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Images for supports; more images...

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

Images, UC QuakeStudies

The badly damaged Carlton Hotel on Papanui Road. One wall of the upper storey has collapsed, exposing the rooms within, and bricks litter the footpath below. Bracing have been placed against the building as support.

Images, UC QuakeStudies

A photograph of the intersection of High Street, Lichfield Street and Manchester Street. Stacks of coloured shipping containers can be seen supporting the facades of buildings on both Lichfield Street and Manchester Street.

Images, UC QuakeStudies

A photograph of the Moko cafe building on the corner of Gloucester Street and New Regent Street. Scaffolding is being used to support part of the awning and a yellow sticker can be seen on the door.