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Images, eqnz.chch.2010

Photos taken in New Brighton on March 31 following the February 22 earthquake. File reference: CCL-2011-03-25-New Brighton-After-The-Earthquake-NB Parkland 007 From the collection of Christchurch City Libraries

Videos, UC QuakeStudies

A video of people participating in the 'Bare Your Bum for Brighton' protest in New Brighton. The protest was organised by Pier Side Café owner Tony Brooks, as a humorous way of getting Christchurch city leaders to take notice of New Brighton after the 22 February 2011 earthquake.

Research papers, University of Canterbury Library

This paper presents the probabilistic seismic performance and loss assessment of an actual bridge– foundation–soil system, the Fitzgerald Avenue twin bridges in Christchurch, New Zealand. A two-dimensional finite element model of the longitudinal direction of the system is modelled using advanced soil and structural constitutive models. Ground motions at multiple levels of intensity are selected based on the seismic hazard deaggregation at the site. Based on rigorous examination of several deterministic analyses, engineering demand parameters (EDP’s), which capture the global and local demand, and consequent damage to the bridge and foundation are determined. A probabilistic seismic loss assessment of the structure considering both direct repair and loss of functionality consequences was performed to holistically assess the seismi risk of the system. It was found that the non-horizontal stratification of the soils, liquefaction, and soil–structure interaction had pronounced effects on the seismic demand distribution of the bridge components, of which the north abutment piles and central pier were critical in the systems seismic performance. The consequences due to loss of functionality of the bridge during repair were significantly larger than the direct repair costs, with over a 2% in 50 year probability of the total loss exceeding twice the book-value of the structure.

Research papers, University of Canterbury Library

Seismic behaviour of typical unreinforced masonry (URM) brick houses, that were common in early last century in New Zealand and still common in many developing countries, is experimentally investigated at University of Canterbury, New Zealand in this research. A one halfscale model URM house is constructed and tested under earthquake ground motions on a shaking table. The model structure with aspect ratio of 1.5:1 in plan was initially tested in the longitudinal direction for several earthquakes with peak ground acceleration (PGA) up to 0.5g. Toppling of end gables (above the eaves line) and minor to moderate cracking around window and door piers was observed in this phase. The structure was then rotated 90º and tested in the transverse (short) direction for ground motions with PGA up to 0.8g. Partial out-of-plane failure of the face loaded walls in the second storey and global rocking of the model was observed in this phase. A finite element analysis and a mechanism analysis are conducted to assess the dynamic properties and lateral strength of the model house. Seismic fragility function of URM houses is developed based on the experimental results. Damping at different phases of the response is estimated using an amplitude dependent equivalent viscous damping model. Financial risk of similar URM houses is then estimated in term of expected annual loss (EAL) following a probabilistic financial risk assessment framework. Risks posed by different levels of damage and by earthquakes of different frequencies are then examined.

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.