There is a growing awareness of the need for the earthquake engineering practice to incorporate in addition to empirical approaches in evaluation of liquefaction hazards advanced methods which can more realistically represent soil behaviour during earthquakes. Currently, this implementation is hindered by a number of challenges mainly associated with the amount of data and user-experience required for such advanced methods. In this study, we present key steps of an advanced seismic effective-stress analysis procedure, which on the one hand can be fully automated and, on the other hand, requires no additional input (at least for preliminary applications) compared to simplified cone penetration test (CPT)-based liquefaction procedures. In this way, effective-stress analysis can be routinely applied for quick, yet more robust estimations of liquefaction hazards, in a similar fashion to the simplified procedures. Important insights regarding the dynamic interactions in liquefying soils and the actual system response of a deposit can be gained from such analyses, as illustrated with the application to two sites from Christchurch, New Zealand.
INTRODUCTION: After the 2011 Canterbury earthquake, the provision of school social work was extended into a larger number of schools in the greater Christchurch region to support discussions of their practice priorities and responses in post-earthquake schools. FINDINGS: Two main interpretations of need are reflected in the school social workers’ accounts of their work with children and families. Firstly, hardship-focused need, which represented children as adversely influenced by their home circumstances; the interventions were primarily with parents. These families were mainly from schools in low socioeconomic areas. Secondly, anxiety-based need, a newer practice response, which emphasised children who were considered particularly susceptible to the impacts of the disaster event. This article considers how these practitioners conceptualised and responded to the needs of the children and their families in this context. METHOD: A qualitative study examining recovery policy and school social work practice following the earthquakes including 12 semi-structured interviews with school social workers. This article provides a Foucauldian analysis of the social worker participants’ perspectives on emotional and psychological issues for children, particularly those from middle-class families; the main interventions were direct therapeutic work with children themselves. Embedded within these practice accounts are moments in which the social workers contested the predominant, individualising conceptualisations of need to enable more open-ended, negotiable, interconnected relationships in post-earthquake schools. IMPLICATIONS: In the aftermath of disasters, school social workers can reflect on their preferred practice responses and institutional influences in schools to offer children and families opportunities to reject the prevalent norms of risk and vulnerability.
Social and natural capital are fundamental to people’s wellbeing, often within the context of local community. Developing communities and linking people together provide benefits in terms of mental well-being, physical activity and other associated health outcomes. The research presented here was carried out in Christchurch - Ōtautahi, New Zealand, a city currently re-building, after a series of devastating earthquakes in 2010 and 2011. Poor mental health has been shown to be a significant post-earthquake problem, and social connection has been postulated as part of a solution. By curating a disparate set of community services, activities and facilities, organised into a Geographic Information Systems (GIS) database, we created i) an accessibility analysis of 11 health and well-being services, ii) a mobility scenario analysis focusing on 4 general well-being services and iii) a location-allocation model focusing on 3 primary health care and welfare location optimisation. Our results demonstrate that overall, the majority of neighbourhoods in Christchurch benefit from a high level of accessibility to almost all the services; but with an urban-rural gradient (the further away from the centre, the less services are available, as is expected). The noticeable exception to this trend, is that the more deprived eastern suburbs have poorer accessibility, suggesting social inequity in accessibility. The findings presented here show the potential of optimisation modelling and database curation for urban and community facility planning purposes.
Pumice materials, which are problematic from an engineering viewpoint, are widespread in the central part of the North Island. Considering the impacts of the 2010-2011 Christchurch earthquakes, a clear understanding of their properties under earthquake loading is necessary. For example, the 1987 Edgecumbe earthquake showed evidence of localised liquefaction of sands of volcanic origin. To elucidate on this, research was undertaken to investigate whether existing empirical field-based methods to evaluate the liquefaction potential of sands, which were originally developed for hard-grained soils, are applicable to crushable pumice-rich deposits. For this purpose, two sites, one in Whakatane and another in Edgecumbe, were selected where the occurrence of liquefaction was reported following the Edgecumbe earthquake. Manifestations of soil liquefaction, such as sand boils and ejected materials, have been reported at both sites. Field tests, including cone penetration tests (CPT), shear-wave velocity profiling, and screw driving sounding (SDS) tests were performed at the sites. Then, considering estimated peak ground accelerations (PGAs) at the sites based on recorded motions and possible range of ground water table locations, liquefaction analysis was conducted at the sites using available empirical approaches. To clarify the results of the analysis, undisturbed soil samples were obtained at both sites to investigate the laboratory-derived cyclic resistance ratios and to compare with the field-estimated values. Research results clearly showed that these pumice-rich soils do not fit existing liquefaction assessment frameworks and alternate methods are necessary to characterise them.
