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We propose the asynchronous control of anisotropic diffusion (AD) algorithm, and such asynchronous anisotropic diffusion (AAD) algorithm is demonstrated experimentally to reduce noise from the sensing signals obtained from Brillouin distributed optical fiber sensors. The performance of the proposed AAD algorithm is analyzed in detail for different experimental conditions and compared with that of block-matching and 3D filtering, two-dimensional wavelet denoising, AD, and non-local means algorithms. Some key factors of the proposed algorithm, such as the impact of convolution kernel size on the performance of AD algorithms, the influence of low sampling point number (SPN) on the quality of Brillouin frequency shift and the selection of diffusion thresholds are analyzed and discussed with experimental results. The experimental results validate that the AAD algorithm can provide better root-mean-square error (RMSE) and spatial resolution (SR) than the other four algorithms, especially for higher signal-to-noise ratio (SNR) improvement and higher SPNs. For lower SPNs, the performance of AAD is also not inferior to the RMSE performance of NLM and AD. The runtime of the AAD algorithm is also quite low. Moreover, the proposed algorithm offers the best SR performance as compared to other noise reduction algorithms investigated in this study. Thus, the proposed AAD algorithm can be an effective candidate to improve the measurement accuracy of Brillouin distributed optical fiber sensors.

The dynamic stall process in three-dimensional (3D) cases on a rectangular wing undergoing a constant rate ramp-up motion is introduced to provide a qualitative analysis about the onset and development of the stall phenomenon. Based on the enhanced understanding of the mechanism of dynamic stalls, a 3D dynamic stall model is constructed with the emphasis of the onset, the growth, and the convection of the dynamic stall vortex on the 3D wing surface. The results show that this engineering dynamic stall model can simulate the 3D unsteady aerodynamic performance appropriately.