The Catholic Cathedral of the Blessed Sacrament is a category 1 listed heritage building constructed largely of unreinforced stone masonry, and was significantly damaged in the recent Canterbury earthquakes. The building experienced ground shaking in excess of its capacity leading to block failures and partial collapse of parts of the building, which left the building standing but still posing a significant hazard. In this paper we discuss the approach to securing the building, and the interaction of the structural, heritage and safety demands involved in a dynamic seismic risk environment. We briefly cover the types of failures observed and the behaviour of the structure, and investigate the performance of both strengthened and un-strengthened parts of the building. Seismic strengthening options are investigated at a conceptual level. We draw conclusions as to how the building performed in the earthquakes, comment on the effectiveness of the strengthening and securing work and discuss the potential seismic strengthening methods.
The context of this study is the increasing need for public transport as issues over high private vehicle usage are becoming increasingly obvious. Public transport services need to compete with private transport to improve patronage, and issues with reliability need to be addressed. Bus bunching affects reliability through disruptions to the scheduled headways. The purpose of this study was to collect and analyse data to compare how travel time and dwell time vary, to explore the variation of key variables, and to better understand the sources of these variations. The Orbiter bus service in Christchurch was used as a case study, as it is particularly vulnerable to bus bunching. The dwell time was found to be more variable than travel time. It appeared the Canterbury earthquake had significantly reduced the average speeds for the Orbiter service. In 1964, Newell and Potts described a basic bus bunching theory, which was used as the basis for an Excel bus bunching model. This model allows input variables to vary stochastically. Random values were generated from four specified distributions derived from manually collected data, allowing variance across all bus platforms and buses. However the complexity resulted in stability and difficulty in achieving convergence, so the model was run in single Monte Carlo simulations. The outputs were realistic and showed a higher degree of bunching behaviour than previous models. The model demonstrated bunching phenomena that had not been observed in previous models, including spontaneously un-pairing, overtaking of buses delayed at platforms, and odd-numbered bunches of three buses. Furthermore, the study identified areas of further research for data collection and model development.
