The seismic performance of soil profiles with potentially liquefiable deposits is a complex phenomenon that requires a thorough understanding of the soil properties and ground motion characteristics. The limitations of simplified liquefaction assessment methods have prompted an increase in the use of non-linear dynamic analysis methods. Focusing on onedimensional site response of a soil column, this thesis validated a soil constitutive model using in-situ pore pressure measurements and then assessed the influence of input ground motion characteristics on soil column response using traditional and newly developed metrics. Pore pressure recordings during the Canterbury Earthquake Sequence (CES) in New Zealand were used to validate the PM4Sand constitutive model. Soil profile characterization was key to accurate prediction of excess pore pressure response and accounting for any densification during the CES. Response during multiple earthquakes was captured effectively and cross-layer interaction demonstrated the model capability to capture soil response at the system-level. Synthetic and observed ground motions from the Christchurch earthquake were applied to the validated soil column to quantify the performance of synthetic motions. New metrics were developed to facilitate a robust comparison to assess performance. The synthetic input motions demonstrated a slightly larger acceleration and excess pore pressure response compared to the observed input motions. The results suggest that the synthetic motions may accumulate higher excess pore pressure at a faster rate and with fewer number of cycles in the shear response. This research compares validated soil profile subject to spectrally-matched pulse and non-pulse motions, emphasizing the inclusion of pulse motions with distinctive characteristics in ground motion suites for non-linear dynamic analysis. However, spectral matching may lead to undesired alterations in pulse characteristics. Cumulative absolute velocity and significant duration significantly differed between these two groups compared to the other key characteristics and contributed considerably to the liquefaction response. Unlike the non-pulse motions, not all of the pulse motions triggered liquefaction, likely due to their shorter significant duration. Non-pulse motions developed a greater spatial extent of liquefaction triggering in the soil profile and extended to a greater depth
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
Micro - electro - mechanical system (MEMS) based accelerometers are now frequently used in many different parts of our day - to - day lives. It is also increasingly being used for structural testing applications. Researchers have had res ervation of using these devices as they are relatively untested, but now with the wider adoption, it provides a much cheaper and more versatile tool for structural engineering researchers. A number of damaged buildings in the Christchurch Central Business District (CBD) were instrumented with a number of low - cost MEMS accelerometers after the major Christchurch earthquakes. The accelerometers captured extremely high quality building response data as the buildings experienced thousands of aftershocks. This d ata set was amongst one of only a handful of data set s available around the world which provides building response data subjected to real ground motion. Furthermore, due to technological advances, a much larger than usual number of accelerometers has been deployed making the data set one of the most comprehensive available. This data set is utilised to extract modal parameters of the buildings. This paper summarises the operating requirements and preference for using such accelerometers for experimental mod al analysis. The challenges for adapting MEMS based devices for successful modal parameters identification are also discussed
