The paper proposes a simple method for quick post-earthquake assessment of damage and condition of a stock of bridges in a transportation network using seismic data recorded by a strong motion array. The first part of the paper is concerned with using existing free field strong motion recorders to predict peak ground acceleration (PGA) at an arbitrary bridge site. Two methods are developed using artificial neural networks (a single network and a committee of neural networks) considering influential parameters, such as seismic magnitude, hypocentral depth and epicentral distance. The efficiency of the proposed method is explored using actual strong motion records from the devastating 2010 Darfield and 2011 Christchurch earthquakes in New Zealand. In the second part, two simple ideas are outlined how to infer the likely damage to a bridge using either the predicted PGA and seismic design spectrum, or a broader set of seismic metrics, structural parameters and damage indices.
The Canterbury earthquake series of 2010/2011 has turned the city of Christchurch into a full scale natural laboratory testing the structural and non-structural response of buildings under moderate to very severe earthquake shaking. The lessons learned from this, which have come at great cost socially and economically, are extremely valuable in increasing our understanding of whole building performance in severe earthquakes. Given current initiatives underway on both sides of the Tasman towards developing joint Australasian steel and composite steel/concrete design and construction standards that would span a very wide range of geological conditions and seismic zones, these lessons are relevant to both countries. This paper focusses on the performance of steel framed buildings in Christchurch city, with greatest emphasis on multi-storey buildings, but also covering single storey steel framed buildings and light steel framed housing. It addresses such issues as the magnitude and structural impact of the earthquake series, importance of good detailing, lack of observed column base hinging, the excellent performance of composite floors and it will briefly cover research underway to quantify some of these effects for use in design.
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 2010 Darfield and 2011 Christchurch Earthquakes triggered extensive liquefaction-induced lateral spreading proximate to streams and rivers in the Christchurch area, causing significant damage to structures and lifelines. A case study in central Christchurch is presented and compares field observations with predicted displacements from the widely adopted empirical model of Youd et al. (2002). Cone penetration testing (CPT), with measured soil gradation indices (fines content and median grain size) on typical fluvial deposits along the Avon River were used to determine the required geotechnical parameters for the model input. The method presented attempts to enable the adoption of the extensive post-quake CPT test records in place of the lower quality and less available Standard Penetration Test (SPT) data required by the original Youd model. The results indicate some agreement between the Youd model predictions and the field observations, while the majority of computed displacements error on the side of over-prediction by more than a factor of two. A sensitivity analysis was performed with respect to the uncertainties used as model input, illustrating the model’s high sensitivity to the input parameters, with median grain size and fines content among the most influential, and suggesting that the use of CPT data to quantify these parameters may lead to variable results.
Liquefaction-induced lateral spreading in Christchurch and surrounding suburbs during the recent Canterbury Earthquake Sequence (2010-2011) caused significant damage to structures and lifelines located in close proximity to streams and rivers. Simplified methods used in current engineering practice for predicting lateral ground displacements exhibit a high degree of epistemic uncertainty, but provide ‘order of magnitude’ estimates to appraise the hazard. We wish to compare model predictions to field measurements in order to assess the model’s capabilities and limitations with respect to Christchurch conditions. The analysis presented focuses on the widely-used empirical model of Youd et al. (2002), developed based on multi-linear regression (MLR) of case history data from lateral spreading occurrence in Japan and the US. Two issues arising from the application of this model to Christchurch were considered: • Small data set of Standard Penetration Test (SPT) and soil gradation indices (fines content FC, and mean grain size, D50) required for input. We attempt to use widely available CPT data with site specific correlations to FC and D50. • Uncertainty associated with the model input parameters and their influence on predicted displacements. This has been investigated for a specific location through a sensitivity analysis.
On February 22, 2011, a magnitude Mw 6.2 earthquake affected the Canterbury region, New Zealand, resulting in many fatalities. Liquefaction occurred across many areas, visible on the surface as ‘‘sand volcanoes’’, blisters and subsidence, causing significant damage to buildings, land and infrastructure. Liquefaction occurred at a number of sites across the Christchurch Boys High School sports grounds; one area in particular contained a piston ground failure and an adjacent silt volcano. Here, as part of a class project, we apply near-surface geophysics to image these two liquefaction features and determine whether they share a subsurface connection. Hand auger results enable correlation of the geophysical responses with the subsurface stratigraphy. The survey results suggest that there is a subsurface link, likely via a paleo-stream channel. The anomalous responses of the horizontal loop electromagnetic survey and electrical resistivity imaging highlight the disruption of the subsurface electrical properties beneath and between the two liquefaction features. The vertical magnetic gradient may also show a subtle anomalous response in this area, however the results are inconclusive. The ground penetrating radar survey shows disruption of the subsurface stratigraphy beneath the liquefaction features, in particular sediment mounding beneath the silt ejection (‘‘silt volcano’’) and stratigraphic disruption beneath the piston failure. The results indicate how near-surface geophysics allow the characteristics of liquefaction in the subsurface to be better understood, which could aid remediation work following liquefaction-induced land damage and guide interpretation of geophysical surveys of paleoliquefaction features.
