The city of Christchurch, New Zealand, incurred significant damage due to a series of earthquakes in 2010 and 2011. The city had, by the late 2010s, regained economic and social normalcy after a sustained period of rebuilding and economic recovery. Through the concerted rebuilding effort, a modern central business district (CBD) with redesigned infrastructure and amenities was developed. The Christchurch rebuild was underpinned by a commitment of urban planners to an open and connected city, including the use of innovative technologies to gather, use and share data. As was the case elsewhere, the COVID-19 pandemic brought about significant disruptions to social and economic life in Christchurch. Border closures, lockdowns, trading limitations and other restrictions on movement led to changes in traditional consumer behaviors and affected the retail sector’s resilience. In this study, we used CBD pedestrian traffic data gathered from various locations to predict changes in retail spending and identify recovery implications through the lens of retail resilience. We found that the COVID-19 pandemic and its related lockdowns have driven a substantive change in the behavioral patterns of city users. The implications for resilient retail, sustainable policy and further research are explored.
The research is funded by Callaghan Innovation (grant number MAIN1901/PROP-69059-FELLOW-MAIN) and the Ministry of Transport New Zealand in partnership with Mainfreight Limited. Need – The freight industry is facing challenges related to climate change, including natural hazards and carbon emissions. These challenges impact the efficiency of freight networks, increase costs, and negatively affect delivery times. To address these challenges, freight logistics modelling should consider multiple variables, such as natural hazards, sustainability, and emission reduction strategies. Freight operations are complex, involving various factors that contribute to randomness, such as the volume of freight being transported, the location of customers, and truck routes. Conventional methods have limitations in simulating a large number of variables. Hence, there is a need to develop a method that can incorporate multiple variables and support freight sustainable development. Method - A minimal viable model (MVM) method was proposed to elicit tacit information from industrial clients for building a minimally sufficient simulation model at the early modelling stages. The discrete-event simulation (DES) method was applied using Arena® software to create simulation models for the Auckland and Christchurch corridor, including regional pick-up and delivery (PUD) models, Christchurch city delivery models, and linehaul models. Stochastic variables in freight operations such as consignment attributes, customer locations, and truck routes were incorporated in the simulation. The geographic information system (GIS) software ArcGIS Pro® was used to identify and analyse industrial data. The results obtained from the GIS software were applied to create DES models. Life cycle assessment (LCA) models were developed for both diesel and battery electric (BE) trucks to compare their life cycle greenhouse gas (GHG) emissions and total cost of ownership (TCO) and support GHG emissions reduction. The line-haul model also included natural hazards in several scenarios, and the simulation was used to forecast the stock level of Auckland and Christchurch depots in response to each corresponding scenario. Results – DES is a powerful technique that can be employed to simulate and evaluate freight operations that exhibit high levels of variability, such as regional pickup and delivery (PUD) and linehaul. Through DES, it becomes possible to analyse multiple factors within freight operations, including transportation modes, routes, scheduling, and processing times, thereby offering valuable insights into the performance, efficiency, and reliability of the system. In addition, GIS is a useful tool for analysing and visualizing spatial data in freight operations. This is exemplified by their ability to simulate the travelling salesman problem (TSP) and conduct cluster analysis. Consequently, the integration of GIS into DES modelling is essential for improving the accuracy and reliability of freight operations analysis. The outcomes of the simulation were utilised to evaluate the ecological impact of freight transport by performing emission calculations and generating low-carbon scenarios to identify approaches for reducing the carbon footprint. LCA models were developed based on simulation results. Results showed that battery-electric trucks (BE) produced more greenhouse gas (GHG) emissions in the cradle phase due to battery manufacturing but substantially less GHG emissions in the use phase because of New Zealand's mostly renewable energy sources. While the transition to BE could significantly reduce emissions, the financial aspect is not compelling, as the total cost of ownership (TCO) for the BE truck was about the same for ten years, despite a higher capital investment for the BE. Moreover, external incentives are necessary to justify a shift to BE trucks. By using simulation methods, the effectiveness of response plans for natural hazards can be evaluated, and the system's vulnerabilities can be identified and mitigated to minimize the risk of disruption. Simulation models can also be utilized to simulate adaptation plans to enhance the system's resilience to