The 2015 New Zealand strong-motion database provides a wealth of new strong motion data for engineering applications. An important component of this database is the compilation of new site metadata, describing the soil conditions and site response at GeoNet strong motion stations. We have assessed and compiled four key site parameters for the ~460 GeoNet stations that recorded significant historical ground motions. Parameters include: site classification (NZS1170.5), Vs30, fundamental site period (Tsite) and depth to bedrock (Z1.0, i.e. depth to material with Vs > 1000 m/s). In addition, we have assigned a quality estimate (Quality 1 – 3) to these parameters to provide a qualitative estimate of the uncertainty. New highquality Tsite estimates have largely been obtained from newly available HVSR amplification curves and spectral ratios from inversion of regional strong motion data that has been reconciled with available geological information. Good quality Vs30 estimates, typically in urban centres, have also been incorporated following recent studies. Where site-specific measurements of Vs30 are not available, Vs30 is estimated based on surface geology following national Vs30 maps. New Z1.0 values have been provided from 3D subsurface models for Canterbury and Wellington. This database will be used in efforts to guide development and testing of new and existing ground motion prediction models in New Zealand. In particular, it will allow reexamination of the most important site parameters that control and predict site response in a New Zealand setting. Furthermore, it can be used to provide information about suitable rock reference sites for seismological research, and as a guide to site-specific references in the literature. We discuss compilation of the database, preliminary insights so far, and future directions.
This study analyses the Earthquake Commission’s (EQC) insurance claims database to investigate the influence of seismic intensity and property damage resulting from the Canterbury Earthquake Sequence (CES) on the repair costs and claim settlement duration for residential buildings. Firstly, the ratio of building repair cost to its replacement cost was expressed as a Building Loss Ratio (BLR), which was further extended to Regional Loss Ratio (RLR) for greater Christchurch by multiplying the average of all building loss ratios with the proportion of building stock that lodged an insurance claim. Secondly, the total time required to settle the claim and the time taken to complete each phase of the claim settlement process were obtained. Based on the database, the regional loss ratio for greater Christchurch for three events producing shakings of intensities 6, 7, and 8 on the modified Mercalli intensity scale were 0.013, 0.066, and 0.171, respectively. Furthermore, small (less than NZD15,000), medium (between NZD15,000 and NZD100,000), and large (more than NZD100,000) claims took 0.35-0.55, 1.95-2.45, and 3.35-3.85 years to settle regardless of the building’s construction period and earthquake intensities. The number of claims was also disaggregated by various building characteristics to evaluate their relative contribution to the damage and repair costs.
Case study analysis of the 2010-2011 Canterbury Earthquake Sequence (CES), which particularly impacted Christchurch City, New Zealand, has highlighted the value of practical, standardised and coordinated post-earthquake geotechnical response guidelines for earthquake-induced landslides in urban areas. The 22nd February 2011 earthquake, the second largest magnitude event in the CES, initiated a series of rockfall, cliff collapse and loess failures around the Port Hills which severely impacted the south-eastern part of Christchurch. The extensive slope failure induced by the 22nd February 200 earthquake was unprecedented; and ground motions experienced significantly exceeded the probabilistic seismic hazard model for Canterbury. Earthquake-induced landslides initiated by the 22nd February 2011 earthquake posed risk to life safety, and caused widespread damage to dwellings and critical infrastructure. In the immediate aftermath of the 22nd February 2011 earthquake, the geotechnical community responded by deploying into the Port Hills to conduct assessment of slope failure hazards and life safety risk. Coordination within the voluntary geotechnical response group evolved rapidly within the first week post-earthquake. The lack of pre-event planning to guide coordinated geotechnical response hindered the execution of timely and transparent management of life safety risk from coseismic landslides in the initial week after the earthquake. Semi-structured interviews were conducted with municipal, management and operational organisations involved in the geotechnical response during the CES. Analysis of interview dialogue highlighted the temporal evolution of priorities and tasks during emergency response to coseismic slope failure, which was further developed into a phased conceptual model to inform future geotechnical response. Review of geotechnical responses to selected historical earthquakes (Northridge, 1994; Chi-Chi, 1999; Wenchuan, 2008) has enabled comparison between international practice and local response strategies, and has emphasised the value of pre-earthquake preparation, indicating the importance of integration of geotechnical response within national emergency management plans. Furthermore, analysis of the CES and international earthquakes has informed pragmatic recommendations for future response to coseismic slope failure. Recommendations for future response to earthquake-induced landslides presented in this thesis include: the integration of post-earthquake geotechnical response with national Civil Defence and Emergency Management; pre-earthquake development of an adaptive management structure and standard slope assessment format for geotechnical response; and emergency management training for geotechnical professionals. Post-earthquake response recommendations include the development of geographic sectors within the area impacted by coseismic slope failure, and the development of a GIS database for analysis and management of data collected during ground reconnaissance. Recommendations provided in this thesis aim to inform development of national guidelines for geotechnical response to earthquake-induced landslides in New Zealand, and prompt debate concerning international best practice.
