Search

found 6 results

Research papers, University of Canterbury Library

Though rare and unpredictable, earthquakes can and do cause catastrophic destruction when they impact unprepared and vulnerable communities. Extensive damage and failure of vulnerable buildings is a key factor which contributes to seismic-related disasters, making the proactive management of these buildings a necessity to reduce the risk of future disasters arising. The devastating Canterbury earthquakes of 2010 and 2011 brought the urgency of this issue to national importance in New Zealand. The national earthquake-prone building framework came into effect in 2017, obligating authorities to identify existing buildings with the greatest risk of collapse in strong earthquakes and for building owners to strengthen or demolish these buildings within a designated period of time. Though this framework is unique to New Zealand, the challenge of managing the seismic risk of such buildings is common amongst all seismically-active countries. Therefore, looking outward to examine how other jurisdictions legally manage this challenge is useful for reflecting on the approaches taken in New Zealand and understand potential lessons which could be adopted. This research compares the legal framework used to reduce the seismic risk of existing buildings in New Zealand with that of the similarly earthquake-prone countries of Japan and Italy. These legal frameworks are examined with a particular focus on the proactive goal of reducing risk and improving resilience, as is the goal of the international Sendai Framework for Disaster Risk Reduction 2015-2030. The Sendai Framework, which each of the case study countries have committed to and thus have obligations under, forms the legal basis of the need for states to reduce disaster risk in their jurisdictions. In particular, the states’ legal frameworks for existing building risk reduction are examined in the context of the Sendai priorities of understanding disaster risk, strengthening disaster risk governance, and investing in resilience. While this research illustrates that the case study countries have each adopted more proactive risk reduction frameworks in recent years in anticipation of future earthquakes, the frameworks currently focus on a very narrow range of existing buildings and thus are not currently sufficient for promoting the long-term resilience of building stocks. In order to improve resilience, it is argued, legal frameworks need to include a broader range of buildings subject to seismic risk reduction obligations and also to broaden the focus on long-term monitoring of potential risk to buildings.

Research papers, The University of Auckland Library

As damage and loss caused by natural hazards have increased worldwide over the past several decades, it is important for governments and aid agencies to have tools that enable effective post-disaster livelihood recovery to create self-sufficiency for the affected population. This study introduces a framework of critical components that constitute livelihood recovery and the critical factors that lead to people’s livelihood recovery. A comparative case study is employed in this research, combined with questionnaire surveys and interviews with those communities affected by large earthquakes in Lushan, China and in Christchurch and Kaikōura, New Zealand. In Lushan, China, a framework with four livelihood components was established, namely, housing, employment, wellbeing and external assistance. Respondents considered recovery of their housing to be the most essential element for livelihood diversification. External assistance was also rated highly in assisting with their livelihood recovery. Family ties and social connections seemed to have played a larger role than that of government agencies and NGOs. However, the recovery of livelihood cannot be fully achieved without wellbeing aspects being taken into account, and people believed that quality of life and their physical and mental health were essential for livelihood restoration. In Christchurch, New Zealand, the identified livelihood components were validated through in-depth interviews. The results showed that the above framework presenting what constitutes successful livelihood recovery could also be applied in Christchurch. This study also identified the critical factors to affect livelihood recovery following the Lushan and Kaikōura earthquakes, and these include community safety, availability of family support, level of community cohesion, long-term livelihood support, external housing recovery support, level of housing recovery and availability of health and wellbeing support. The framework developed will provide guidance for policy makers and aid agencies to prioritise their strategies and initiatives in assisting people to reinstate their livelihood in a timely manner post-disaster. It will also assist the policy makers and practitioners in China and New Zealand by setting an agenda for preparing for livelihood recovery in non-urgent times so the economic impact and livelihood disruption of those affected can be effectively mitigated.

