The performance of retrofitted unreinforced masonry (URM) bearing wall buildings in Christchurch is examined, considering ground motion recordings from multiple events. Suggestions for how the experiences in Christchurch might be relevant to retrofit practices common to New Zealand, U.S. and Canada are also provided. Whilst the poor performance of unretrofitted URM buildings in earthquakes is well known, much less is known about how retrofitted URM buildings perform when subjected to strong ground shaking.
Having a quick but reliable insight into the likelihood of damage to bridges immediately after an earthquake is an important concern especially in the earthquake prone countries such as New Zealand for ensuring emergency transportation network operations. A set of primary indicators necessary to perform damage likelihood assessment are ground motion parameters such as peak ground acceleration (PGA) at each bridge site. Organizations, such as GNS in New Zealand, record these parameters using distributed arrays of sensors. The challenge is that those sensors are not installed at, or close to, bridge sites and so bridge site specific data are not readily available. This study proposes a method to predict ground motion parameters for each bridge site based on remote seismic array recordings. Because of the existing abundant source of data related to two recent strong earthquakes that occurred in 2010 and 2011 and their aftershocks, the city of Christchurch is considered to develop and examine the method. Artificial neural networks have been considered for this research. Accelerations recorded by the GeoNet seismic array were considered to develop a functional relationship enabling the prediction of PGAs. http://www.nzsee.org.nz/db/2013/Posters.htm
The objective of the study presented herein is to assess three commonly used CPT-based liquefaction evaluation procedures and three liquefaction severity index frameworks using data from the 2010–2011 Canterbury earthquake sequence. Specifically, post-event field observations, ground motion recordings, and results from a recently completed extensive geotechnical site investigation programme at selected strong motion stations (SMSs) in the city of Christchurch and surrounding towns are used herein. Unlike similar studies that used data from free-field sites, accelerogram characteristics at the SMS locations can be used to assess the performance of liquefaction evaluation procedures prior to their use in the computation of surficial manifestation severity indices. Results from this study indicate that for cases with evidence of liquefaction triggering in the accelerograms, the majority of liquefaction evaluation procedures yielded correct predictions, regardless of whether surficial manifestation of liquefaction was evident or not. For cases with no evidence of liquefaction in the accelerograms (and no observed surficial evidence of liquefaction triggering), the majority of liquefaction evaluation procedures predicted liquefaction was triggered. When all cases are used to assess the performance of liquefaction severity index frameworks, a poor correlation is shown between the observed severity of liquefaction surface manifestation and the calculated severity indices. However, only using those cases where the liquefaction evaluation procedures yielded correct predictions, there is an improvement in the correlation, with the Liquefaction Severity Number (LSN) being the best performing of the frameworks investigated herein. However scatter in the relationship between the observed and calculated surficial manifestation still remains for all liquefaction severity index frameworks.
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.
