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Research papers, The University of Auckland Library

Seismic retrofitting of unreinforced masonry buildings using posttensioning has been the topic of many recent experimental research projects. However, the performance of such retrofit designs in actual design level earthquakes has previously been poorly documented. In 1984 two stone masonry buildings within The Arts Centre of Christchurch received posttensioned seismic retrofits, which were subsequently subjected to design level seismic loads during the 2010/2011 Canterbury earthquake sequence. These 26 year old retrofits were part of a global scheme to strengthen and secure the historic building complex and were subject to considerable budgetary constraints. Given the limited resources available at the time of construction and the current degraded state of the steel posttension tendons, the posttensioned retrofits performed well in preventing major damage to the overall structure of the two buildings in the Canterbury earthquakes. When compared to other similar unretrofitted structures within The Arts Centre, it is demonstrated that the posttensioning significantly improved the in-plane and out-of-plane wall strength and the ability to limit residual wall displacements. The history of The Arts Centre buildings and the details of the Canterbury earthquakes is discussed, followed by examination of the performance of the posttension retrofits and the suitability of this technique for future retrofitting of other historic unreinforced masonry buildings. http://www.aees.org.au/downloads/conference-papers/

Research papers, The University of Auckland Library

Utility managers are always looking for appropriate tools to estimate seismic damage in wastewater networks located in earthquake prone areas. Fragility curves, as an appropriate tool, are recommended for seismic vulnerability analysis of buried pipelines, including pressurised and unpressurised networks. Fragility curves are developed in pressurised networks mainly for water networks. Fragility curves are also recommended for seismic analysis in unpressurised networks. Applying fragility curves in unpressurised networks affects accuracy of seismic damage estimation. This study shows limitations of these curves in unpressurised networks. Multiple case study analysis was applied to demonstrate the limitations of the application of fragility curves in unpressurised networks in New Zealand. Four wastewater networks within New Zealand were selected as case studies and various fragility curves used for seismic damage estimation. Observed damage in unpressurised networks after the 2007 earthquake in Gisborne and the 2010 earthquake in Christchurch demonstrate the appropriateness of the applied fragility curves to New Zealand wastewater networks. This study shows that the application of fragility curves, which are developed from pressurised networks, cannot be accurately used for seismic damage assessment in unpressurised wastewater networks. This study demonstrated the effects of different parameters on seismic damage vulnerability of unpressurised networks.

Research papers, The University of Auckland Library

As part of a seismic retrofit scheme, surface bonded glass fiber-reinforced polymer (GFRP) fabric was applied to two unreinforced masonry (URM) buildings located in Christchurch, New Zealand. The unreinforced stone masonry of Christchurch Girls’ High School (GHS) and the unreinforced clay brick masonry Shirley Community Centre were retrofitted using surface bonded GFRP in 2007 and 2009, respectively. Much of the knowledge on the seismic performance of GFRP retrofitted URM was previously assimilated from laboratory-based experimental studies with controlled environments and loading schemes. The 2010/2011 Canterbury earthquake sequence provided a rare opportunity to evaluate the GFRP retrofit applied to two vintage URM buildings and to document its performance when subjected to actual design-level earthquake-induced shaking. Both GFRP retrofits were found to be successful in preserving architectural features within the buildings as well as maintaining the structural integrity of the URM walls. Successful seismic performance was based on comparisons made between the GFRP retrofitted GHS building and the adjacent nonretrofitted Boys’ High School building, as well as on a comparison between the GFRP retrofitted and nonretrofitted walls of the Shirley Community Centre building. Based on detailed postearthquake observations and investigations, the GFRP retrofitted URM walls in the subject buildings exhibited negligible to minor levels of damage without delamination, whereas significant damage was observed in comparable nonretrofitted URM walls. AM - Accepted Manuscript

Research papers, The University of Auckland Library

The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings.