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Audio, Radio New Zealand

There are hopes an earthquake simulation in Porirua might result in homes being better prepared for a big shake. Houses on Christchurch's Port Hills suffered more damage than houses in other areas during the Canterbury Earthquakes - even though the ground shaking was roughly the same. Now the Earthquake Commission is on a mission to find out why that was - and prevent the same level of damage in a future quake. Checkpoint reporter Logan Church and video journalist Dom Thomas start their report up on a hilly farm above Wellington.

Research papers, University of Canterbury Library

Earthquakes cause significant damage to buildings due to strong vibration of the ground. Levitating houses using magnets and electromagnets would provide a complete isolation of ground motion for protecting buildings from seismic damage. Two types of initial configuration for the electromagnet system were proposed with the same air gap (10mm) between the electromagnet and reluctance plate. Both active and passive controller are modelled to investigate the feasibility of using a vibration control system for stabilizing the magnetic system within the designed air gap (10mm) in the vertical direction. A nonlinear model for the magnetic system is derived to implement numerical simulation of structural response under the earthquake record in Christchurch Botanic Gardens on 21 February 2011. The performance of the uncontrolled and the controlled systems are compared and the optimal combination of control gains are determined for the PID active controller. Simulation results show both active PID controller with constant and nonlinear attracting force are able to provide an effective displacement control within the required air gap (+/-5mm). The maximum control force demand for the PID controller in the presence of nonlinear attracting force is 4.1kN, while the attracting force in equilibrium position is 10kN provided by the electromagnet. These results show the feasibility of levitating a house using the current electromagnet and PID controller. Finally, initial results of passive control using two permanent magnets or dampers show the structural responses can be effectively reduced and centralized to +/-1mm using a nonlinear centring barrier function.

Research papers, University of Canterbury Library

High-quality ground motion records are required for engineering applications including response history analysis, seismic hazard development, and validation of physics-based ground motion simulations. However, the determination of whether a ground motion record is high-quality is poorly handled by automation with mathematical functions and can become prohibitive if done manually. Machine learning applications are well-suited to this problem, and a previous feed-forward neural network was developed (Bellagamba et al. 2019) to determine high-quality records from small crustal events in the Canterbury and Wellington regions for simulation validation. This prior work was however limited by the omission of moderate-to-large magnitude events and those from other tectonic environments, as well as a lack of explicit determination of the minimum usable frequency of the ground motion. To address these shortcomings, an updated neural network was developed to predict the quality of ground motion records for all magnitudes and all tectonic sources—active shallow crustal, subduction intraslab, and subduction interface—in New Zealand. The predictive performance of the previous feed-forward neural network was matched by the neural network in the domain of small crustal records, and this level of predictive performance is now extended to all source magnitudes and types in New Zealand making the neural network applicable to global ground motion databases. Furthermore, the neural network provides quality and minimum usable frequency predictions for each of the three orthogonal components of a record which may then be mapped into a binary quality decision or otherwise applied as desired. This framework provides flexibility for the end user to predict high-quality records with various acceptability thresholds allowing for this neural network to be used in a range of applications.

Research papers, University of Canterbury Library

Reconnaissance reports have highlighted the poor performance of non-ductile reinforced concrete buildings during the 2010-11 Canterbury earthquakes. These buildings are widely expected to result in significant losses under future earthquakes due to their seismic vulnerability and prevalence in densely populated urban areas. Wellington, for example, contains more than 70 pre-1970s multi-storey reinforced concrete buildings, ranging in height from 5 to 18 storeys. This study seeks to characterise the seismic performance and evaluate the likely failure modes of a typical pre-1970s reinforced concrete building in Wellington, by conducting advanced numerical simulations to evaluate its 3D nonlinear dynamic response. A representative 9-storey office building constructed in 1951 is chosen for this study and modelled in the finite element analysis programme DIANA, using a previously developed and validated approach to predict the failure modes of doubly reinforced walls with confined boundary regions. The structure consists of long walls and robust framing elements resulting in a stiff lateral load resisting system. Barbell-shaped walls are flanked by stiff columns with sufficient transverse reinforcement to serve as boundary regions. Curved shell elements are used to model the walls and their boundary columns, for which the steel reinforcement is explicitly modelled. Line elements are used to model the frame elements. The steel reinforcement in each member is explicitly modelled. The floor slabs are modelled using elastic shell elements. The model is analysed under short and long duration ground motions selected to match site specific targets in Wellington at the DBE and MCE intensity levels. The observed response of the building including drift profiles at each intesity level, strain localization effects around wall openings, and the influence of bidirectional loading are discussed.