This article presents a subset of findings from a larger mixed methods CEISMIC1 funded study of twenty teachers’ earthquake experiences and post-earthquake adjustment eighteen months after a fatal earthquake struck Christchurch New Zealand, in the middle of a school day (Geonet Science, 2011; O’Toole & Friesen, 2016). This earthquake was a significant national and personal disaster with teachers’ emotional self-management as first responders being crucial to the students’ immediate safety (O’Toole & Friesen, 2016). At the beginning of their semi-structured interviews conducted eighteen months later, the teachers shared their earthquake stories (O’Toole & Friesen, 2016). They recalled the moment it struck in vivid detail, describing their experiences in terms of what they saw (destruction), heard (sonic boom, screaming children) and felt (fright and fear) as though they were back in that moment similar to flashbulb memory (Brown & Kulik, 1977). Their memories of the early aftermath were similarly vivid (Rubin & Kozin, 1984). This article focuses on how the mood meter (Brackett & Kremenitzer, 2011) was then used (with permission) to further explore the teachers’ perceived affect to enlighten their lived experiences.
The increase of the world's population located near areas prone to natural disasters has given rise to new ‘mega risks’; the rebuild after disasters will test the governments’ capabilities to provide appropriate responses to protect the people and businesses. During the aftermath of the Christchurch earthquakes (2010-2012) that destroyed much of the inner city, the government of New Zealand set up a new partnership between the public and private sector to rebuild the city’s infrastructure. The new alliance, called SCIRT, used traditional risk management methods in the many construction projects. And, in hindsight, this was seen as one of the causes for some of the unanticipated problems. This study investigated the risk management practices in the post-disaster recovery to produce a specific risk management model that can be used effectively during future post-disaster situations. The aim was to develop a risk management guideline for more integrated risk management and fill the gap that arises when the traditional risk management framework is used in post-disaster situations. The study used the SCIRT alliance as a case study. The findings of the study are based on time and financial data from 100 rebuild projects, and from surveying and interviewing risk management professionals connected to the infrastructure recovery programme. The study focussed on post-disaster risk management in construction as a whole. It took into consideration the changes that happened to the people, the work and the environment due to the disaster. System thinking, and system dynamics techniques have been used due to the complexity of the recovery and to minimise the effect of unforeseen consequences. Based on an extensive literature review, the following methods were used to produce the model. The analytical hierarchical process and the relative importance index have been used to identify the critical risks inside the recovery project. System theory methods and quantitative graph theory have been used to investigate the dynamics of risks between the different management levels. Qualitative comparative analysis has been used to explore the critical success factors. And finally, causal loop diagrams combined with the grounded theory approach has been used to develop the model itself. The study identified that inexperienced staff, low management competency, poor communication, scope uncertainty, and non-alignment of the timing of strategic decisions with schedule demands, were the key risk factors in recovery projects. Among the critical risk groups, it was found that at a strategic management level, financial risks attracted the highest level of interest, as the client needs to secure funding. At both alliance-management and alliance-execution levels, the safety and environmental risks were given top priority due to a combination of high levels of emotional, reputational and media stresses. Risks arising from a lack of resources combined with the high volume of work and the concern that the cost could go out of control, alongside the aforementioned funding issues encouraged the client to create the recovery alliance model with large reputable construction organisations to lock in the recovery cost, at a time when the scope was still uncertain. This study found that building trust between all parties, clearer communication and a constant interactive flow of information, established a more working environment. Competent and clear allocation of risk management responsibilities, cultural shift, risk prioritisation, and staff training were crucial factors. Finally, the post-disaster risk management (PDRM) model can be described as an integrated risk management model that considers how the changes which happened to the environment, the people and their work, caused them to think differently to ease the complexity of the recovery projects. The model should be used as a guideline for recovery systems, especially after an earthquake, looking in detail at all the attributes and the concepts, which influence the risk management for more effective PDRM. The PDRM model is represented in Causal Loops Diagrams (CLD) in Figure 8.31 and based on 10 principles (Figure 8.32) and 26 concepts (Table 8.1) with its attributes.
