Finite element study on bearing capacities of hook-bolt joint of assembled GRC wall with light steel skeleton frame

A new assembled external wall is composed of two glass fiber reinforced concrete (GRC) panels and built-in light steel skeleton frames and a layer of filled insulated core materials. To connect this new wall to the main steel structure, the new hook-bolt joint is used. The finite element (FE) software ABAQUS was used to study the bearing capacities of hook-bolt joint under horizontal force and vertical force. The FE results show that under horizontal and vertical force, the hook-bolt joint shows good elastic-plastic behaviour. In the initial stage of displacement loading, there is slip displacement stage and the load is very small. After this initial stage, with the gradual increase of displacement, the load increases gradually. Larger stresses are mainly distributed at the intersection of the hook-shaped connector and the U-shaped connector. The vertical bearing capacity of the hook-bolt joint is about two times larger than that of horizontal one. These studies can provide referential basis for the design and application of the hook-bolt joint of the assembled wall with light steel skeleton frame

Finite element study on mechanical performances of multi-span metal faced sandwich panels under temperature actions

Metal faced sandwich panel is composed of two relatively high strength metal faces and a relatively thick and lightweight insulated core. Under the continuous action of temperature such as strong sunlight, the multi-span metal faced sandwich panels can be destroyed. In this paper, the finite element (FE) software ABAQUS was used to study the stress and deformation of these sandwich panels under temperature action. The FE results show that the compressive stress in the mid-span region of the metal panel is larger and it gradually decreased from the middle to the two sides. The deformation at the centre of side span of sandwich panels is larger. The support constraints at the bottom of the sandwich panel have a great influence on the temperature stress. The fixed sandwich panel is more likely to occur wrinkle failure than the hinged one. To reduce the effects of temperature, two effective methods are proposed. The method increasing the density of the core material can increase the buckling stress and improve the bearing capacity against temperature action. The other method reducing the length of each segment of the sandwich panel can effectively release the temperature stress and reduce the negative effects of temperature

Finite element study on shear performances of in-filled bolt joint of assembled grc wall with light steel skeleton frame

A new in-filled wall is used in assembled steel structure buildings, which consists of two layers of glass fiber reinforced concrete (GRC) panels and a built-in light steel skeleton frame. To make this new wall fill in the main steel structure, a new in-filled bolt joint is used. In order to obtain the mechanical properties and failure modes under shear load, the shear performances of this joint were studied with the finite element (FE) software ABAQUS. The results show that before reaching the fracture failure strain, the in-filled bolt joint shows good elastic-plastic behaviour. When the strain of the in-filled bolt joint reaches the failure strain, the shear load reaches the peak value. Subsequently, due to the shear fracture of the bolt, the shear load drops rapidly. Throughout the loading process, the stress of steel beam and rectangular steel tube is always very small and the stress of the joint yields in a large area in the later stage

3D ShapeNets: A Deep Representation for Volumetric Shapes

3D shape is a crucial but heavily underutilized cue in today's computer vision systems, mostly due to the lack of a good generic shape representation. With the recent availability of inexpensive 2.5D depth sensors (e.g. Microsoft Kinect), it is becoming increasingly important to have a powerful 3D shape representation in the loop. Apart from category recognition, recovering full 3D shapes from view-based 2.5D depth maps is also a critical part of visual understanding. To this end, we propose to represent a geometric 3D shape as a probability distribution of binary variables on a 3D voxel grid, using a Convolutional Deep Belief Network. Our model, 3D ShapeNets, learns the distribution of complex 3D shapes across different object categories and arbitrary poses from raw CAD data, and discovers hierarchical compositional part representations automatically. It naturally supports joint object recognition and shape completion from 2.5D depth maps, and it enables active object recognition through view planning. To train our 3D deep learning model, we construct ModelNet -- a large-scale 3D CAD model dataset. Extensive experiments show that our 3D deep representation enables significant performance improvement over the-state-of-the-arts in a variety of tasks.Comment: to be appeared in CVPR 201

Active Q-switched X-Ray Regenerative Amplifier Free-Electron Laser

Despite tremendous progress in x-ray free-electron laser (FEL) science over the last decade, future applications still demand fully coherent, stable x-rays that have not been demonstrated in existing X-ray FEL facilities. In this Letter, we describe an active Q-switched x-ray regenerative amplifier FEL scheme to produce fully coherent, high-brightness, hard x rays at a high-repetition rate. By using simple electron-beam phase space manipulation, we show this scheme is flexible in controlling the x-ray cavity quality factor Q and hence the output radiation. We report both theoretical and numerical studies on this scheme with a wide range of accelerator, x-ray cavity, and undulator parameters