Turbofan engine performance prediction methodology integrated high-fidelity secondary air system models

Abstract

This research studies the performance of an ultra-high bypass ratio turbofan engine, and specifically its secondary air system (SAS). A co-simulation methodology is explored whereby a high-fidelity SAS model and an engine performance code featuring flexible modules can be coupled and interactively executed. The percentage of bleed flows and boundary conditions for the SAS are updated at each iteration step. For this purpose, a SAS model including different elements is developed. Furthermore, a commercial computational fluid dynamics (CFD) solver is adopted to capture the complex flow field in the pre-swirl system. The credibility of cycle calculation and SAS elements is validated by comparing with publicly available data. Subsequently, an elaborately designed SAS is modeled and co-simulated with the AGTF30 engine using a flow network simulation method. The coupling effect between the engine performance and the SAS is studied for eight different flight conditions. The correlation and prediction of engine performance due to seal clearance change is presented. The co-simulation approach clarifies the mutual interactions between the engine overall parameters and the SAS. The results reveal that the enhanced flow network model can improve the simulation accuracy of engine performance over a wide range of operating conditions.