During the last 10 years, the various type of high speed craft have been greatly developed, and since around of 1990 the large size of high speed passenger and/or cargo vessels are also introduced and took into the service in the various routes over the world. In a marine traffic way some bridge need to build across a rivers, cannals or a waterways. This one will be an obstruction and potential risk of collision in the way of high speed craft. Accordingly some of collision accident have been reported, which were caused by a lost control, wind and hydrodynamic forces, fog or human errors. In this paper a high speed craft having 40 m length is assumed to be collided with a circular type of bridge piers at right angle. The mode of deformation, penetration depth of collapse, impact forces, reduction of speed, loss of kinetic energy, and influence of scantlings, etc. have been calculated in each speed with a time variation to find a maximum values within a limit, and are graphically presented.

This paper proposes an automated crack evaluation technique for a high-rise bridge pier using a climbing robot. The proposed technique enables to automatically detect and quantify the bridge pier cracks even where cannot easily access by human for visual inspection. To achieve it, high quality images are obtained by scanning the vision cameras embedded on the climbing robot along the bridge pier surface. Then, a feature extraction-based image stitching algorithm is newly developed and applied for establishing the entire region of interest (ROI) images. The ROI images are then processed with a semantic segmentation algorithm for automated crack detection. Finally, the detected cracks are precisely quantified by a crack quantification algorithm. The proposed technique is validated using in-situ test data obtained from Jang-Duck bridge located at Gangneung city, South Korea. The test results reveal that the proposed technique successfully evaluate the bridge pier cracks with precision of 90.92 % and recall of 97.47 %.