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An efficient data-driven approach for predicting steady airfoil flows is proposed based on the Fourier neural operator (FNO), which is a new framework of neural networks. Theoretical reasons and experimental results are provided to support the necessity and effectiveness of the improvements made to the FNO, which involve using an additional branch neural operator to approximate the contribution of boundary conditions to steady solutions. The proposed approach runs several orders of magnitude faster than the traditional numerical methods. The predictions for flows around airfoils and ellipses demonstrate the superior accuracy and impressive speed of this novel approach. Furthermore, the property of zero-shot super-resolution enables the proposed approach to overcome the limitations of predicting airfoil flows with Cartesian grids, thereby improving the accuracy in the near-wall region. There is no doubt that the unprecedented speed and accuracy in forecasting steady airfoil flows have massive benefits for airfoil design and optimization. [ABSTRACT FROM AUTHOR]

We utilize the nonlinear acoustic solver (NLAS) and Ffowcs-Williams/Hawkings (FW-H) equation to investigate the noise generation and radiation due to shock (wave) and boundary layer interaction (SBLI) in the inlet duct. A classical benchmark for SBLI is chosen to validate the flow features and numerical results show good agreement with experimental results. In the simulation of the noise generated by SBLI, the inlet buzz phenomenon is successfully observed. The oscillation of the normal shock is a kind of little buzz and the oscillation of inner shocks is a kind of big buzz with a frequency around 100 Hz. In the far-field, frequency spectrums show a dominant frequency close to the frequency of inner shocks oscillation. This indicates that the oscillation of inner shocks determines the magnitude of the overall sound pressure level (OASPL) of the far-field noise. [ABSTRACT FROM AUTHOR]

With the continuous increase in the total quantity and quality of wind energy used by society, the aerodynamic complexity of wind turbine impellers has also gradually increased. This requires a more accurate analysis and understanding of the aerodynamic performance of important parts of the wind turbine impeller. The blade tip vortex is undoubtedly one of the most important issues. This article used the state-of-the-art lattice Boltzmann method (LBM), combining large eddy simulation (LES) and wall-adapting local-eddy (WALE) model, to investigate the unsteady flow characteristics of the blade tip region due to impeller wake for a wind turbine. The trend of this calculation result is consistent with the experimental data, both for the axial force and the torque on the impeller. Therefore, it indicates the calculation model of LBM is reasonable and effective. The relevant in-depth results clearly showed the dynamic stability of a spiral structure will increase as operating conditions continue to advance and it is also synchronously affected by the tower wake flow structures. The fluctuation amplitude of the static pressure value on both sides of the impeller gradually decreases with time. The distribution of static pressure near the leading edge of the tip is very different for each blade due to the influences of turbulence intensity and the tower shadow effect. The random minor fluctuations of the axial force and torque both exhibit similar characteristics, and the overall torque is more sensitive to random changes in the tip vortex on the impeller surface. [ABSTRACT FROM AUTHOR]