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.
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.
Christchurch Ōtautahi, New Zealand, is a city of myriad waterways and springs. Māori, the indigenous people of New Zealand, have water quality at the core of their cultural values. The city’s rivers include the Avon/Ōtākaro, central to the city centre’s aesthetic appeal since early settlement, and the Heathcote/Ōpāwaho. Both have been degraded with increasing urbanisation. The destructive earthquake sequence that occurred during 2010/11 presented an opportunity to rebuild significant areas of the city. Public consultation identified enthusiasm to rebuild a sustainable city. A sustainable water sensitive city is one where development is constructed with the water environment in mind. Water sensitive urban design applies at all scales and is a holistic concept. In Christchurch larger-scale multi-value stormwater management solutions were incorporated into rapidly developed greenfield sites on the city’s outskirts and in satellite towns, as they had been pre-earthquake. Individual properties on greenfield sites and within the city, however, continued to be constructed without water sensitive features such as rainwater tanks or living roofs. This research uses semi-structured interviews, policy analysis, and findings from local and international studies to investigate the benefits of building-scale WSUD and the barriers that have resulted in their absence. Although several inter-related barriers became apparent, cost, commonly cited as a barrier to sustainable development in general, was strongly represented. However, it is argued that the issue is one of mindset rather than cost. Solutions are proposed, based on international and national experience, that will demonstrate the benefits of adopting water sensitive urban design principles including at the building scale, and thereby build public and political support. The research is timely - there is still much development to occur, and increasing pressures from urban densification, population growth and climate change to mitigate.
The Canterbury earthquake and aftershock sequence in New Zealand during 2010-2011 subjected the city’s structures to a significant accumulated cyclic demand and raised significant questions regarding the low-cycle fatigue demands imposed upon the structures. There is a significant challenge to quantify the level of cumulative demand imposed on structures and to assess the percentage of a structure's fatigue life that has been consumed as a result of this earthquake sequence. It is important to be able to quantify the cumulative demand to determine how a building will perform in a subsequent large earthquake and inform repair and re-occupancy decisions. This paper investigates the cumulative fatigue demand for a structure located within the Christchurch Central Business District (CBD). Time history analysis and equivalent cycle counting methods are applied across the Canterbury earthquake sequence, using key events from September 4th 2010 and February 22nd , 2011 main shocks. The estimate of the cumulative fatigue demand is then compared to the expected capacity of a case study reinforced concrete bridge pier, to undertake a structure-specific fatigue assessment. The analysis is undertaken to approximate the portion of the structural fatigue capacity that has been consumed, and how much residual capacity remains. Results are assessed for recordings at the four Christchurch central city strong motion recording sites installed by the GeoNet programme, to provide an estimate of variation in results. The computed cyclic demand results are compared to code-based design methods and as assessment of the inelastic displacement demand of the reinforcing steel. Results are also presented in a fragility context where a de minimis (inconsequential), irreparable damage and full fatigue fracture are defined to provide a probabilistic assessment of the fatigue damage incurred. This methodology can provide input into the overall assessment of fatigue demands and residual capacity.
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.
