Natural catastrophes are increasing worldwide. They are becoming more frequent but also more severe and impactful on our built environment leading to extensive damage and losses. Earthquake events account for the smallest part of natural events; nevertheless seismic damage led to the most fatalities and significant losses over the period 1981-2016 (Munich Re). Damage prediction is helpful for emergency management and the development of earthquake risk mitigation projects. Recent design efforts focused on the application of performance-based design engineering where damage estimation methodologies use fragility and vulnerability functions. However, the approach does not explicitly specify the essential criteria leading to economic losses. There is thus a need for an improved methodology that finds the critical building elements related to significant losses. The here presented methodology uses data science techniques to identify key building features that contribute to the bulk of losses. It uses empirical data collected on site during earthquake reconnaissance mission to train a machine learning model that can further be used for the estimation of building damage post-earthquake. The first model is developed for Christchurch. Empirical building damage data from the 2010-2011 earthquake events is analysed to find the building features that contributed the most to damage. Once processed, the data is used to train a machine-learning model that can be applied to estimate losses in future earthquake events.
This thesis revisits the topic of earthquake recovery in Christchurch City more than a decade after the Canterbury earthquakes. Despite promising visions of a community reconnected and a sustainable and liveable city, significant portions of the city’s core – the Red Zone – remain dilapidated and “eerily empty”. At the same time, new developments in other areas have proven to be alienated or underutilised. Currently, the Canterbury Earthquake Recovery Authority’s plans for the rebuilding highlight the delivery of more residential housing to re-populate the city centre. However, prevalent approaches to housing development in Christchurch are ineffective for building an inclusive and active community. Hence, the central inquiry of the thesis is how the development of housing complexes can revitalise the Red Zone within the Christchurch city centre. The inquiry has been carried out through a research-through-design methodology, recognising the importance of an in-depth investigation that is contextualised and combined with the intuition and embodied knowledge of the designer. The investigation focuses on a neglected site in the Red Zone in the heart of Christchurch city, with significant Victorian and Edwardian Baroque heritage buildings, including Odeon Theatre, Lawrie & Wilson Auctioneers, and Sol Square, owned by The Regional Council Environment Canterbury. The design inquiry argues, develops, and is carried through a place-assemblage lens to housing development for city recovery, which recognizes the significance of socially responsive architecture that explores urban renewal by forging connections within the social network. Therefore, place-assemblage criteria and methods for developing socially active and meaningful housing developments are identified. Firstly, this thesis argues that co-living housing models are more focused on people relations and collective identity than the dominant developer-driven housing rebuilds, as they prioritise conduits for interaction and shared social meaning and practices. Secondly, the adaptive reuse of derelict heritage structures is proposed to reinvigorate the urban fabric, as heritage is seen to be conceived as and from a social assemblage of people. The design is realised by the principles outlined in the ICOMOS charter, which involves incorporating the material histories of existing structures and preserving the intangible heritage of the site by ensuring the continuity of cultural practices. Lastly, design processes and methods are also vital for place-sensitive results, which pay attention to the site’s unique characteristics to engage with local stakeholders and communities. The research explores place-assemblage methods of photographic extraction, the drawing of story maps, precedent studies, assemblage maps, bricolages, and paper models, which show an assembly of layers that piece together the existing heritage, social conduits, urban commons and housing to conceptualise the social network within its place.
Our poster will present on-going QuakeCoRE-founded work on strong motion seismology for Dunedin-Mosgiel area, focusing on ground motion simulations for Dunedin Central Business District (CBD). Source modelling and ground motion simulations are being carried out using the SCEC (Southern California Earthquakes Center) Broad Band simulation Platform (BBP). The platform computes broadband (0-10 Hz) seismograms for earthquakes and was first implemented at the University of Otago in 2016. As large earthquakes has not been experienced in Dunedin in the time of period of instrumental recording, user-specified scenario simulations are of great value. The Akatore Fault, the most active fault in Otago and closest major fault to Dunedin, is the source focused on in the present study. Simulations for various Akatore Fault source scenarios are run and presented. Path and site effects are key components considered in the simulation process. A 1D shear wave velocity profile is required by SCEC BBP, and this is being generated to represent the Akatore-to-CBD path and site within the BBP. A 3D shear velocity model, with high resolution within Dunedin CBD, is being developed in parallel with this study (see Sangster et al. poster). This model will be the basis for developing a 3D shear wave velocity model for greater Dunedin-Mosgiel area for future ground motion simulations, using Canterbury software (currently under development).