Research papers, Victoria University of Wellington

<b>Ōtautahi-Christchurch faces the future in an enviable position. Compared to other New Zealand cities Christchurch has lower housing costs, less congestion, and a brand-new central city emerging from the rubble of the 2011 earthquakes. ‘Room to Breathe: designing a framework for medium density housing (MDH) in Ōtautahi-Christchurch’ seeks to answer the timely question how can medium density housing assist Ōtautahi-Christchurch to respond to growth in a way that supports a well-functioning urban environment? Using research by design, the argument is made that MDH can be used to support a safe, accessible, and connected urban environment that fosters community, while retaining a level of privacy. This is achieved through designing a neighbourhood concept addressing 3 morphological scales- macro- the city; meso- the neighbourhood; and micro- the home and street. The scales are used to inform a design framework for MDH specific to Ōtautahi-Christchurch, presenting a typological concept that takes full advantage of the benefits higher density living has to offer.</b> Room to Breathe proposes repurposing underutilised areas surrounding existing mass transit infrastructure to provide a concentrated populous who do not solely rely on private vehicles for transport. By considering all morphological scales Room to Breathe provides one suggestion on how MDH could become accepted as part of a well-functioning urban environment.

Research papers, University of Canterbury Library

In response to the February 2011 earthquake, Parliament enacted the Canterbury Earthquake Recovery Act. This emergency legislation provided the executive with extreme powers that extended well beyond the initial emergency response and into the recovery phase. Although New Zealand has the Civil Defence Emergency Management Act 2002, it was unable to cope with the scale and intensity of the Canterbury earthquake sequence. Considering the well-known geological risk facing the Wellington region, this paper will consider whether a standalone “Disaster Recovery Act” should be established to separate an emergency and its response from the recovery phase. Currently, Government policy is to respond reactively to a disaster rather than proactively. In a major event, this typically involves the executive being given the ability to make rules, regulations and policy without the delay or oversight of normal legislative process. In the first part of this paper, I will canvas what a “Disaster Recovery Act” could prescribe and why there is a need to separate recovery from emergency. Secondly, I will consider the shortfalls in the current civil defence recovery framework which necessitates this kind of heavy governmental response after a disaster. In the final section, I will examine how

Research papers, The University of Auckland Library

This thesis presents the application of data science techniques, especially machine learning, for the development of seismic damage and loss prediction models for residential buildings. Current post-earthquake building damage evaluation forms are developed for a particular country in mind. The lack of consistency hinders the comparison of building damage between different regions. A new paper form has been developed to address the need for a global universal methodology for post-earthquake building damage assessment. The form was successfully trialled in the street ‘La Morena’ in Mexico City following the 2017 Puebla earthquake. Aside from developing a framework for better input data for performance based earthquake engineering, this project also extended current techniques to derive insights from post-earthquake observations. Machine learning (ML) was applied to seismic damage data of residential buildings in Mexico City following the 2017 Puebla earthquake and in Christchurch following the 2010-2011 Canterbury earthquake sequence (CES). The experience showcased that it is readily possible to develop empirical data only driven models that can successfully identify key damage drivers and hidden underlying correlations without prior engineering knowledge. With adequate maintenance, such models have the potential to be rapidly and easily updated to allow improved damage and loss prediction accuracy and greater ability for models to be generalised. For ML models developed for the key events of the CES, the model trained using data from the 22 February 2011 event generalised the best for loss prediction. This is thought to be because of the large number of instances available for this event and the relatively limited class imbalance between the categories of the target attribute. For the CES, ML highlighted the importance of peak ground acceleration (PGA), building age, building size, liquefaction occurrence, and soil conditions as main factors which affected the losses in residential buildings in Christchurch. ML also highlighted the influence of liquefaction on the buildings losses related to the 22 February 2011 event. Further to the ML model development, the application of post-hoc methodologies was shown to be an effective way to derive insights for ML algorithms that are not intrinsically interpretable. Overall, these provide a basis for the development of ‘greybox’ ML models.