Predicting building collapse due to seismic motion is critical in design and more so after a major event. Damaged structures can appear sound, but collapse under following major events. There can thus be significant risk in decision making after a major seismic event concerning the safe occupation of a building or surrounding areas, versus the unknown impact of unknown major aftershocks. Model-based pushover analyses are effective if the structural properties are well understood, which is not valid post-event when this risk information is most useful. This research combines Hysteresis Loop Analysis (HLA) structural health monitoring (SHM) and Incremental Dynamic Analysis (IDA) methods to determine collapse capacity and probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. The nonlinear dynamic analysis method presented enables constant updating of building performance predictions using post-event SHM results. The resulting combined methods provide near real-time updating of collapse fragility curves as events progress, quantifying the change of collapse probability or seismic induced losses for decision-making - a novel, higher resolution risk analysis than previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model. Results show significant potential benefits and a clear evolution of risk. They also show clear need for extending SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010-2011 had significant post-event aftershocks after each main event. Finally, the overall method is generalisable to any typical engineering demand parameter.
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Prediction of building collapse due to significant seismic motion is a principle objective of earthquake engineers, particularly after a major seismic event when the structure is damaged and decisions may need to be made rapidly concerning the safe occupation of a building or surrounding areas. Traditional model-based pushover analyses are effective, but only if the structural properties are well understood, which is not the case after an event when that information is most useful. This paper combines hysteresis loop analysis (HLA) structural health monitoring (SHM) and incremental dynamic analysis (IDA) methods to identify and then analyse collapse capacity and the probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. This nonlinear dynamic analysis enables constant updating of building performance predictions following a given and subsequent earthquake events, which can result in difficult to identify deterioration of structural components and their resulting capacity, all of which is far more difficult using static pushover analysis. The combined methods and analysis provide near real-time updating of the collapse fragility curves as events progress, thus quantifying the change of collapse probability or seismic induced losses very soon after an earthquake for decision-making. Thus, this combination of methods enables a novel, higher-resolution analysis of risk that was not previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model, thus providing a relatively simpler means of assessing collapse probability immediately post-event when such speed can provide better information for critical decision-making. Finally, the results also show a clear need to extend the area of SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010–2011 had significant post-event aftershocks.
The ultimate goal of this study is to develop a model representing the in-plane behaviour of plasterboard ceiling diaphragms, as part of the efforts towards performance-based seismic engineering of low-rise light timber-framed (LTF) residential buildings in New Zealand (NZ). LTF residential buildings in NZ are constructed according to a prescriptive standard – NZS 3604 Timberframed buildings [1]. With regards to seismic resisting systems, LTF buildings constructed to NZS3604 often have irregular bracing arrangements within a floor plane. A damage survey of LTF buildings after the Canterbury earthquake revealed that structural irregularity (irregular bracing arrangement within a plane) significantly exacerbated the earthquake damage to LTF buildings. When a building has irregular bracing arrangements, the building will have not only translational deflections but also a torsional response in earthquakes. How effectively the induced torsion can be resolved depends on the stiffness of the floors/roof diaphragms. Ceiling and floor diaphragms in LTF buildings in NZ have different construction details from the rest of the world and there appears to be no information available on timber diaphragms typical of NZ practice. This paper presents experimental studies undertaken on plasterboard ceiling diaphragms as typical of NZ residential practice. Based on the test results, a mathematical model simulating the in-plane stiffness of plasterboard ceiling diaphragms was developed, and the developed model has a similar format to that of plasterboard bracing wall elements presented in an accompany paper by Liu [2]. With these two models, three-dimensional non-linear push-over studies of LTF buildings can be undertaken to calculate seismic performance of irregular LTF buildings.
