Buckling Behavior of Steel Plates and Concrete Filled Composite Shear Walls Related Nuclear Power Engineering

Based on the program of nuclear power engineering, the in-plane buckling behavior of Steel plates and concrete filled composite shear wall (SCSW) was investigated. 9 1/5 scaled specimens were conducted under horizontal cyclic load and constant vertical load. The parameters such as the space of studs, the vertical load, the form of connectors, and the thickness of the steel plate were designed to research the affection on the buckling of the steel plate. According to the results of tests, it can be seen that the bulge of the steel plate occurred at about 50mm above the top of the foundation beam. The bulge can be connected as a whole in the specimens with studs only, but not in the specimens with stiffeners. Finite element models were performed to simulate the buckling behavior of the steel plate, and the results were found to be in good agreement with the test results. The buckling stress of the steel plate was calculated by equations based on the measuring data. It was found that they were smaller than that of finite element analysis. The more accurate simulation was needed

OmniZoomer: Learning to Move and Zoom in on Sphere at High-Resolution

Omnidirectional images (ODIs) have become increasingly popular, as their large field-of-view (FoV) can offer viewers the chance to freely choose the view directions in immersive environments such as virtual reality. The M\"obius transformation is typically employed to further provide the opportunity for movement and zoom on ODIs, but applying it to the image level often results in blurry effect and aliasing problem. In this paper, we propose a novel deep learning-based approach, called \textbf{OmniZoomer}, to incorporate the M\"obius transformation into the network for movement and zoom on ODIs. By learning various transformed feature maps under different conditions, the network is enhanced to handle the increasing edge curvatures, which alleviates the blurry effect. Moreover, to address the aliasing problem, we propose two key components. Firstly, to compensate for the lack of pixels for describing curves, we enhance the feature maps in the high-resolution (HR) space and calculate the transformed index map with a spatial index generation module. Secondly, considering that ODIs are inherently represented in the spherical space, we propose a spherical resampling module that combines the index map and HR feature maps to transform the feature maps for better spherical correlation. The transformed feature maps are decoded to output a zoomed ODI. Experiments show that our method can produce HR and high-quality ODIs with the flexibility to move and zoom in to the object of interest. Project page is available at http://vlislab22.github.io/OmniZoomer/.Comment: Accepted by ICCV 202