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Other, UC QuakeStudies

A zip file containing the suite of SCIRT CAD customisation tools. This file contains:SCIRT CAD LISP routines (198 files)SCIRT CAD dialogue box filesa complete set of layer listsa full set of text files containing the complete list of street names in Christchurchtemplates and lists used for translating 12d outputs to useable dwg reference filesa full set of SCIRT CAD manualsThis file is not sufficient for someone to set up a full SCIRT CAD System, but it will allow a developer to select tools to incorporate with an existing system.

Images, UC QuakeStudies

A photograph of a kitchen in the Diabetes Centre. Several power tools have been left on the bench and a roll of plastic sheeting has been propped up against it. A hole has been cut in the wall behind to expose several pipes and wires.

Research papers, The University of Auckland Library

Following a damaging earthquake, the immediate emergency response is focused on individual collapsed buildings or other "hotspots" rather than the overall state of damage. This lack of attention to the global damage condition of the affected region can lead to the reporting of misinformation and generate confusion, causing difficulties when attempting to determine the level of postdisaster resources required. A pre-planned building damage survey based on the transect method is recommended as a simple tool to generate an estimate of the overall level of building damage in a city or region. A methodology for such a transect survey is suggested, and an example of a similar survey conducted in Christchurch, New Zealand, following the 22 February 2011 earthquake is presented. The transect was found to give suitably accurate estimates of building damage at a time when information was keenly sought by government authorities and the general public. VoR - Version of Record

Research papers, University of Canterbury Library

After a high-intensity seismic event, inspections of structural damages need to be carried out as soon as possible in order to optimize the emergency management, as well as improving the recovery time. In the current practice, damage inspections are performed by an experienced engineer, who physically inspect the structures. This way of doing not only requires a significant amount of time and high skilled human resources, but also raises the concern about the inspector’s safety. A promising alternative is represented using new technologies, such as drones and artificial intelligence, which can perform part of the damage classification task. In fact, drones can safely access high hazard components of the structures: for instance, bridge piers or abutments, and perform the reconnaissance by using highresolution cameras. Furthermore, images can be automatically processed by machine learning algorithms, and damages detected. In this paper, the possibility of applying such technologies for inspecting New Zealand bridges is explored. Firstly, a machine-learning model for damage detection by performing image analysis is presented. Specifically, the algorithm was trained to recognize cracks in concrete members. A sensitivity analysis was carried out to evaluate the algorithm accuracy by using database images. Depending on the confidence level desired,i.e. by allowing a manual classification where the alghortim confidence is below a specific tolerance, the accuracy was found reaching up to 84.7%. In the second part, the model is applied to detect the damage observed on the Anzac Bridge (GPS coordinates -43.500865, 172.701138) in Christchurch by performing a drone reconnaissance. Reults show that the accuracy of the damage detection was equal to 88% and 63% for cracking and spalling, respectively.