As a global phenomenon, many cities are undergoing urban renewal to accommodate rapid growth in urban population. However, urban renewal can struggle to balance social, economic, and environmental outcomes, whereby economic outcomes are often primarily considered by developers. This has important implications for urban forests, which have previously been shown to be negatively affected by development activities. Urban forests serve the purpose of providing ecosystem services and thus are beneficial to human wellbeing. Better understanding the effect of urban renewal on city trees may help improve urban forest outcomes via effective management and policy strategies, thereby maximising ecosystem service provision and human wellbeing. Though the relationship between certain aspects of development and urban forests has received consideration in previous literature, little research has focused on how the complete property redevelopment cycle affects urban forest dynamics over time. This research provides an opportunity to gain a comprehensive understanding of the effect of residential property redevelopment on urban forest dynamics, at a range of spatial scales, in Christchurch, New Zealand following a series of major earthquakes which occurred in 2010 – 2011. One consequence of the earthquakes is the redevelopment of thousands of properties over a relatively short time-frame. The research quantifies changes in canopy cover city-wide, as well as, tree removal, retention, and planting on individual residential properties. Moreover, the research identifies the underlying reasons for these dynamics, by exploring the roles of socio-economic and demographic factors, the spatial relationships between trees and other infrastructure, and finally, the attitudes of residential property owners. To quantify the effect of property redevelopment on canopy cover change in Christchurch, this research delineated tree canopy cover city-wide in 2011 and again in 2015. An object-based image analysis (OBIA) technique was applied to aerial imagery and LiDAR data acquired at both time steps, in order to estimate city-wide canopy cover for 2011 and 2015. Changes in tree canopy cover between 2011 and 2015 were then spatially quantified. Tree canopy cover change was also calculated for all meshblocks (a relatively fine-scale geographic boundary) in Christchurch. The results show a relatively small magnitude of tree canopy cover loss, city-wide, from 10.8% to 10.3% between 2011 and 2015, but a statistically significant change in mean tree canopy cover across all the meshblocks. Tree canopy cover losses were more likely to occur in meshblocks containing properties that underwent a complete redevelopment cycle, but the loss was insensitive to the density of redevelopment within meshblocks. To explore property-scale individual tree dynamics, a mixed-methods approach was used, combining questionnaire data and remote sensing analysis. A mail-based questionnaire was delivered to residential properties to collect resident and household data; 450 residential properties (321 redeveloped, 129 non- redeveloped) returned valid questionnaires and were identified as analysis subjects. Subsequently, 2,422 tree removals and 4,544 tree retentions were identified within the 450 properties; this was done by manually delineating individual tree crowns, based on aerial imagery and LiDAR data, and visually comparing the presence or absence of these trees between 2011 and 2015. The tree removal rate on redeveloped properties (44.0%) was over three times greater than on non-redeveloped properties (13.5%) and the average canopy cover loss on redeveloped properties (52.2%) was significantly greater than on non-redeveloped properties (18.8%). A classification tree (CT) analysis was used to model individual tree dynamics (i.e. tree removal, tree retention) and candidate explanatory variables (i.e. resident and household, economic, land cover, and spatial variables). The results indicate that the model including land cover, spatial, and economic variables had the best predicting ability for individual tree dynamics (accuracy = 73.4%). Relatively small trees were more likely to be removed, while trees with large crowns were more likely to be retained. Trees were most likely to be removed from redeveloped properties with capital values lower than NZ$1,060,000 if they were within 1.4 m of the boundary of a redeveloped building. Conversely, trees were most likely to be retained if they were on a property that was not redeveloped. The analysis suggested that the resident and household factors included as potential explanatory variables did not influence tree removal or retention. To conduct a further exploration of the relationship between resident attitudes and actions towards trees on redeveloped versus non-redeveloped properties, this research also asked the landowners from the 450 properties that returned mail questionnaires to indicate their attitudes towards tree management (i.e. tree removal, tree retention, and tree planting) on their properties. The results show that residents from redeveloped properties were more likely to remove and/or plant trees, while residents from non- redeveloped properties were more likely to retain existing trees. A principal component analysis (PCA) was used to explore resident attitudes towards tree management. The results of the PCA show that residents identified ecosystem disservices (e.g. leaf litter, root damage to infrastructure) as common reasons for tree removal; however, they also noted ecosystem services as important reasons for both tree planting and tree retention on their properties. Moreover, the reasons for tree removal and tree planting varied based on whether residents’ property had been redeveloped. Most tree removal occurred on redeveloped properties because trees were in conflict with redevelopment, but occurred on non- redeveloped properties because of perceived poor tree health. Residents from redeveloped properties were more likely to plant trees due to being aesthetically pleasing or to replace trees removed during redevelopment. Overall, this research adds to, and complements, the existing literature on the effects of residential property redevelopment on urban forest dynamics. The findings of this research provide empirical support for developing specific legislation or policies about urban forest management during residential property redevelopment. The results also imply that urban foresters should enhance public education on the ecosystem services provided by urban forests and thus minimise the potential for tree removal when undertaking property redevelopment.
