modes. An approximation model will be created and tested in order to estimate engine performances from ambient temperature, rate of climb and descent, aircraft mass, altitude, and true airspeed. The engine performances that will be considered are the total temperatures at the entrance of the high-pressure turbine and at the entrance of the combustor. These are the inputs to obtain NGVs' metal temperature thanks to an experimental formula. Input parameter errors depend on the use of ADS-B data instead of EHM data as input for the digital twin. Their influence on engine performances will result in an overprediction of component wear that can be taken into account with a corrective factor.