The 2010 Darfield earthquake is the largest earthquake on record to have occurred within 40 km of a major city and not cause any fatalities. In this paper the authors have reflected on their experiences in Christchurch following the earthquake with a view to what worked, what didn’t, and what lessons can be learned from this for the benefit of Australian earthquake preparedness. Owing to the fact that most of the observed building damage occurred in Unreinforced Masonry (URM) construction, this paper focuses in particular on the authors’ experience conducting rapid building damage assessment during the first 72 hours following the earthquake and more detailed examination of the performance of unreinforced masonry buildings with and without seismic retrofit interventions.
The progressive damage and subsequent demolition of unreinforced masonry (URM) buildings arising from the Canterbury earthquake sequence is reported. A dataset was compiled of all URM buildings located within the Christchurch CBD, including information on location, building characteristics, and damage levels after each major earthquake in this sequence. A general description of the overall damage and the hazard to both building occupants and to nearby pedestrians due to debris falling from URM buildings is presented with several case study buildings used to describe the accumulation of damage over the earthquake sequence. The benefit of seismic improvement techniques that had been installed to URM buildings is shown by the reduced damage ratios reported for increased levels of retrofit. Demolition statistics for URM buildings in the Christchurch CBD are also reported and discussed. VoR - Version of Record
Quick and reliable assessment of the condition of bridges in a transportation network after an earthquake can greatly assist immediate post-disaster response and long-term recovery. However, experience shows that available resources, such as qualified inspectors and engineers, will typically be stretched for such tasks. Structural health monitoring (SHM) systems can therefore make a real difference in this context. SHM, however, needs to be deployed in a strategic manner and integrated into the overall disaster response plans and actions to maximize its benefits. This study presents, in its first part, a framework of how this can be achieved. Since it will not be feasible, or indeed necessary, to use SHM on every bridge, it is necessary to prioritize bridges within individual networks for SHM deployment. A methodology for such prioritization based on structural and geotechnical seismic risks affecting bridges and their importance within a network is proposed in the second part. An example using the methodology application to selected bridges in the medium-sized transportation network of Wellington, New Zealand is provided. The third part of the paper is concerned with using monitoring data for quick assessment of bridge condition and damage after an earthquake. Depending on the bridge risk profile, it is envisaged that data will be obtained from either local or national seismic monitoring arrays or SHM systems installed on bridges. A method using artificial neural networks is proposed for using data from a seismic array to infer key ground motion parameters at an arbitrary bridges site. The methodology is applied to seismic data collected in Christchurch, New Zealand. Finally, how such ground motion parameters can be used in bridge damage and condition assessment is outlined. AM - Accepted manuscript
