Between September 4, 2010 and December 23, 2011, a series of earthquakes struck the South Island of New Zealand including the city of Christchurch producing heavy damage. During the strongest shaking, the unreinforced masonry (URM) building stock in Christchurch was subjected to seismic loading equal to approximately 150-200% of code values. Post-earthquake reconnaissance suggested numerous failures of adhesive anchors used for retrofit connection of roof and floor diaphragms to masonry walls. A team of researchers from the Universities of Auckland (NZ) and Minnesota (USA) conducted a field investigation on the performance of new adhesive anchors installed in existing masonry walls. Variables included adhesive type, anchor diameter, embedment length, anchor inclination, and masonry quality. Buildings were selected that had been slated for demolition but which featured exterior walls that had not been damaged. A summary of the deformation response measured during the field tests are presented. AM - Accepted Manuscript
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
