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.
Welcome to the Recover newsletter Issue 4 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 4th instalment covers recent work on seaweed recovery in the subtidal zone, ecological engineering in Waikoau / Lyell Creek, and a sneak preview of drone survey results!
Welcome to the Recover newsletter Issue 5 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 5th instalment covers the question of how much of the coast uplifted how much, recent lab work on seaweed responses to stressors, and more on our drone survey work to quantify earthquake impacts and recovery along 130 km of coastline in the intertidal zone!
A number of reverse and strike-slip faults are distributed throughout mid-Canterbury, South Island, New Zealand, due to oblique continental collision. There is limited knowledge on fault interaction in the region, despite historical multi-fault earthquakes involving both reverse and strike-slip faults. The surface expression and paleoseismicity of these faults can provide insights into fault interaction and seismic hazards in the region. In this thesis, I studied the Lake Heron and Torlesse faults to better understand the key differences between these two adjacent faults located within different ‘tectonic domains’. Recent activity and surface expression of the Lake Heron fault was mapped and analysed using drone survey, Structure-from-Motion (SfM) derived Digital Surface Model (DSM), aerial image, 5 m-Digital Elevation Model (DEM), luminescence dating technique, and fold modelling. The results show a direct relationship between deformation zone width and the thickness of the gravel deposits in the area. Fold modelling using fault dip, net slip and gravel thickness produces a deformation zone comparable to the field, indicating that the fault geometry is sound and corroborating the results. This result Is consistent with global studies that demonstrate deposit (or soil thickness) correlates to fault deformation zone width, and therefore is important to consider for fault displacement hazard. A geomorphological study on the Torlesse fault was conducted using SfM-DSM, DEM and aerial images Ground Penetrating Radar (GPR) survey, trenching, and radiocarbon and luminescence dating. The results indicate that the Torlesse fault is primarily strike-slip with some dip slip component. In many places, the bedding-parallel Torlesse fault offsets post-glacial deposits, with some evidence of flexural slip faulting due to folding. Absolute dating of offset terraces using radiocarbon dating and slip on fault determined from lateral displacement calculating tool demonstrates the fault has a slip rate of around 0.5 mm/year to 1.0 mm/year. The likelihood of multi-fault rupture in the Torlesse Range has been characterised using paleoseismic trenching, a new structural model, and evaluation of existing paleoseismic data on the Porters Pass fault. Identification of overlapping of paleoseismic events in main Torlesse fault, flexural-slip faults and the Porters Pass fault in the Torlesse Range shows the possibility of distinct or multi-fault rupture on the Torlesse fault. The structural connectivity of the faults in the Torlesse zone forming a ‘flower structure’ supports the potential of multi-fault rupture. Multi-fault rupture modelling carried out in the area shows a high probability of rupture in the Porters Pass fault and Esk fault which also supports the co-rupture probability of faults in the region. This study offers a new understanding of the chronology, slip distribution, rupture characteristics and possible structural and kinematic relationship of Lake Heron fault and Torlesse fault in the South Island, New Zealand.
