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.
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
During the 2010/2011 Canterbury earthquakes, several reinforced concrete (RC) walls in multi-storey buildings formed a single crack in the plastic hinge region as opposed to distributed cracking. In several cases the crack width that was required to accommodate the inelastic displacement of the building resulted in fracture of the vertical reinforcing steel. This type of failure is characteristic of RC members with low reinforcement contents, where the area of reinforcing steel is insufficient to develop the tension force required to form secondary cracks in the surrounding concrete. The minimum vertical reinforcement in RC walls was increased in NZS 3101:2006 with the equation for the minimum vertical reinforcement in beams also adopted for walls, despite differences in reinforcement arrangement and loading. A series of moment-curvature analyses were conducted for an example RC wall based on the Gallery Apartments building in Christchurch. The analysis results indicated that even when the NZS 3101:2006 minimum vertical reinforcement limit was satisfied for a known concrete strength, the wall was still susceptible to sudden failure unless a significant axial load was applied. Additionally, current equations for minimum reinforcement based on a sectional analysis approach do not adequately address the issues related to crack control and distribution of inelastic deformations in ductile walls.
