Experimental investigation of water, snow and granular ice effects on ice failure processes and impact loads

A large series of laboratory ice crushing experiments was performed to investigate the effects of external boundary condition and indenter contact geometry on ice load magnitude under crushing conditions. Four boundary conditions were considered: dry cases, submerged cases, and cases with the presence of snow and granular ice material on the indenter surface. Indenter geometries were a flat plate, wedge shaped indenter, (reverse) conical indenter, and spherical indenter. These were impacted with artificially produced ice specimens of conical shape with 20° and 30° cone angles. All indenter – ice combinations were tested in dry and submerged environments at 1 mm/s and 100 mm/s indentation rates. Additional tests with the flat indentation plate were conducted at 10 mm/s impact velocity and a subset of scenarios with snow and granular ice material was evaluated. The tests were performed using a material testing system (MTS) machine located inside a cold room at an ambient temperature of - 7°C. Data acquisition comprised time, vertical force, and displacement. In several tests with the flat plate and wedge shaped indenter, supplementary information on local pressure patterns and contact area were obtained using tactile pressure sensors. All tests were recorded with a high speed video camera and still photos were taken before and after each test. Thin sections were taken of some specimens as well. Ice loads were found to strongly depend on contact condition, interrelated with pre-existing confinement and indentation rate. Submergence yielded higher forces, especially at the high indentation rate. This was very evident for the flat indentation plate and spherical indenter, and with restrictions for the wedge shaped indenter. No indication was found for the conical indenter. For the conical indenter it was concluded that the structural restriction due to the indenter geometry was dominating. The working surface for the water to act was not sufficient to influence the failure processes and associated ice loads. The presence of snow and granular ice significantly increased the forces at the low indentation rate (with the flat indentation plate) that were higher compared to submerged cases and far above the dry contact condition. Contact area measurements revealed a correlation of higher forces with a concurrent increase in actual contact area that depended on the respective boundary condition. In submergence, ice debris constitution was changed; ice extrusion, as well as crack development and propagation were impeded. Snow and granular ice seemed to provide additional material sources for establishing larger contact areas. The dry contact condition generally had the smallest real contact area, as well as the lowest forces. The comparison of nominal and measured contact areas revealed distinct deviations. The incorporation of those differences in contact process pressures-area relationships indicated that the overall process pressure was not substantially affected by the increased loads.

Automatic and adaptable registration of live RGBD video streams sharing partially overlapping views

In this thesis, we introduce DeReEs-4v, an algorithm for unsupervised and automatic registration of two video frames captured depth-sensing cameras. DeReEs-4V receives two RGBD video streams from two depth-sensing cameras arbitrary located in an indoor space that share a minimum amount of 25% overlap between their captured scenes. The motivation of this research is to employ multiple depth-sensing cameras to enlarge the field of view and acquire a more complete and accurate 3D information of the environment. A typical way to combine multiple views from different cameras is through manual calibration. However, this process is time-consuming and may require some technical knowledge. Moreover, calibration has to be repeated when the location or position of the cameras change. In this research, we demonstrate how DeReEs-4V registration can be used to find the transformation of the view of one camera with respect to the other at interactive rates. Our algorithm automatically finds the 3D transformation to match the views from two cameras, requires no human interference, and is robust to camera movements while capturing. To validate this approach, a thorough examination of the system performance under different scenarios is presented. The system presented here supports any application that might benefit from the wider field-of-view provided by the combined scene from both cameras, including applications in 3D telepresence, gaming, people tracking, videoconferencing and computer vision.