Asset management in power systems is exercised to improve network reliability to provide confidence and security for customers and asset owners. While there are well-established reliability metrics that are used to measure and manage business-as-usual disruptions, an increasing appreciation of the consequences of low-probability high-impact events means that resilience is increasingly being factored into asset management in order to provide robustness and redundancy to components and wider networks. This is particularly important for electricity systems, given that a range of other infrastructure lifelines depend upon their operation. The 2010-2011 Canterbury Earthquake Sequence provides valuable insights into electricity system criticality and resilience in the face of severe earthquake impacts. While above-ground assets are relatively easy to monitor and repair, underground assets such as cables emplaced across wide areas in the distribution network are difficult to monitor, identify faults on, and repair. This study has characterised in detail the impacts to buried electricity cables in Christchurch resulting from seismically-induced ground deformation caused primarily by liquefaction and lateral spread. Primary modes of failure include cable bending, stretching, insulation damage, joint braking and, being pulled off other equipment such as substation connections. Performance and repair data have been compiled into a detailed geospatial database, which in combination with spatial models of peak ground acceleration, peak ground velocity and ground deformation, will be used to establish rigorous relationships between seismicity and performance. These metrics will be used to inform asset owners of network performance in future earthquakes, further assess component criticality, and provide resilience metrics.
Fine grained sediment deposition in urban environments during natural hazard events can impact critical infrastructure and properties (urban terrain) leading to reduced social and economic function and potentially adverse public health effects. Therefore, clean-up of the sediments is required to minimise impacts and restore social and economic functionality as soon as possible. The strategies employed to manage and coordinate the clean-up significantly influence the speed, cost and quality of the clean-up operation. Additionally, the physical properties of the fine grained sediment affects the clean-up, transport, storage and future usage of the sediment. The goals of the research are to assess the resources, time and cost required for fine grained sediment clean-up in an urban environment following a disaster and to determine how the geotechnical properties of sediment will affect urban clean-up strategies. The thesis focuses on the impact of fine grained sediment (<1 mm) deposition from three liquefaction events during the Canterbury earthquake sequence (2010-2011) on residential suburbs and transport networks in Christchurch. It also presents how geotechnical properties of the material may affect clean-up strategies and methods by presenting geotechnical analysis of tephra material from the North Island of New Zealand. Finally, lessons for disaster response planning and decision making for clean-up of sediment in urban environments are presented. A series of semi-structured interviews of key stakeholders supported by relevant academic literature and media reports were used to record the clean-up operation coordination and management and to make a preliminary qualification of the Christchurch liquefaction ejecta clean-up (costs breakdown, time, volume, resources, coordination, planning and priorities). Further analysis of the costs and resources involved for better accuracy was required and so the analysis of Christchurch City Council road management database (RAMM) was done. In order to make a transition from general fine sediment clean-up to specific types of fine disaster sediment clean-up, adequate information about the material properties is required as they will define how the material will be handled, transported and stored. Laboratory analysis of young volcanic tephra from the New Zealand’s North Island was performed to identify their geotechnical properties (density, granulometry, plasticity, composition and angle of repose). The major findings of this research were that emergency planning and the use of the coordinated incident management system (CIMS) system during the emergency were important to facilitate rapid clean-up tasking, management of resources and ultimately recovery from widespread and voluminous liquefaction ejecta deposition in eastern Christchurch. A total estimated cost of approximately $NZ 40 million was calculated for the Christchurch City clean-up following the 2010-2011 Canterbury earthquake sequence with a partial cost of $NZ 12 million for the Southern part of the city, where up to 33% (418 km) of the road network was impacted by liquefaction ejecta and required clearing of the material following the 22 February 2011 earthquake. Over 500,000 tonnes of ejecta has been stockpiled at Burwood landfill for all three liquefaction inducing earthquake events. The average cost per kilometre for the event clean-up was $NZ 5,500/km (4 September 2010), $NZ 11,650/km (22 February 2011) and $NZ 11,185/km (13 June 2011). The duration of clean-up time of residential properties and the road network was approximately two to three months for each of the three liquefaction ejecta events; despite events volumes and spatial distribution of ejecta. Interviews and quantitative analysis of RAMM data revealed that the experience and knowledge gained from the Darfield earthquake (4 September 2010) clean-up increased the efficiency of the following Christchurch earthquake induced liquefaction ejecta clean-up events. Density, particle size, particle shape, clay content and moisture content, are the important geotechnical properties that need to be considered when planning for a clean-up method that incorporates collection, transport and disposal or storage. The geotechnical properties for the tephra samples were analysed to increase preparedness and reaction response of potentially affected North Island cities from possible product from the active volcanoes in their region. The geotechnical results from this study show that volcanic tephra could be used in road or construction material but the properties would have to be further investigated for a New Zealand context. Using fresh volcanic material in road, building or flood control construction requires good understanding of the material properties and precaution during design and construction to extra care, but if well planned, it can be economically beneficial.
