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Research papers, University of Canterbury Library

Semi-empirical models based on in-situ geotechnical tests have become the standard of practice for predicting soil liquefaction. Since the inception of the “simplified” cyclic-stress model in 1971, variants based on various in-situ tests have been developed, including the Cone Penetration Test (CPT). More recently, prediction models based soley on remotely-sensed data were developed. Similar to systems that provide automated content on earthquake impacts, these “geospatial” models aim to predict liquefaction for rapid response and loss estimation using readily-available data. This data includes (i) common ground-motion intensity measures (e.g., PGA), which can either be provided in near-real-time following an earthquake, or predicted for a future event; and (ii) geospatial parameters derived from digital elevation models, which are used to infer characteristics of the subsurface relevent to liquefaction. However, the predictive capabilities of geospatial and geotechnical models have not been directly compared, which could elucidate techniques for improving the geospatial models, and which would provide a baseline for measuring improvements. Accordingly, this study assesses the realtive efficacy of liquefaction models based on geospatial vs. CPT data using 9,908 case-studies from the 2010-2016 Canterbury earthquakes. While the top-performing models are CPT-based, the geospatial models perform relatively well given their simplicity and low cost. Although further research is needed (e.g., to improve upon the performance of current models), the findings of this study suggest that geospatial models have the potential to provide valuable first-order predictions of liquefaction occurence and consequence. Towards this end, performance assessments of geospatial vs. geotechnical models are ongoing for more than 20 additional global earthquakes.

Research papers, University of Canterbury Library

This paper presents on-going challenges in the present paradigm shift of earthquakeinduced ground motion prediction from empirical to physics-based simulation methods. The 2010-2011 Canterbury and 2016 Kaikoura earthquakes are used to illustrate the predictive potential of the different methods. On-going efforts on simulation validation and theoretical developments are then presented, as well as the demands associated with the need for explicit consideration of modelling uncertainties. Finally, discussion is also given to the tools and databases needed for the efficient utilization of simulated ground motions both in specific engineering projects as well as for near-real-time impact assessment.

Research papers, University of Canterbury Library

Following the Canterbury earthquake sequence of 2010-11, a large and contiguous tract of vacated ‘red zoned’ land lies alongside the lower Ōtākaro / Avon River and is known as the Avon-Ōtākaro Red Zone (AORZ). This is the second report in the Ecological Regeneration Options (ERO) project that addresses future land uses in the AORZ. The purpose of this report is to present results from an assessment of restoration opportunities conducted in April 2017. The objectives of the assessment were to identify potential benefits of ecological restoration activities across both land and water systems in the AORZ and characterise the key options for their implementation. The focus of this report is not to provide specific advice on the methods for achieving specific restoration endpoints per se. This will vary at different sites and scales with a large number of combinations possible. Rather, the emphasis is on providing an overview of the many restoration and regeneration options in their totality across the AORZ. An additional objective is to support their adequate assessment in the identification of optimum land uses and adaptive management practices for the AORZ. Participatory processes may play a useful role in assessment and stakeholder engagement by providing opportunities for social learning and the co-creation of new knowledge. We used a facilitated local knowledge based approach that generated a large quantity of reliable and site specific data in a short period of time. By inviting participation from a wide knowledge-holder network inclusivity is improved in comparison to small-group expert panel approaches. Similar approaches could be applied to other information gathering and assessment needs in the regeneration planning process. Findings from this study represent the most comprehensive set of concepts available to date to address the potential benefits of ecological regeneration in the AORZ. This is a core topic for planning to avoid missed opportunities and opportunity costs. The results identify a wide range of activities that may be applied to generate benefits for Christchurch and beyond, all involving aspects of a potential new ecology in the AORZ. These may be combined at a range of scales to create scenarios, quantify benefits, and explore the potential for synergies between different land use options. A particular challenge is acquiring the information needed within relatively short time frames. Early attention to gathering baseline data, addressing technical knowledge gaps, and developing conceptual frameworks to account for the many spatio-temporal aspects are all key activities that will assist in delivering the best outcomes. Methodologies by which these many facets can be pulled together in quantitative and comparative assessments are the focus of the final report in the ERO series.

Research papers, The University of Auckland Library

Critical infrastructure networks are highly relied on by society such that any disruption to service can have major social and economic implications. Furthermore, these networks are becoming increasingly dependent on each other for normal operation such that an outage or asset failure in one system can easily propagate and cascade across others resulting in widespread disruptions in terms of both magnitude and spatial reach. It is the vulnerability of these networks to disruptions and the corresponding complexities in recovery processes which provide direction to this research. This thesis comprises studies contributing to two areas (i) the modelling of national scale in-terdependent infrastructure systems undergoing major disruptions, and (ii) the tracking and quantification of infrastructure network recovery trajectories following major disruptions. Firstly, methods are presented for identifying nationally significant systemic vulnerabilities and incorporating expert knowledge into the quantification of infrastructure interdependency mod-elling and simulation. With application to the interdependent infrastructures networks across New Zealand, the magnitudes and spatial extents of disruption are investigated. Results high-light the importance in considering interdependencies when assessing disruptive risks and vul-nerabilities in disaster planning applications and prioritising investment decisions for enhancing resilience of national networks. Infrastructure dependencies are further studied in the context of recovery from major disruptions through the analysis of curves measuring network functionality over time. Continued studies into the properties of recovery curves across a database of global natural disasters produce statistical models for predicting the trajectory and expected recovery times. Finally, the use of connectivity based metrics for quantifying infrastructure system functionality during recovery are considered with a case study application to the Christchurch Earthquake (February 22, 2011) wastewater network response.

Research papers, The University of Auckland Library

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.