Collective identity construction in organisations engaged in an inter-organisational collaboration (IOC), especially temporary IOCs set up in disaster situations, has received scant attention in the organisational studies literature yet collective identity is considered to be important in fostering effective IOC operations. This doctoral study was designed to add to our understanding about how collective identity is constituted throughout the entire lifespan of a particular temporary coopetitive (i.e., simultaneously collaborative and competitive) IOC formed in a post-disaster environment. To achieve this purpose, a qualitative case study of the Stronger Christchurch Infrastructure Rebuild Team (SCIRT), a time-bound coopetition formed to repair the horizontal infrastructure in Christchurch, New Zealand after the devastating 2011 Canterbury earthquakes, was undertaken. Using data from semi-structured interviews, field observations, and organisational documents and other artefacts, an inductive analytic method was employed to explore how internal stakeholders engaged with and co- constructed a collective SCIRT identity and reconciled this with their home organization identity. The analysis revealed that the SCIRT collective identity was an ongoing process, involving the interweaving of social, temporal, material and geospatial dimensions constructed through intersecting cycles of senior managers’ sensegiving and employees’ sensemaking across SCIRT’s five and a half years of existence. Senior management deliberately undertook identity work campaigns that used organisational rituals, artefacts, and spatial design to disseminate and encourage a sense of “we are all SCIRT”. However, there was no common sense of “we-ness”. Identification with SCIRT was experienced differently among different groups of employees and across time. Employees’ differing senses of collective identity were accounted for by their past, present, and anticipated future relationships with their home organisation, and also (re)shaped by the geosocial environments in which they worked. The study supports previous research claiming that collective identity is a process of recursive sensegiving and sensemaking between senior managers and employees. However, it extends the literature by revealing the imbricated nature of collective identity, how members’ sense of “who we are” can change across the entire lifetime of a temporary IOC, and how sociomateriality, temporality, and geosocial effects strongly intervene in employees’ emerging senses of collective identity. Moreover, the study demonstrates how the ongoing identity work can be embedded in a time-space frame that further accentuates the influence of temporality, especially the anticipated future, organisational rituals, artefacts, and the geosocial environment. The study’s primary contribution to theory is a processual model of collective identity that applies specifically to a temporary IOC involving coopetition. In doing so, it represents a more finely nuanced and situational model than existing models. At a practical level, this model suggests that managers need to appreciate that organisational artefacts, rituals, and the prevailing organisational geosocial environment are inextricably linked in processes that can be manipulated to enhance the construction of collective identity.
This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
The development of Digital City technologies to manage and visualise spatial information has increasingly become a focus of the research community, and application by city authorities. Traditionally, the Geographic Information Systems (GIS) and Building Information Models (BIM) underlying Digital Cities have been used independently. However, integrating GIS and BIM into a single platform provides benefits for project and asset management, and is applicable to a range of issues. One of these benefits is the means to access and analyse large datasets describing the built environment, in order to characterise urban risk from and resilience to natural hazards. The aim of this thesis is to further explore methodologies of integration in two distinct areas. The first, integration through connectivity of heterogeneous datasets where GIS spatial infrastructure data is merged with 3D BIM building data to create a digital twin. Secondly, integration through analysis whereby data from the digital twin are extracted and integrated with computational models. To achieve this, a workflow was developed to identify the required datasets of a digital twin, and develop a process of integrating those datasets through a combination of; semi-autonomous conversion, translation and extension of data; and semantic web and services-based processes. Through use of a designed schema, the data were streamed in a homogenous format in a web-based platform. To demonstrate the value of this workflow with respect to urban risk and resilience, the process was applied to the Taiora: Queen Elizabeth II recreation and sports centre in eastern Christchurch, New Zealand. After integration of as-built GIS and BIM datasets, targeted data extraction was implemented, with outputs tailored for analysis in an infrastructure serviceability loss model, which assessed potable water network performance in the 22nd February 2011 Christchurch Earthquake. Using the same earthquake conditions as the serviceability loss model, performance of infrastructure assets in service at the time of the 22nd February 2011 Christchurch Earthquake was compared to new assets rebuilt at the site, post-earthquake. Due to improved potable water infrastructure resilience resulting from installation of ductile piles, a decrease of 35.5% in the probability of service loss was estimated in the serviceability loss model. To complete the workflow, the results from the external analysis were uploaded to the web-based platform. One of the more significant outcomes from the workflow was the identification of a lack of mandated metadata standards for fittings/valves connecting a building to private laterals. Whilst visually the GIS and BIM data show the building and pipes as connected, the semantic data does not include this connectivity relationship. This has no material impact on the current serviceability loss model as it is not one of the defined parameters. However, a proposed modification to the model would utilise the metadata to further assess the physical connection robustness, and increase the number of variables for estimating probability of service loss. This thesis has made a methodological contribution to urban resilience analysis by demonstrating how readily available up-to-date building and infrastructure data can be integrated, and with tailored extraction from a Digital City platform, be used for disaster impact analysis in an external computational engine, with results in turn imported and visualised in the Digital City platform. The workflow demonstrated that translation and integration of data would be more successful if a regional/national mandate was implemented for the submission of consent documentation in a specified standard BIM format. The results of this thesis have identified that the key to ensuring the success of an integrated tool lies in the initial workflow required to safeguard that all data can be either captured or translated in an interoperable format.