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.
The initial goal of this research was to explore how SME business models change in response to a crisis. Keeping this in mind, the business model canvas (Osterwalder & Pigneur, 2010) was used as a tool to analyse SME business models in the Canterbury region of New Zealand. The purpose was to evaluate the changes SMEs instituted in their business models after being hit by a series of earthquakes in 2010 and 2011. The idea was to conduct interviews with business owners and analyse them using grounded theory methods. As this method is iterative and requires simultaneous data collection and analysis, a tentative model was proposed after first phase of the data collection and analysis. However, as a result of this process, it became apparent that owner-specific characteristics, action orientation and networks were more prominent in the data than business model elements. Although the SMEs in this study experienced several operational changes in their business models, such as a change of location, modifications to their payment terms or expanded/restricted target markets, the suggested framework highlights how owner-specific attributes ensured the recovery of their businesses. After the initial framework was suggested, subsequent interviews were conducted to test, verify, and modify the tentative model. Three aspects of business recovery emerged: (a) cognitive coping – the business owner’s mind-set and motive; (b) adaptive coping – the ability of business owner to take corrective actions; and (c) social capital – the social network of a business owner, including formal and informal connections and their significance. Three distinct groups were identified; self-sufficient SMEs, socially-based SMEs and surviving SMEs. This thesis proposes a grounded theory of business recovery for SMEs following a disaster. Cognitive coping and social capital enabled the owners to take actions, which eventually led to the desired outcomes for the businesses.
Rapid, accurate structural health monitoring (SHM) assesses damage to optimise decision-making. Many SHM methods are designed to track nonlinear stiffness changes as damage. However, highly nonlinear pinched hysteretic systems are problematic in SHM. Model-based SHM often fails as any mismatch between model and measured response dynamics leads to significant error. Thus, modelfree methods of hysteresis loop tracking methods have emerged. This study compares the robustness and accuracy in the presence of significant measurement noise of the proven hysteresis loop analysis (HLA) SHM method with 3 emerging model-free methods and 2 further novel adaptations of these methods using a highly nonlinear, 6-story numerical structure to provide a known ground-truth. Mean absolute errors in identifying a known nonlinear stiffness trajectory assessed at four points over two successive ground motion inputs from September 2010 and February 2011 in Christchurch range from 1.71-10.52%. However, the variability is far wider with maximum errors ranging from 3.90-49.72%, where the second largest maximum absolute error was still 19.74%. The lowest mean and maximum absolute errors were for the HLA method. The next best method had mean absolute error of 2.92% and a maximum of 10.51%. These results show the clear superiority of the HLA method over all current emerging model-free methods designed to manage the highly nonlinear pinching responses common in reinforced concrete structures. These results, combined with high robustness and accuracy in scaled and fullscale experimental studies, provide further validation for using HLA for practical implementation.
High-quality ground motion records are required for engineering applications including response history analysis, seismic hazard development, and validation of physics-based ground motion simulations. However, the determination of whether a ground motion record is high-quality is poorly handled by automation with mathematical functions and can become prohibitive if done manually. Machine learning applications are well-suited to this problem, and a previous feed-forward neural network was developed (Bellagamba et al. 2019) to determine high-quality records from small crustal events in the Canterbury and Wellington regions for simulation validation. This prior work was however limited by the omission of moderate-to-large magnitude events and those from other tectonic environments, as well as a lack of explicit determination of the minimum usable frequency of the ground motion. To address these shortcomings, an updated neural network was developed to predict the quality of ground motion records for all magnitudes and all tectonic sources—active shallow crustal, subduction intraslab, and subduction interface—in New Zealand. The predictive performance of the previous feed-forward neural network was matched by the neural network in the domain of small crustal records, and this level of predictive performance is now extended to all source magnitudes and types in New Zealand making the neural network applicable to global ground motion databases. Furthermore, the neural network provides quality and minimum usable frequency predictions for each of the three orthogonal components of a record which may then be mapped into a binary quality decision or otherwise applied as desired. This framework provides flexibility for the end user to predict high-quality records with various acceptability thresholds allowing for this neural network to be used in a range of applications.
