The Mw 6.2 February 22nd 2011 Christchurch earthquake (and others in the 2010-2011 Canterbury sequence) provided a unique opportunity to study the devastating effects of earthquakes first-hand and learn from them for future engineering applications. All major events in the Canterbury earthquake sequence caused widespread liquefaction throughout Christchurch’s eastern suburbs, particularly extensive and severe during the February 22nd event. Along large stretches of the Avon River banks (and to a lesser extent along the Heathcote) significant lateral spreading occurred, affecting bridges and the infrastructure they support. The first stage of this research involved conducting detailed field reconnaissance to document liquefaction and lateral spreading-induced damage to several case study bridges along the Avon River. The case study bridges cover a range of ages and construction types but all are reinforced concrete structures which have relatively short, stiff decks. These factors combined led to a characteristic deformation mechanism involving deck-pinning and abutment back-rotation with consequent damage to the abutment piles and slumping of the approaches. The second stage of the research involved using pseudo-static analysis, a simplified seismic modelling tool, to analyse two of the bridges. An advantage of pseudo-static analysis over more complicated modelling methods is that it uses conventional geotechnical data in its inputs, such as SPT blowcount and CPT cone resistance and local friction. Pseudo-static analysis can also be applied without excessive computational power or specialised knowledge, yet it has been shown to capture the basic mechanisms of pile behaviour. Single pile and whole bridge models were constructed for each bridge, and both cyclic and lateral spreading phases of loading were investigated. Parametric studies were carried out which varied the values of key parameters to identify their influence on pile response, and computed displacements and damages were compared with observations made in the field. It was shown that pseudo-static analysis was able to capture the characteristic damage mechanisms observed in the field, however the treatment of key parameters affecting pile response is of primary importance. Recommendations were made concerning the treatment of these governing parameters controlling pile response. In this way the future application of pseudo-static analysis as a tool for analysing and designing bridge pile foundations in liquefying and laterally spreading soils is enhanced.
This paper presents the probabilistic seismic performance and loss assessment of an actual bridge– foundation–soil system, the Fitzgerald Avenue twin bridges in Christchurch, New Zealand. A two-dimensional finite element model of the longitudinal direction of the system is modelled using advanced soil and structural constitutive models. Ground motions at multiple levels of intensity are selected based on the seismic hazard deaggregation at the site. Based on rigorous examination of several deterministic analyses, engineering demand parameters (EDP’s), which capture the global and local demand, and consequent damage to the bridge and foundation are determined. A probabilistic seismic loss assessment of the structure considering both direct repair and loss of functionality consequences was performed to holistically assess the seismi risk of the system. It was found that the non-horizontal stratification of the soils, liquefaction, and soil–structure interaction had pronounced effects on the seismic demand distribution of the bridge components, of which the north abutment piles and central pier were critical in the systems seismic performance. The consequences due to loss of functionality of the bridge during repair were significantly larger than the direct repair costs, with over a 2% in 50 year probability of the total loss exceeding twice the book-value of the structure.
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.