The development of Digital City technologies to manage and visualise spatial information has increasingly become a focus of the research community, and application by city authorities. Traditionally, the Geographic Information Systems (GIS) and Building Information Models (BIM) underlying Digital Cities have been used independently. However, integrating GIS and BIM into a single platform provides benefits for project and asset management, and is applicable to a range of issues. One of these benefits is the means to access and analyse large datasets describing the built environment, in order to characterise urban risk from and resilience to natural hazards. The aim of this thesis is to further explore methodologies of integration in two distinct areas. The first, integration through connectivity of heterogeneous datasets where GIS spatial infrastructure data is merged with 3D BIM building data to create a digital twin. Secondly, integration through analysis whereby data from the digital twin are extracted and integrated with computational models. To achieve this, a workflow was developed to identify the required datasets of a digital twin, and develop a process of integrating those datasets through a combination of; semi-autonomous conversion, translation and extension of data; and semantic web and services-based processes. Through use of a designed schema, the data were streamed in a homogenous format in a web-based platform. To demonstrate the value of this workflow with respect to urban risk and resilience, the process was applied to the Taiora: Queen Elizabeth II recreation and sports centre in eastern Christchurch, New Zealand. After integration of as-built GIS and BIM datasets, targeted data extraction was implemented, with outputs tailored for analysis in an infrastructure serviceability loss model, which assessed potable water network performance in the 22nd February 2011 Christchurch Earthquake. Using the same earthquake conditions as the serviceability loss model, performance of infrastructure assets in service at the time of the 22nd February 2011 Christchurch Earthquake was compared to new assets rebuilt at the site, post-earthquake. Due to improved potable water infrastructure resilience resulting from installation of ductile piles, a decrease of 35.5% in the probability of service loss was estimated in the serviceability loss model. To complete the workflow, the results from the external analysis were uploaded to the web-based platform. One of the more significant outcomes from the workflow was the identification of a lack of mandated metadata standards for fittings/valves connecting a building to private laterals. Whilst visually the GIS and BIM data show the building and pipes as connected, the semantic data does not include this connectivity relationship. This has no material impact on the current serviceability loss model as it is not one of the defined parameters. However, a proposed modification to the model would utilise the metadata to further assess the physical connection robustness, and increase the number of variables for estimating probability of service loss. This thesis has made a methodological contribution to urban resilience analysis by demonstrating how readily available up-to-date building and infrastructure data can be integrated, and with tailored extraction from a Digital City platform, be used for disaster impact analysis in an external computational engine, with results in turn imported and visualised in the Digital City platform. The workflow demonstrated that translation and integration of data would be more successful if a regional/national mandate was implemented for the submission of consent documentation in a specified standard BIM format. The results of this thesis have identified that the key to ensuring the success of an integrated tool lies in the initial workflow required to safeguard that all data can be either captured or translated in an interoperable format.