A Novel Deep Learning Model for the Flow Field Reconstruction of An Oscillating Airfoil

In this paper, a novel model is presented for reconstructing unsteady periodic fields of velocity vector and pressure scalar over an oscillating foil. This data-driven method based on convolutional neural network can be utilized to accomplish two objections: fields reconstruction from limited measurements and transient aerodynamic characteristics prediction. The verification results of an oscillating foil under low Reynolds number show that this method can accurately reconstruct all the fields only by limited pressure information at probes on the foil surface. The evaluation on aerodynamic characteristics prediction illustrates that our model outperforms four classical machine learning methods. Meanwhile, a well-trained CNN model can almost achieve real-time flow field prediction by leveraging the GPU acceleration. Finally, the exploration of the robustness for the CNN model is conducted on several aspects, including training size, probe layouts, probe numbers and measurement noises.

Исследование радиационной эрозии в газоразрядном детекторе с помощью атомно-силовой микроскопии

Using Atomic Force Microscopy Methods, we studied the samples of the cathodes of multiwire proportional chambers after long-term irradiation with a beta-source 90Sr at the longevity test. The changes in the morphology of the copper foil surface at the cathode of the detector as a result of the influence of the electron flow are described. It is presented a quantitative assessment and analysis of the evolution of the resulting radiation defects depending on the irradiation conditions. It is shown the similarity of the radiation defects in the laboratory prototypes and in full scale proportional chambers that have been operated at the LHC for almost 10 years.

Use of synthetic jet to a fully-active flapping foil for power extraction enhancement

The power extraction performance of a fully-active flapping foil with synthetic jet is numerically investigated in this work. An elliptic airfoil with ratio of 8, which is placed in a two-dimensional laminar flow, is adopted to extract power from the flow. The foil implements the imposed translational and rotational motions synchronously. A pair of synthetic jets with the same frequency and strength is integrated into the upper and lower surfaces of flapping foil. As a result, the flow field around the foil could be affected by the synthetic jets greatly. At the Reynolds number of 1000 and the pitching axis location of half chord, the effects of the jet strength, the inclined angle between the jet direction and the chord line, as well as the phase angle between the synthetic jets and the flapping motion on the power extraction performance are systematically investigated. Compared with the traditional flapping foil, it is demonstrated that the enhancement of power extraction efficiency can be achieved with the help of synthetic jets. Based on the numerical analysis, it is indicated that the jet flow on the foil surfaces alters the vortex-shedding process and modifies the pressure distribution on the foil surface. As a result, the overall power extraction of the flapping foil can be benefitted.