Civil aero-engine performance prediction using a low-order code and uncertainty quantification estimation

In the last decades, the attention for pollutant emissions in the civil air transport field has grown up continuously. Especially considering the performances of current turbofan engines, even a modest increase in overall efficiency can lead to great benefits in terms of emissions reduction. Therefore, dedicated performance prediction tools are mandatory in order to carry out an estimation of such outputs. The aim of the present study is to develop a procedure devoted to a preliminary output prediction of an aero engine for civil transportation and an uncertainty quantification analysis based on main performance parameters. For the first step, following the strategy already adopted in previous work on this topic [1], the GEnX, a high-bypass turbofan engine, has been considered as the reference cases. The main design characteristics available from the constructor for this engine have been employed to model the engine with a 0-D numerical tool (ESMS), developed by the University of Florence [2]. Great effor...