Reconnaissance reports have highlighted the poor performance of non-ductile reinforced concrete buildings during the 2010-11 Canterbury earthquakes. These buildings are widely expected to result in significant losses under future earthquakes due to their seismic vulnerability and prevalence in densely populated urban areas. Wellington, for example, contains more than 70 pre-1970s multi-storey reinforced concrete buildings, ranging in height from 5 to 18 storeys. This study seeks to characterise the seismic performance and evaluate the likely failure modes of a typical pre-1970s reinforced concrete building in Wellington, by conducting advanced numerical simulations to evaluate its 3D nonlinear dynamic response. A representative 9-storey office building constructed in 1951 is chosen for this study and modelled in the finite element analysis programme DIANA, using a previously developed and validated approach to predict the failure modes of doubly reinforced walls with confined boundary regions. The structure consists of long walls and robust framing elements resulting in a stiff lateral load resisting system. Barbell-shaped walls are flanked by stiff columns with sufficient transverse reinforcement to serve as boundary regions. Curved shell elements are used to model the walls and their boundary columns, for which the steel reinforcement is explicitly modelled. Line elements are used to model the frame elements. The steel reinforcement in each member is explicitly modelled. The floor slabs are modelled using elastic shell elements. The model is analysed under short and long duration ground motions selected to match site specific targets in Wellington at the DBE and MCE intensity levels. The observed response of the building including drift profiles at each intesity level, strain localization effects around wall openings, and the influence of bidirectional loading are discussed.
Exploring women’s experiences of entering, working in, or leaving the Christchurch construction industry between 2010 and 2018 led to the creation of the theory of “deferential tailoring.” Deferential tailoring explains how women shape their responses to industry conditions as an intentional behavioural adjustment process. Most importantly, this theory provides insight into women’s unseen efforts to build positive workplace relationships, their capability to advance, and challenges to existing views of gender roles in this context. Research on women in construction focusses primarily on identifying and explaining barriers that impact on women’s entry, progression, and retention in the industry. There is an absence of process studies that explain the actions women take to manage industry conditions in business-as-usual, let alone post-disaster contexts. In the eight years following the 2010 Canterbury (New Zealand) earthquakes, rapid changes to the construction industry meant women had unprecedented access and new opportunities in this historically male-dominated domain. This setting provided a unique context within which to investigate how women respond to industry opportunities and challenges. The aim of this interpretive research was to construct a response theory, particular to women working in the Christchurch construction industry. Applying a constructivist grounded theory approach, theoretical sampling, coding and memo writing allowed for the collection and comparative analysis of 36 semi-structured interviews conducted with women working in a cross-section of industry occupations. Three inter- related categories were built: capitalising on opportunity, building capability and token tolerance, which together constitute the deferential tailoring process. Akin to building an invisible glass scaffold, women intentionally regulate their behaviours to successfully seize opportunities and manage social challenges. In building this scaffold, women draw heavily on personal values and positive, proactive attributes as a response to industry conditions. In contrast to previous research, which suggests that women conform to the male-dominated norms of the industry, the theory of deferential tailoring proposes that women are prepared to regulate their behaviour to address the gendered norms that impact on their work experiences. This research contributes towards an evolving body of knowledge that aims to understand how women’s entry into the construction industry, retention, and workplace relationships can be improved. By expanding the view of how women respond to industry conditions over time, this research has generated knowledge that addresses gaps in construction industry literature relating to the management of coping strategies, capitalising on opportunities, and building positive workplace relationships. Knowledge and concepts generated from this research could be integrated into recruitment and training programmes to enhance women’s professional development, shift perceptions of women’s work, and address cultural norms that impact on women’s retention in the construction industry.
