The influence of the moving endwall on the behavior of the tip leakage flow in compressors holds substantial significance. This work investigates the unsteadiness of the compressor's tip leakage flow under the impact of the moving endwall, employing both experimental methods and unsteady Reynolds-averaged Navier–Stokes (URANS) simulations. First, a numerical decomposition technique is proposed to isolate the tip leakage flow within a controlled diffusion airfoil (CDA) cascade. Subsequently, URANS simulations based on the CDA cascade are conducted at various incidence angles (−6° to +7°), tip clearances (clearance to chord: 0.83% to 3.33%), and flow coefficients (0.4 to 0.6), and additional URANS simulations based on the Virginia Tech cascade are also performed. The results indicate that the moving endwall induces a greater inclination of the tip leakage flow in the pitchwise direction, allowing it to impinge upon the pressure side of the adjacent blade. The impingement, if sufficiently intense, leads to the periodic generation of unsteady tip leakage flow by altering the blade loading. Moreover, the degree of unsteadiness diminishes significantly as the endwall speed and clearance height decrease. Additionally, it is observed that the breakdown of the tip leakage vortex does not serve as the root cause of the periodic unsteadiness. These findings underscore the critical role played by the moving endwall in the unsteadiness of the compressor's tip leakage flow.

The cavity flow of shrouded stators is quite complex and not yet completely understood, especially for its loss characteristics. In this paper, a matrix of numerical simulations was designed and conducted to investigate the loss characteristics of the cavity flow in a compressor cascade, with a wide range of incidence, two flow coefficients, and three seal clearances. The effect of the skewed boundary layer was introduced to simulate the practical compressor environment as far as possible. The results show that the total pressure loss coefficient is unable to evaluate the cavity leakage loss correctly since it ignores the temperature rise. With the reduction of the flow coefficient, the entropy loss coefficient and thermal entropy generation rate tend to increase, while the change of the viscous entropy generation rate is dependent on the incidence since the high tangential velocity deteriorates the flow of the pressure side at large negative incidence but significantly improves the flow of the suction side as the incidence increases. In addition, there is a significant difference in loss sensitivity to the seal clearance at various incidences. One of the major reasons is the change of pressure difference between the downstream and upstream. And the other major reason is the distribution difference of the high-loss fluid caused by the variation in the passage vortex. These key findings are able to provide insights leading to reducing the compressor loss due to the cavity leakage flow.

Deep transfer learning is frequently employed to address the challenges arising from limited or hard-to-obtain training data in the target domain, but its application in axial compressors has been scarcely explored thus far. In this paper, a multi-objective optimization framework of a transonic rotor is established using deep transfer learning. This framework first pre-trains deep neural networks based on the peak efficiency condition of 100% design speed and then fine-tunes the networks to predict the performance of off-design conditions based on the small training dataset. Finally, the design optimization of the transonic rotor is carried out through non-dominated sorting genetic algorithm II. Compared to neural networks that are trained directly, transfer learning models can achieve higher prediction accuracy, particularly in scenarios with small training datasets. This is because the pre-trained weights can offer a better initial state for transfer learning models. Moreover, transfer learning models can use fewer samples to obtain an approximate Pareto front, making the optimized rotor increase the isentropic efficiency at both peak efficiency and high loading conditions. The efficiency improvement of the optimized rotor is attributed to the reduction of the loss associated with the tip leakage flow by adjusting the tip loading distribution. Overall, this study fully demonstrates the effectiveness of transfer learning in predicting compressor performance, which provides a promising approach to solving high-cost compressor design problems.

The moving endwall has a great influence on the development and stability of axial compressor leakage flow. This paper presents a novel experimental facility with a high-speed moving endwall for studying axial compressor leakage flow. The uniqueness of the design concept is that using a large disk simulates the high-speed moving endwall. When R/C_x = 16, theoretical analysis shows that the maximum linear velocity difference is about 2.5% while the maximum axial velocity difference of the mid-three passages is less than 5%. Single-passage simulations show that the disk radius of R/C_x = 16 can achieve an acceptable accuracy in terms of static pressure, total pressure, and density flow. Seven-passage simulations confirm that the mid-three passages have small errors from the axial velocity difference. Subsequently, preliminary experimental results obtained from the experimental facility are presented. The results reveal that the moving endwall significantly changes the distributions of the total pressure loss and static pressure coefficient. The relative difference in the averaged total pressure loss between the experiment and CFD is 11.33% and 7.69% for the static and moving endwall, respectively. It is expected that the experimental facility will make more useful contributions to the understanding of axial compressor leakage flow in the future.

Next-generation boundary layer ingesting (BLI) aircraft can achieve significant reductions in fuel burns compared to conventional aircraft. One of the challenges for BLI aircraft is the need for the fan to continuously operate with inlet distortions. However, until now the effect of real BLI distortions on rotating stall remains unclear. In this work, full-annulus unsteady simulations are conducted to analyze the mechanism of rotating stalls in a boundary layer ingesting fan. The complete stall hysteresis loop at BLI distortions is investigated. Similar to the uniform inflow, the fan at the BLI distortions also exhibits the spike-type rotating stalls, and its stall inception is also attributed to the radial vortex structure caused by the shear interaction between the incoming flow and backflow. However, at the BLI distortions, the evolution process of rotating stall is accompanied by the growth and decay of disturbances because of the significant variation of the inflow condition around the whole annulus. Only when the stall disturbance becomes large enough can it propagate circumferentially across the whole annulus to form the full stall cell. In addition, due to the significant decrease in total pressure ratio, the fan at the BLI distortions is easier to exit the rotating stall compared to the uniform inflow. These results enhance the understanding of the rotating stall mechanism not only for BLI fans but also for many turbine engines that suffer from inlet distortions.