Investigation of near and post stall behaviour of axial compression systems

Abstract

The design of modern gas-turbine engines is continuously being improved towards better performance, better efficiency and reduced cost. This trend of aero-engine design requires compression systems which produce higher pressure ratios and thus, have higher loaded blades and a closer spacing between blade rows. Such designs are more prone to aerodynamic instabilities and consequent stall and surge can be catastrophic. The majority of the research conducted on compressor stall and surge is limited to old designs with lower pressure ratios or single stage compression systems. In this thesis, the near and post stall behaviour of a modern multi-stage high-speed intermediate pressure compressor rig and an aero-engine three-shaft compression system are studied in detail. The main objective is to develop and validate reliable CFD models to predict surge and rotating stall and shed light on the underlying physical mechanism of the phenomena. CFD computations were performed to gain understanding of the current capability to model the flow behaviour of a multi-stage compressor rig near stall condition. Two turbulence models were tested and an extensive grid discretization study was performed. In order to improve the prediction of the compressor's stability boundary, a modification in the widely known Spalart-Allmaras turbulence model is proposed. Subsequently, unsteady CFD computations were carried out to evaluate the impact of flow unsteadiness in the performance prediction of this compressor rig. It was found that for operating conditions characterized by non-axisymmetric flow features, an unsteady full annulus model is required to predict the compressor performance. For low speeds, these flow features develop over a wide range of operating conditions. When the compressor operates at high speeds, these flow features are limited to operating conditions near the stability boundary. The above findings were validated against experimental results. Early stages of this research revealed that numerical calibration of a CFD surge computation in a three-shaft engine is a challenging task due to compressor matching. Hence, an iterative methodology for matching the compressors was introduced and validated against experimental data. This study considered a surge event where the engine was initially operating at mid power condition. When comparing the numerical result with measured data, it was found that the engine bleed system has a major impact on the aerodynamic loading predictions in the core system. Therefore, this system needs to be considered by component designers when accounting for robustness to surge loads. The post stall response of a three-shaft engine compression system which is initially operating at design was investigated. It was found that the maximum surge over-pressures are caused by a combined effect between a surge induced shock wave and high pressure gas travelling towards the core inlet during the surge blow-down period. Furthermore, it was demonstrated that the maximum surge loads are obtained for a surge event initiated by fuel-spike. Finally, a cheaper computational approach to model surge in axial compression systems is proposed. This approach consisted of using an unsteady single passage model to predict the flow behaviour during the surge event. After comparison with full annulus results for three different scenarios, it was concluded that the single passage is capable of predicting the blow-down period of surge which is characterized by a long period of flow reversal. This model fails to predict the correct time and length scales during surge onset and flow transition between reverse to forward flow at the beginning of recovery. These time instants are characterized by non-axisymmetric flow features. However, the single passage model shows a good correlation with the results obtained using a full annulus model for estimation of average values of static pressure and mass flows during surge. This can drastically reduce simulations times from months to days during compressor surge analysis.