Rapid, reliable information on earthquake-affected structures' current damage/health conditions and predicting what would happen to these structures under future seismic events play a vital role in accelerating post-event evaluations, leading to optimized on-time decisions. Such rapid and informative post-event evaluations are crucial for earthquake-prone areas, where each earthquake can potentially trigger a series of significant aftershocks, endangering the community's health and wealth by further damaging the already-affected structures. Such reliable post-earthquake evaluations can provide information to decide whether an affected structure is safe to stay in operation, thus saving many lives. Furthermore, they can lead to more optimal recovery plans, thus saving costs and time. The inherent deficiency of visual-based post-earthquake evaluations and the importance of structural health monitoring (SHM) methods and SHM instrumentation have been highlighted within this thesis, using two earthquake-affected structures in New Zealand: 1) the Canterbury Television (CTV) building, Christchurch; 2) the Bank of New Zealand (BNZ) building, Wellington. For the first time, this thesis verifies the theoretically- and experimentally validated hysteresis loop analysis (HLA) SHM method for the real-world instrumented structure of the BNZ building, which was damaged severely due to three earthquakes. Results indicate the HLA-SHM method can accurately estimate elastic stiffness degradation for this reinforced concrete (RC) pinched structure across the three earthquakes, which remained unseen until after the third seismic event. Furthermore, the HLA results help investigate the pinching effects on the BNZ building's seismic response. This thesis introduces a novel digital clone modelling method based on the robust and accurate SHM results delivered by the HLA method for physical parameters of the monitored structure and basis functions predicting the changes of these physical parameters due to future earthquake excitations. Contrary to artificial intelligence (AI) based predictive methods with black-box designs, the proposed predictive method is entirely mechanics-based with an explicitly-understandable design, making them more trusted and explicable to stakeholders engaging in post-earthquake evaluations, such as building owners and insurance firms. The proposed digital clone modelling framework is validated using the BNZ building and an experimental RC test structure damaged severely due to three successive shake-table excitations. In both structures, structural damage intensifies the pinching effects in hysteresis responses. Results show the basis functions identified from the HLA-SHM results for both structures under Event 1 can online estimate structural damage due to subsequent Events 2-3 from the measured structural responses, making them valuable tool for rapid warning systems. Moreover, the digital twins derived for these two structures under Event 1 can successfully predict structural responses and damage under Events 2-3, which can be integrated with the incremental dynamic analysis (IDA) method to assess structural collapse and its financial risks. Furthermore, it enables multi-step IDA to evaluate earthquake series' impacts on structures. Overall, this thesis develops an efficient method for providing reliable information on earthquake-affected structures' current and future status during or immediately after an earthquake, considerably guaranteeing safety. Significant validation is implemented against both experimental and real data of RC structures, which thus clearly indicate the accurate predictive performance of this HLA-based method.
Light timber framed (LTF) structures provide a cost-effective and structurally efficient solution for low-rise residential buildings. This paper studies seismic performance of single-storey LTF buildings sheathed by gypsum-plasterboards (GPBs) that are a typical lining product in New Zealand houses. Compared with wood-based structural panels, GPBs tend to be more susceptible to damage when they are used in bracing walls to resist earthquake loads. This study aims to provide insights on how the bracing wall irregularity allowed by the current New Zealand standard NZS 3604 and the in-plane rigidity of ceiling diaphragms affect the overall seismic performance of these GPB-braced LTF buildings. Nonlinear time-history analyses were conducted on a series of single-storey baseline buildings with different levels of bracing wall irregularities and ceiling diaphragm rigidity. The results showed significant torsional effect caused by the eccentric bracing wall layout with semi-rigid/rigid ceiling diaphragms. On average, bracing wall drift demand caused by the extreme bracing wall irregularities was three times of that in the regular bracing wall layout under the rigid diaphragm assumption. This finding agreed well with the house survey after the 2011 Canterbury Earthquake in which significantly more damage was observed in the houses with irregular bracing wall layouts and relatively rigid diaphragms. Therefore, it is recommended to limit the level of bracing wall eccentricity and ensure the sufficiently rigid diaphragms to avoid excessive damage in these LTF buildings in future events.
INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
It is not a matter of if a major earthquake will happen in New Zealand, it is when. Earthquakes wreak havoc, cut off power and water supply, lines of communication, sewer, supply chains, and transport infrastructure. People get injured and whole communities can get cut off the rest of the country for extended periods of time. Countries taking measures to increase the population's preparedness tend to suffer less severe consequences than those that do not. Disaster management authorities deliver comprehensive instructions and preparation guidance, yet communities remain grossly underprepared. There are multiple factors that influence motivation for preparedness. Personal experience is one of the most significant factors that influence preparedness motivation. Not many people will experience a severe and damaging earthquake in their lifetime. A serious game (SG) that is a computer simulation of an earthquake is a tool that can let participants experience the earthquake and its aftermath from the safety of their computer. The main result of this research is a positive answer to the question: Can a serious game motivate people to prepare for earthquakes at least just as good as a personal experience of at least a moderate earthquake? There are different levels of immersion this serious game can be implemented at. In this thesis the same earthquake experience scenario – SG “ShakeUp” is implemented as a desktop application and a virtual reality (VR) application. A user study is conducted with the aim of comparing the motivation level achieved by the two versions of the SG “ShakeUp”. In this study no benefits of using VR over traditional desktop application were found: participants trying both versions of the SG “ShakeUp” reported similar levels of motivation to prepare for earthquakes immediately after the experiment. This means that both versions of the experience were equally effective in motivating participants to prepare for earthquakes. An additional benefit of this result is that the cheaper and easier to deliver desktop version can be widely used in various education campaigns. Participants reported being more motivated to prepare for earthquakes by either version of the SG “ShakeUp” than by any other contributing factor, including their previous earthquake experience or participation in a public education campaign. Both versions of the SG “ShakeUp” can successfully overcome personal bias, unrealistic optimism, pessimism, lack of perceived control over one’s earthquake preparation actions, fatalism, and sense of helplessness in the face of the earthquakes and motivate the individual to prepare for earthquakes. Participants without the prior earthquake experience benefit most from the SG “ShakeUp” regardless of the version tried, compared to the participants who had experienced an earthquake: significantly more of them will reconsider their current level of earthquake preparedness; about 24% more of them attribute their increased level of motivation to prepare for earthquakes to the SG “ShakeUp”. For every earthquake preparation action there is about 25% more people who felt motivated to do it after trying the SG “ShakeUp” than those who have done this preparation action before the experiment. After trying either version of the SG “ShakeUp”, people who live in a free standing house and those who live in a rental property reported highest levels of intent to carry on with the preparation actions. The proposed application prototype has been discussed with the University of Canterbury Earthquake Centre and received very positive feedback as having potential for practical use by various disaster management authorities and training institutions. The research shows that the SG “ShakeUp” motivates people to prepare for earthquakes as good as a personal earthquake experience and can be successfully used in various education campaigns.