This thesis describes the management process of innovation through construction infrastructure projects. This research focuses on the innovation management process at the project level from four views. These are categorised into the separate yet related areas of: “innovation definition”, “Project time”, “project team motivation” and “Project temporary organisation”. A practical knowledge is developed for each of these research areas that enables project practitioners to make the best decision for the right type of innovation at the right phase of projects, through a capable project organisation. The research developed a holistic view on both innovation and the construction infrastructure project as two complex phenomena. An infrastructure project is a long-term capital investment, highly risky and an uncertain. Infrastructure projects can play a key role in innovation and performance improvement throughout the construction industry. The delivery of an infrastructure project is affected in most cases by critical issues of budget constraint, programme delays and safety Where the business climate is characterized by uncertainty, risk and a high level of technological change, construction infrastructure projects are unable to cope with the requirement to develop innovation. Innovation in infrastructure projects, as one of the key performance indicators (KPI) has been identified as a critical capability for performance improvement through the industry. However, in spite of the importance of infrastructure projects in improving innovation, there are a few research efforts that have developed a comprehensive view on the project context and its drivers and inhibitors for innovation in the construction industry. Two main reasons are given as the inhibitors through the process of comprehensive research on innovation management in construction. The first reason is the absence of an understanding of innovation itself. The second is a bias towards research at a firm and individual level, so a comprehensive assessment of project-related factors and their effects on innovation in infrastructure projects has not been undertaken. This study overcomes these issues by adopting as a case study approach of a successful infrastructure project. This research examines more than 500 construction innovations generated by a unique infrastructure alliance. SCIRT (Stronger Christchurch Infrastructure Rebuild Team) is a temporary alliancing organisation that was created to rebuild and recover the damaged infrastructure after the Christchurch 2011 earthquake. Researchers were given full access to the innovation project information and innovation systems under a contract with SCIRT Learning Legacy, provided the research with material which is critical for understanding innovations in large, complex alliancing infrastructure organisation. In this research, an innovation classification model was first constructed. Clear definitions have been developed for six types of construction innovation with a variety of level of novelties and benefits. The innovation classification model was applied on the SCIRT innovation database and the resultant trends and behaviours of different types of innovation are presented. The trends and behaviours through different types of SCIRT innovations developed a unique opportunity to research the projectrelated factors and their effect on the behaviour of different classified types of innovation throughout the project’s lifecycle. The result was the identification of specific characteristics of an infrastructure project that affect the innovation management process at the project level. These were categorised in four separate chapters. The first study presents the relationship between six classified types of innovation, the level of novelty and the benefit they come up with, by applying the innovation classification model on SCIRT innovation database. The second study focused on the innovation potential and limitations in different project lifecycle phases by using a logic relationship between the six classified types of innovation and the three classified phases of the SCIRT project. The third study result develops a holistic view of different elements of the SCIRT motivation system and results in a relationship between the maturity level of definition developed for innovation as one of the KPIs and a desire though the SCIRT innovation incentive system to motivate more important innovations throughout the project. The fourth study is about the role of the project’s temporary organisation that finally results in a multiple-view innovation model being developed for project organisation capability assessment in the construction industry. The result of this thesis provides practical and instrumental knowledge to be used by a project practitioner. Benefits of the current thesis could be categorized in four groups. The first group is the innovation classification model that provides a clear definition for six classified types of innovation with four levels of novelty and specifically defined outcomes and the relationship between the innovation types, novelty and benefit. The second is the ability that is provided for the project practitioner to make the best decision for the right type of innovation at the right phases of a project’s lifecycle. The third is an optimisation that is applied on the SCIRT innovation motivation system that enables the project practitioner to incentivize the right type of innovation with the right level of financial gain. This drives the project teams to develop a more important innovation instead of a simple problemsolving one. Finally, the last and probably more important benefit is the recommended multiple-view innovation model. This is a tool that could be used by a project practitioner in order to empower the project team to support innovation throughout the project.
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.
