No abstract

No abstract

Purpose For an axial-flow compressor rotor, the upstream inflow conditions will vary as the aircraft faces harsh flight conditions (such as taking off, landing or maneuvering) or the whole compressor operates at off-design conditions. With the increase of upstream boundary layer thickness, the rotor blade tip will be loaded and the increased blade load will deteriorate the shock/boundary layer interaction and tip leakage flows, resulting in high aerodynamic losses in the tip region. The purpose of this paper is to achieve a better flow control for tip secondary flows and provide a probable design strategy for high-load compressors to tolerate complex upstream inflow conditions. Design/methodology/approach This paper presents an analysis and application of shroud wall optimization to a typical transonic axial-flow compressor rotor by considering the inlet boundary layer (IBL). The design variables are selected to shape the shroud wall profile at the tip region with the purpose of controlling the tip leakage loss and the shock/boundary layer interaction loss. The objectives are to improve the compressor efficiency at the inlet-boundary-layer condition while keeping its aerodynamic performance at the uniform condition. Findings After the optimization of shroud wall contour, aerodynamic benefits are achieved mainly on two aspects. On the one hand, the shroud wall optimization has reduced the intensity of the tip leakage flow and the interaction between the leakage and main flows, thereby decreasing the leakage loss. On the other hand, the optimized shroud design changes the shock structure and redistributes the shock intensity in the spanwise direction, especially weakening the shock near the tip. In this situation, the shock/boundary layer interaction and the associated flow separations and wakes are also eliminated. On the whole, at the inlet-boundary-layer condition, the compressor with optimized shroud design has achieved a 0.8 per cent improvement of peak efficiency over that with baseline shroud design without sacrificing the total pressure ratio. Moreover, the re-designed compressor also maintains the aerodynamic performance at the uniform condition. The results indicate that the shroud wall profile has significant influences on the rotor tip losses and could be properly designed to enhance the compressor aerodynamic performance against the negative impacts of the IBL. Originality/value The originality of this paper lies in developing a shroud wall contour optimization design strategy to control the tip leakage loss and the shock/boundary layer interaction loss in a transonic compressor rotor. The obtained results could be beneficial for transonic compressors to tolerate the complex upstream inflow conditions.

In a Boundary Layer Ingesting (BLI) propulsion system, the fan blades operate continuously under large-scale inflow distortions, degrading fan performance and overall aerodynamic benefits of the aircraft. Therefore, in preliminary design of a BLI propulsion system, it is necessary to evaluate the influence of fuselage boundary layer under different flight conditions on fan aerodynamic performance. However, a gap exists in the current computational methods for BLI fan performance evaluation. The three-dimensional full-annulus unsteady simulation is of high-fidelity but can be computationally expensive for design iterations. The low-order computational methods are cost-efficient but rely on loss models for accurate prediction. The conventional empirical or physics-based loss models show notable limitations under complex distortion-induced off-design working conditions in a BLI fan, especially in rotor tip region, compromising the reliability of low-order computational methods. To balance the accuracy and cost of loss prediction, the paper proposes a data-driven based tip flow loss prediction framework for BLI fan. It employs a neural network to build a surrogate model of complex non-uniform aerodynamic conditions for tip flow loss. Physical understandings of BLI fan inner flow fields are integrated into the data-driven modeling process, to further reduce the computational cost and improve the method's applicability. Not only does it have higher accuracy than the conventional physics-based loss models, but also consumes much fewer computational resources than the full-annulus time-accurate simulations.

No abstract