Flow separation, which often occurs at the junction of blades and endwalls and seriously limits the aerodynamic performance of turbomachinery, is caused mainly by the boundary layer mixing on the blades and endwall surfaces and the transverse secondary flow. Focusing on a linear diffusion cascade with 42° turning angle, the transverse secondary flow is found to be the dominant factor for flow separation, based on detailed analysis. Therefore, controlling the secondary flow to reduce the flow separation is very important. Based on the investigations, the flow separation can be controlled by cutting off the secondary flow. Therefore, nine kinds of streamwise grooves were designed and analyzed herein. Grooves at the endwall substantially inhibited the transverse secondary flow, but the flow structure varied over different spans. An optimum combination of groove width and height was identified, with the height being more important. A detailed flow analysis of the best scheme (with a smaller width and moderate height) was conducted. The loss reduction mechanism was obtained by 3D flow field and entropy analysis. This configuration can reduce the corner zone separation effect, energy loss coefficient, and flow loss.

The optimization of high-pressure ratio impeller with splitter blades is difficult because of large-scale design parameters, high time cost, and complex flow field. So few relative works are published. In this paper, an engineering-applied centrifugal impeller with ultrahigh pressure ratio 9 was selected as datum geometry. One kind of advanced optimization strategy including the parameterization of impeller with 41 parameters, high-quality CFD simulation, deep machine learning model based on SVR (Support Vector Machine), random forest, and multipoint genetic algorithm (MPGA) were set up based on the combination of commercial software and in-house python code. The optimization objective is to maximize the peak efficiency with the constraints of pressure-ratio at near stall point and choked mass flow. Results show that the peak efficiency increases by 1.24% and the overall performance is improved simultaneously. By comparing the details of the flow field, it is found that the weakening of the strength of shock wave, reduction of tip leakage flow rate near the leading edge, separation region near the root of leading edge, and more homogenous outlet flow distributions are the main reasons for performance improvement. It verified the reliability of the SVR-MPGA model for multiparameter optimization of high aerodynamic loading impeller and revealed the probable performance improvement pattern.

The flow field in a compressor cascade is very complex owing to the highly 3D, turbulent, and viscous properties. However, in the through-flow analysis method, the viscosity effects are taken into account using empirical models. These models were based on experimental results for early blades. However, the blade types in modern compressors are quite different from those in older compressors. Therefore, it is not possible to predict the performance of modern compressors using the old empirical models. In this study, several multiple circular-arc (MCA) blades commonly used in modern compressors were simulated. After the simulations, a database of the cascade performance was built. Based on this database, some new models were established to predict the performance of modern cascades using regression analysis methods and an artificial neural network (ANN) method. The accuracy of all these new models is high enough for use in engineering applications.

Corner separation limits the increase of the aerodynamic loading in the compressor. Previous numerical studies indicate that the Blended Blade and End Wall (BBEW) technology is useful in delaying, or reducing, or even eliminating the corner separation. This paper presents combined experimental and numerical investigations on a BBEW cascade and its prototype. The experimental results show that the design of Blended Blade and End Wall (BBEW) can improve the performance of the cascade when the incidence angle was positive or at the design point, and the total pressure loss coefficient was reduced by 7 %-8 %. The performance improvement mainly located from 10 %-25 % span heights. Compared with the experiment data, the SST turbulence model shows the best results of the flow field. Based on the numerical results, the details of the flow field and the effect of the Blended Blade and End Wall (BBEW) design on the corner separation are discussed and analyzed.

Monitoring of aerodynamic parameters of the blade helps to enhance the operating capabilities of the Wells turbine. In this study, a few discrete pressure points were used to estimate the pressure patterns by fitting the exact potential-flow solution for flow over a parabola. The sectional aerodynamics was assessed by the leading-edge flow sensing (LEFS) algorithm. A characteristic parameter was employed to deduce leading-edge flow status. Moreover, the influence of rotor speeds and tip gaps on the vortex boundary was discussed in terms of the Lagrangian frame. For the rotor speed larger than 1000 rpm at the incipient stall point, there is no boundary layer separation at the suction side of the blade tip leading edge. At the same rotor speed, a large tip gap reduces the axial shear of the suction flows and the axial stretching of the tip leakage vortex, which helps to enhance the interaction time and strength of the leakage vortex and the suction flows. For the Wells turbine with attached flows, the LEFS algorithm can accurately evaluate the pressure distribution and suction parameters near the leading edge. The LEFS-derived dimensionless parameter can act as an equivalent angle of attack under different tip gaps, providing the possibility for stall warning of Wells turbines.