The internal flow dynamics within transonic compressors are characterized by a complex interplay of phenomena including shock waves, turbulent boundary layers, and vortices. Among these, the interaction be-tween shock waves and turbulent boundary layers (SWTBLI) stands out as a significant challenge in transonic compressor flow fields. This paper employs a high-precision Computational Fluid Dynamics (CFD) approach, utilizing the k-ω turbulence model, to analyze the flow behavior of Rotor37 within the transonic com-pressor. Specifically, we focus on studying the SWTBLI phenomenon within the rotor channels. The obtained results agree with the experimental values, and the total pressure ratio calculation error is less than 4%. Notably, due to the significant losses caused by shock waves, the adiabatic efficiency of Rotor 37 calculated is slightly lower than the experimental values. The calculation procedure developed in this paper can accurately predict the details of the shock wave/turbulent boundary layer interference in the rotor blade passages, which indicates that the CFD calculation procedure is suitable for flow calculation of transonic compressors.
This establishes a mathematical model rooted in blade element-momentum theory, to accurately predict propeller aerodynamic loads under oblique inflow conditions. Leveraging this model, we achieve rapid computa-tion of propeller aerodynamic loads. High-precision CFD methods verified the aerodynamic load calculation procedures of the propeller under different inflow angles, and the calculation errors of procedures were all within 10%. Under the same oblique flow angle condition, the aerodynamic load change rules on propellers with different blade numbers were analyzed. The calculation results show that the pulsation amplitude of the bending moment and tangential force of the single propeller blade increases with the number of blades. In addition, the max value of the bending moment and tangential force of the propeller increase with the number of blades within a small fluctuation range. The number of fluctuations in a rotational cycle is the same as the number of blades.
The study of the characteristics of the pulsating velocity distribution in a flat plate turbulent boundary layer is important for the development of pulsating velocity turbulence models. In this paper, high temporal and spatial resolution measurements of velocity pulsations within the boundary layer of a flat plate turbulence are carried out in a wind tunnel using a laser Doppler velocimeter (LDV). By analyzing the measurement results, a mean velocity distribution curve is obtained, which is consistent with the turbulent velocity distribution curve given by other studies, confirming that the experimental setup of measuring the velocity in the flat plate boundary layer using LDV is reliable in this experiment. The analysis of the statistical results of the pulsation velocity reveals that the root mean square distribution of the pulsation velocity has a distinct inner peak and a small outer peak within the boundary layer, which is consistent with the results of recent studies and further characterizes the distribution of the pulsation velocity within the boundary layer. At the same time, the spectral analysis of the pulsation velocity reveals that the pulsation characteristics in different regions of the boundary layer are different, the pulsation amplitude in the logarithmic law region fluctuates from high to low, and the pulsation in the outer layer of the boundary layer appears to be intermittent.
Based on the fluid momentum equation and its Reynolds-averaged form, the fluctuation velocity equation is derived. By assuming the incompressibility of fluctuation velocity and applying the Bernoulli equation to handle the viscosity term and pressure fluctuation term in the fluctuation velocity equation. Then drawing on the partial averaging approach of the GAO-YONG turbulence model for fluctuation velocity, the relationship between the derivative of fluctuation velocity and the derivative of partial average fluctuation velocity is established through the introduction of turbulence kinetic energy spectrum theory, thus obtaining a new partial average fluctuation velocity model equation. Finally, this equation is integrated into a CFD program to simulate turbulent boundary layer flow over a flat plate. After adjustment and optimization, the simulated boundary layer velocity distribution agrees well with experimental data, although differences exist in the distribution of fluctuation velocity compared to experimental data, especially in the log-law region, indicating that the model equation needs further study and improvement.
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