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Research papers, The University of Auckland Library

The research presented in this thesis investigated the environmental impacts of structural design decisions across the life of buildings located in seismic regions. In particular, the impacts of expected earthquake damage were incorporated into a traditional life cycle assessment (LCA) using a probabilistic method, and links between sustainable and resilient design were established for a range of case-study buildings designed for different seismic performance objectives. These links were quantified using a metric herein referred to as the seismic carbon risk, which represents the expected environmental impacts and resource use indicators associated with earthquake damage during buildings’ life. The research was broken into three distinct parts: (1) a city-level evaluation of the environmental impacts of demolitions following the 2010/2011 Canterbury earthquake sequence in New Zealand, (2) the development of a probabilistic framework to incorporate earthquake damage into LCA, and (3) using case-study buildings to establish links between sustainable and resilient design. The first phase of the research focused on the environmental impacts of demolitions in Christchurch, New Zealand following the 2010/2011 Canterbury Earthquake Sequence. This large case study was used to investigate the environmental impact of the demolition of concrete buildings considering the embodied carbon and waste stream distribution. The embodied carbon was considered here as kilograms of CO2 equivalent that occurs on production, construction, and waste management stage. The results clearly demonstrated the significant environmental impacts that can result from moderate and large earthquakes in urban areas, and the importance of including environmental considerations when making post-earthquake demolition decisions. The next phase of the work introduced a framework for incorporating the impacts of expected earthquake damage based on a probabilistic approach into traditional LCA to allow for a comparison of seismic design decisions using a carbon lens. Here, in addition to initial construction impacts, the seismic carbon risk was quantified, including the impacts of seismic repair activities and total loss scenarios assuming reconstruction in case of non-reparability. A process-based LCA was performed to obtain the environmental consequence functions associated with structural and non-structural repair activities for multiple environmental indicators. In the final phase of the work, multiple case-study buildings were used to investigate the seismic consequences of different structural design decisions for buildings in seismic regions. Here, two case-study buildings were designed to multiple performance objectives, and the upfront carbon costs, and well as the seismic carbon risk across the building life were compared. The buildings were evaluated using the framework established in phase 2, and the results demonstrated that the seismic carbon risk can significantly be reduced with only minimal changes to the upfront carbon for buildings designed for a higher base shear or with seismic protective systems. This provided valuable insight into the links between resilient and sustainable design decisions. Finally, the results and observations from the work across the three phases of research described above were used to inform a discussion on important assumptions and topics that need to be considered when quantifying the environmental impacts of earthquake damage on buildings. These include: selection of a non-repairable threshold (e.g. a value beyond which a building would be demolished rather than repaired), the time value of carbon (e.g. when in the building life the carbon is released), the changing carbon intensity of structural materials over time, and the consideration of deterministic vs. probabilistic results. Each of these topics was explored in some detail to provide a clear pathway for future work in this area.

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.