natural disasters. Novel contributions – The study employed a combination of DES and GIS methods to incorporate a large number of stochastic variables and driver’s decisions into freight logistics modelling. Various realistic operational scenarios were simulated, including customer clustering and PUD truck allocation. This showed that complex pickup and delivery routes with high daily variability can be represented using a model of roads and intersections. Geographic regions of high customer density, along with high daily variability could be represented by a two-tier architecture. The method could also identify delivery runs for a whole city, which has potential usefulness in market expansion to new territories. In addition, a model was developed to address carbon emissions and total cost of ownership of battery electric trucks. This showed that the transition was not straightforward because the economics were not compelling, and that policy interventions – a variety were suggested - could be necessary to encourage the transition to decarbonised freight transport. A model was developed to represent the effect of natural disasters – such as earthquake and climate change – on road travel and detour times in the line haul freight context for New Zealand. From this it was possible to predict the effects on stock levels for a variety of disruption scenarios (ferry interruption, road detours). Results indicated that some centres rather than others may face higher pressure and longer-term disturbance after the disaster subsided. Remedies including coastal shipping were modelled and shown to have the potential to limit the adverse effects. A philosophical contribution was the development of a methodology to adapt the agile method into the modelling process. This has the potential to improve the clarification of client objectives and the validity of the resulting model.
High demolition rates were observed in New Zealand after the 2010-2011 Canterbury Earthquake Sequence despite the success of modern seismic design standards to achieve required performance objectives such as life safety and collapse prevention. Approximately 60% of the multi-storey reinforced concrete (RC) buildings in the Christchurch Central Business District were demolished after these earthquakes, even when only minor structural damage was present. Several factors influenced the decision of demolition instead of repair, one of them being the uncertainty of the seismic capacity of a damaged structure. To provide more insight into this topic, the investigation conducted in this thesis evaluated the residual capacity of moderately damaged RC walls and the effectiveness of repair techniques to restore the seismic performance of heavily damaged RC walls. The research outcome provided insights for developing guidelines for post-earthquake assessment of earthquake-damaged RC structures. The methodology used to conduct the investigation was through an experimental program divided into two phases. During the first phase, two walls were subjected to different types of pre-cyclic loading to represent the damaged condition from a prior earthquake, and a third wall represented a repair scenario with the damaged wall being repaired using epoxy injection and repair mortar after the pre-cyclic loading. Comparisons of these test walls to a control undamaged wall identified significant reductions in the stiffness of the damaged walls and a partial recovery in the wall stiffness achieved following epoxy injection. Visual damage that included distributed horizontal and diagonal cracks and spalling of the cover concrete did not affect the residual strength or displacement capacity of the walls. However, evidence of buckling of the longitudinal reinforcement during the pre-cyclic loading resulted in a slight reduction in strength recovery and a significant reduction in the displacement capacity of the damaged walls. Additional experimental programs from the literature were used to provide recommendations for modelling the response of moderately damaged RC walls and to identify a threshold that represented a potential reduction in the residual strength and displacement capacity of damaged RC walls in future earthquakes. The second phase of the experimental program conducted in this thesis addressed the replacement of concrete and reinforcing steel as repair techniques for heavily damaged RC walls. Two walls were repaired by replacing the damaged concrete and using welded connections to connect new reinforcing bars with existing bars. Different locations of the welded connections were investigated in the repaired walls to study the impact of these discontinuities at the critical section. No significant changes were observed in the stiffness, strength, and displacement capacity of the repaired walls compared to the benchmark undamaged wall. Differences in the local behaviour at the critical section were observed in one of the walls but did not impact the global response. The results of these two repaired walls were combined with other experimental programs found in the literature to assemble a database of repaired RC walls. Qualitative and quantitative analyses identified trends across various parameters, including wall types, damage before repair, and repair techniques implemented. The primary outcome of the database analysis was recommendations for concrete and reinforcing steel replacement to restore the strength and displacement capacity of heavily damaged RC walls.