Research papers, University of Canterbury Library

In this thesis, focus is given to develop methodologies for rapidly estimating specific components of loss and downtime functions. The thesis proposes methodologies for deriving loss functions by (i) considering individual component performance; (ii) grouping them as per their performance characteristics; and (iii) applying them to similar building usage categories. The degree of variation in building stock and understanding their characteristics are important factors to be considered in the loss estimation methodology and the field surveys carried out to collect data add value to the study. To facilitate developing ‘downtime’ functions, this study investigates two key components of downtime: (i) time delay from post-event damage assessment of properties; and (ii) time delay in settling the insurance claims lodged. In these two areas, this research enables understanding of critical factors that influence certain aspects of downtime and suggests approaches to quantify those factors. By scrutinising the residential damage insurance claims data provided by the Earthquake Commission (EQC) for the 2010- 2011 Canterbury Earthquake Sequence (CES), this work provides insights into various processes of claims settlement, the time taken to complete them and the EQC loss contributions to building stock in Christchurch city and Canterbury region. The study has shown diligence in investigating the EQC insurance claim data obtained from the CES to get new insights and build confidence in the models developed and the results generated. The first stage of this research develops contribution functions (probabilistic relationships between the expected losses for a wide range of building components and the building’s maximum response) for common types of claddings used in New Zealand buildings combining the probabilistic density functions (developed using the quantity of claddings measured from Christchurch buildings), fragility functions (obtained from the published literature) and cost functions (developed based on inputs from builders) through Monte Carlo simulations. From the developed contribution functions, glazing, masonry veneer, monolithic and precast concrete cladding systems are found to incur 50% loss at inter-storey drift levels equal to 0.027, 0.003, 0.005 and 0.011, respectively. Further, the maximum expected cladding loss for glazing, masonry veneer, monolithic, precast concrete cladding systems are found to be 368.2, 331.9, 365.0, and 136.2 NZD per square meter of floor area, respectively. In the second stage of this research, a detailed cost breakdown of typical buildings designed and built for different purposes is conducted. The contributions of structural and non- structural components to the total building cost are compared for buildings of different usages, and based on the similar ratios of non-structural performance group costs to the structural performance group cost, four-building groups are identified; (i) Structural components dominant group: outdoor sports, stadiums, parkings and long-span warehouses, (ii) non- structural drift-sensitive components dominant group: houses, single-storey suburban buildings (all usages), theatres/halls, workshops and clubhouses, (iii) non-structural acceleration- sensitive components dominant group: hospitals, research labs, museums and retail/cold stores, and (iv) apartments, hotels, offices, industrials, indoor sports, classrooms, devotionals and aquariums. By statistically analysing the cost breakdowns, performance group weighting factors are proposed for structural, and acceleration-sensitive and drift-sensitive non-structural components for all four building groups. Thus proposed building usage groupings and corresponding weighting factors facilitate rapid seismic loss estimation of any type of building given the EDPs at storey levels are known. A model for the quantification of post-earthquake inspection duration is developed in the third stage of this research. Herein, phase durations for the three assessment phases (one rapid impact and two rapid building) are computed using the number of buildings needing inspections, the number of engineers involved in inspections and a phase duration coefficient (which considers the median building inspection time, efficiency of engineer and the number of engineers involved in each assessment teams). The proposed model can be used: (i) by national/regional authorities to decide the length of the emergency period following a major earthquake, and estimate the number of engineers required to conduct a post-earthquake inspection within the desired emergency period, and (ii) to quantify the delay due to inspection for the downtime modelling framework. The final stage of this research investigates the repair costs and insurance claim settlement time for damaged residential buildings in the 2010-2011 Canterbury earthquake sequence. Based on the EQC claim settlement process, claims are categorized into three groups; (i) Small Claims: claims less than NZD15,000 which were settled through cash payment, (ii) Medium Claims: claims less than NZD100,000 which were managed through Canterbury Home Repair Programme (CHRP), and (iii) Large Claims: claims above NZD100,000 which were managed by an insurance provider. The regional loss ratio (RLR) for greater Christchurch for three events inducing shakings of approximate seismic intensities 6, 7, and 8 are found to be 0.013, 0.066, and 0.171, respectively. Furthermore, the claim duration (time between an event and the claim lodgement date), assessment duration (time between the claim lodgement day and the most recent assessment day), and repair duration (time between the most recent assessment day and the repair completion day) for the insured residential buildings in the region affected by the Canterbury earthquake sequence is found to be in the range of 0.5-4 weeks, 1.5- 5 months, and 1-3 years, respectively. The results of this phase will provide useful information to earthquake engineering researchers working on seismic risk/loss and insurance modelling.