It is still a big challenge to obtain excellent low-temperature toughness for bulk steel materials. Delamination is an effective method to improve low-temperature toughness. In the present study, delamination toughening in a low carbon microalloyed steel plate with elongated and ultrafine-grained microstructure rolled in the dual-phase region has been investigated in detail. When toughness was measured along normal direction, the steel plate had a high upper shelf energy and no delamination occurred in the upper shelf region. A large delaminated crack parallel to rolling plane started to appear and changed the propagation path of main crack when testing temperature was lower than −60 °C. We find this kind of delamination induces a second upper shelf in the Charpy transition–temperature curve. The second upper shelf, reaching up to 300 J in the temperature range of −60 °C to −140 °C, results in excellent low-temperature toughness for the steel plate, and the ductile-brittle transition temperature is lowered to −157 °C. The developed steel plate also has high low-temperature toughness measured along transverse direction due to delamination. The effect factors on upper shelf energy, delamination mechanism and delamination toughening are discussed.

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CycloMedia is a Dutch company specialized in the large-scale and systematic visualization of environments based on 360° panoramic photographs. The images are captured from public roads at street level, using a car to carry a panoramic camera system. High resolution spherical panoramas are geometrically correct and thus allow a user to perform photogrammetric 3D measurements and use imagery for 3D modelling and texture mapping. Drawing 3D point cloud (or rather pixel cloud) is a relatively new approach to use panoramic images. Currently there is no completely steady and consummate method to reconstruct digital building models from point clouds, thus this project aims to propose an innovative and practical framework of building reconstruction in particular. The developed method uses segmentation by region growing based on normals and curvature, constructing topology between segments by Voronoi partitioning, shape simplification by segmented least squares and principal component analysis methods. The method proves to have good results while tested on Lidar point clouds, however with some modifications is also applicable to pixel clouds obtained from panoramic imagery.@en