The micro-riblet structures have been demonstrated effective in controlling the Total Pressure Loss (TPL) of aero-engine blades. However, due to the considerable scale gap between micro-texture and an actual aero-engine blade, wind tunnel tests and numerical simulations with massive grids directly describing the global flow field are costly for aerodynamic evaluation. Furthermore, the fine micro surface structure brings unavoidable manufacturing errors, and the probability prediction contributes to gaining the confidence interval of the results. Therefore, a novel relay-based probabilistic model for multi-fidelity scenarios in the TPL prediction of a compressor cascade with micro-riblet surfaces is proposed to trade off accuracy and efficiency. Combined with the low-fidelity flow data generated by an aerodynamic solution strategy using the boundary surrogate model and the high-fidelity flow data from the experiment, the relay-based modeling has been achieved through knowledge transferring, and the confidence interval can be provided by the Gaussian Process Regression (GPR) model. The TPL of compressor cascades with micro-riblet surfaces under different surface structures at March number Ma = 0.64, 0.74, 0.84 have been evaluated using the Relay-Based Probabilistic (RBP) model. The results illustrate that the RBP model could provide higher accuracy than the Single-Fidelity-Data-Driven (SFDD) prediction model, which show the promising potential of multi-fidelity scenarios data fusion in the aerodynamic evaluation of multi-scale configurations.

To alleviate the curse of dimensionality problem in aerodynamic shape optimization and improve the representation capability as well as optimization efficiency of parameterization method, this paper proposes a new airfoil parameterization method named Latent Diffusion Model (LDM), which combines Class-Shape Transformation (CST), Autoencoder (AE), and Denoising Diffusion Implicit Model (DDIM). The geometric quality of the airfoils generated by the proposed method is analyzed. Then, the effect of different latent dimensions on the distribution of the samples is examined. Next, the fitting accuracy and the representational capability of LDM is compared with those of four different parameterization methods: CST-AE, Principal Component Analysis (PCA), Free Form Deformation (FFD), and CST. Finally, airfoil aerodynamic optimization is conducted to verify the performance of the LDM method. The results show that the LDM can generate smooth and acceptable airfoil samples. Compared with other parameterization methods, this method offers a more accurate description and stronger representation capability for airfoils. Additionally, the LDM demonstrates faster convergence and shorter optimization time. The optimized airfoil exhibits better aerodynamic performance and a more stable optimization process. In the future, this method has the potential to be extended to aerodynamic optimization for more complex shapes, such as wing segments, nacelles and fans.

Aerodynamic noise of High-Lift Devices (HLDs) is one of the main sources of airframe noise, and has immediate impacts on the airworthiness certification, environmental protection and security of commercial aircraft. In this study, a novel hybrid method is proposed for the aerodynamic noise prediction of HLD. A negative Spalart-Allmaras (S-A) turbulence model based Improved Delayed Detached Eddy Simulation (IDDES) method coupling with AFT-2017b transition model is developed, in order to elaborately simulate the complex flow field around the HLD and thus obtain the information of acoustic sources. A Farassat-Kirchhoff hybrid method is developed to filter the spurious noise sources caused by the vortex motions in solving the Ffowcs Williams-Hawkings (FW-H) equation with permeable integral surfaces, and accurately predict the far-field noise radiation of the HLD. The results of the 30P30N HLD indicate that, the computational Sound Pressure Levels (SPLs) obtained by the Farassat-Kirchhoff hybrid method conform well with the experimental ones in the spectrum for the given observation point, and are more accurate than those obtained by the Farassat 1A method. Based on the hybrid method, the acoustic directivity of the HLD of a commercial aircraft is obtained, and the variation of the SPLs in the spectrum with the deflection angle of the slat is analyzed.

The application of grooved surface structure is an emerging and effective means in turbulence flow control. However, for a realistic configuration, the global flow field described directly by simple application of massive grids makes it unfeasible to simulate. In this paper, a boundary surrogate model reproducing the effect of microscopic near-wall region is proposed to improve computational efficiency. The surrogate model trained with Lattice Boltzmann Method (LBM) considering the rarefied effect based on real micro/nanoflow field is new among literature, which accurately shows flow characteristics of the micro/nano structure. With this approach, numerical simulations via Reynolds-averaged Navier Stokes equations with modified wall boundary condition are performed in subsonic and transonic flow. The results show that micro/nano grooved surface structure has the effect of delaying transition from laminar to turbulence, thus reducing the skin friction significantly. Analysis of turbulence intensity and turbulence kinetic energy shows that the near-wall flow field of grooved airfoil is more stable compared with that of the smooth airfoil. The reducing rate of maximum turbulent intensity reaches 13.39%. The paper shows a perspective for further application of micro/nano groove structure to turbulence flow control in aircraft design by providing an accurate and efficient simulation method.