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Audio, Radio New Zealand

Professor Andrew Barrie discusses an exhibition that comes up with ways to keep Christchurch communities together after the loss of so many earthquake damaged parish churches.

Research papers, The University of Auckland Library

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.

Audio, Radio New Zealand

One of New Zealand's most celebrated authors, Kate De Goldi's short fiction, novels and picture books engage children, teenagers and adults alike. Novel The 10pm Question was published to critical acclaim, quickly becoming an iconic piece of New Zealand literature. Her latest, Eddy, Eddy is being met with similar excitement.

Research papers, University of Canterbury Library

The University of Canterbury has initialized a research program focusing on the seismic sustainability of structures. As part of this program, the relative seismic sustainability of various structures will be assessed to identify those with the highest sustainability for the Christchurch rebuild and general use in New Zealand. This preliminary case study assesses one reinforced concrete (RC) frame structure and one RC wall structure. The scenario loss is evaluated for two earthquake records considering direct losses only in order to explain and illustrate the methodology.