The 2010–2011 Canterbury earthquakes, which involved widespread damage during the February 2011 event and ongoing aftershocks near the Christchurch Central Business District, left this community with more than $NZD 40 billion in losses (~20 % GDP), demolition of approximately 60 % of multi-storey concrete buildings (3 storeys and up), and closure of the core business district for over 2 years. The aftermath of the earthquake sequence has revealed unique issues and complexities for the owners of commercial and multi-storey residential buildings in relation to unexpected technical, legal, and financial challenges when making decisions regarding the future of their buildings impacted by the earthquakes. The paper presents a framework to understand the factors influencing post-earthquake decisions (repair or demolish) on multi-storey concrete buildings in Christchurch. The study, conducted in 2014, includes in-depth investigations on 15 case-study buildings using 27 semi-structured interviews with various property owners, property managers, insurers, engineers, and government authorities in New Zealand. The interviews revealed insights regarding the multitude of factors influencing post-earthquake decisions and losses. As expected, the level of damage and repairability (cost to repair) generally dictated the course of action. There is strong evidence, however, that other variables have significantly influenced the decision on a number of buildings, such as insurance, business strategies, perception of risks, building regulations (and compliance costs), and government decisions. The decision-making process for each building is complex and unique, not solely driven by structural damage. Furthermore, the findings have put the spotlight on insurance policy wordings and the paradoxical effect of insurance on the recovery of Christchurch, leading to other challenges and issues going forward.
A number of field testing techniques, such as standard penetration test (SPT), cone penetration test (CPT), and Swedish weight sounding (SWS), are popularly used for in-situ characterisation. The screw driving sounding (SDS) method, which has been recently developed in Japan, is an improved version of the SWS technique and measures more parameters, including the required torque, load, speed of penetration and rod friction; these provide more robust way of characterising soil stratigraphy. It is a cost-efficient technique which uses a machine-driven and portable device, making it ideal for testing in small-scale and confined areas. Moreover, with a testing depth of up to 10-15m, it is suitable for liquefaction assessment. Thus, the SDS method has great potential as an in-situ testing method for geotechnical site characterisation, especially for residential house construction. In this paper, the results of SDS tests performed at a variety of sites in New Zealand are presented. The soil database was employed to develop a soil classification chart based on SDS-derived parameters. Moreover, using the data obtained following the 2010-2011 Christchurch Earthquake Se-quence, a methodology was established for liquefaction potential evaluation using SDS data. http://www.isc5.com.au/wp-content/uploads/2016/09/1345-2-ORENSE.pdf
This thesis presents the application of data science techniques, especially machine learning, for the development of seismic damage and loss prediction models for residential buildings. Current post-earthquake building damage evaluation forms are developed for a particular country in mind. The lack of consistency hinders the comparison of building damage between different regions. A new paper form has been developed to address the need for a global universal methodology for post-earthquake building damage assessment. The form was successfully trialled in the street ‘La Morena’ in Mexico City following the 2017 Puebla earthquake. Aside from developing a framework for better input data for performance based earthquake engineering, this project also extended current techniques to derive insights from post-earthquake observations. Machine learning (ML) was applied to seismic damage data of residential buildings in Mexico City following the 2017 Puebla earthquake and in Christchurch following the 2010-2011 Canterbury earthquake sequence (CES). The experience showcased that it is readily possible to develop empirical data only driven models that can successfully identify key damage drivers and hidden underlying correlations without prior engineering knowledge. With adequate maintenance, such models have the potential to be rapidly and easily updated to allow improved damage and loss prediction accuracy and greater ability for models to be generalised. For ML models developed for the key events of the CES, the model trained using data from the 22 February 2011 event generalised the best for loss prediction. This is thought to be because of the large number of instances available for this event and the relatively limited class imbalance between the categories of the target attribute. For the CES, ML highlighted the importance of peak ground acceleration (PGA), building age, building size, liquefaction occurrence, and soil conditions as main factors which affected the losses in residential buildings in Christchurch. ML also highlighted the influence of liquefaction on the buildings losses related to the 22 February 2011 event. Further to the ML model development, the application of post-hoc methodologies was shown to be an effective way to derive insights for ML algorithms that are not intrinsically interpretable. Overall, these provide a basis for the development of ‘greybox’ ML models.
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.
