Abstract:Capital investment in national infrastructure is significant. The need to maintain and protect critical infrastructure links has led in recent years to significant developments in the area of structural health monitoring. The objective is to track a structure's long-term performance, typically using sensors, and to successively compare most recently measured responses with prior response history. During construction of the West Street On-Ramp, a curved concrete box girder bridge, located in the city of Anaheim (California), eleven accelerometers were permanently installed on its bridge deck. The associated data acquisition system was configured to record once a specified threshold acceleration response was exceeded; during the period 2002 -2010 a total of 1350 datasets including six earthquakes, for each of the eleven sensors, were acquired. This automatically acquired data was supplemented, during the summer of 2009, with responses measured during controlled vehicle tests. Six accelerometers were additionally installed on the frame of the weighed test vehicle. This paper presents the findings of the analyses of these measured data sets and serves to inform owners and managers as to the potential feedback from their instrumentation investment. All response histories were analyzed using frequency domain techniques for system identification. Extraction of the modal characteristics revealed a continuous reduction, of approximately 5%, in the first three natural frequencies over the period of the study. The measured responses from the vehicle sensors are discussed in the context of identifying the potential for bridge frequency measurement using instrumented vehicles.

In the probabilistic seismic risk assessment of highway transportation networks, fragility curves are used to represent the vulnerability of a bridge. Because these networks have hundreds or thousands of bridges, it is not possible to study each bridge individually. Instead, bridges with similar properties are grouped together and are represented by the same fragility curve. However, this approach may be inadequate at times for different reasons. For instance, bridges with similar geometrical and material properties could have different age and/or could deteriorate at a different rate. Moreover, certain bridges are unique such as a cable stayed bridge or a suspension bridge. In this study, fragility curves are calculated based not only on the geometry and material properties but also on vibration data recorded by a structural health monitoring system. The fragility curves are used to track changes of the structural parameters of a bridge throughout its service life. Based on vibration data the fragility curves are updated reflecting a change in structural parameters. Fragility curves based on vibration data, whenever these are available, represent the vulnerability of a bridge with greater accuracy than fragility curves based only on the geometry and material properties. This article demonstrates the applicability of structural health monitoring to generate more reliable fragility curves. This is useful not only for bridges that are unique, which are usually the first to be instrumented, but for every instrumented bridge as well.

SUMMARY Between 2005 and 2010 six earthquakes triggered a monitoring system consisting of 11 acceleration channels installed on the West Street On‐Ramp, a three‐span curved highway bridge located in the city of Anaheim, California. In this paper, three different system identification techniques are applied to the acceleration records to investigate and corroborate the dynamic properties of the bridge, that is, vibration frequencies, associated damping ratios and mode shapes. The identification techniques are applied to each one of the six seismic events. The identified frequencies and damping ratios are shown to be dependent variables of the earthquake intensity. In general, larger earthquake intensities result in reduced vibration frequencies and higher damping ratios of the bridge. Sensitivity analysis using a simple finite element model reveals that soil softening at the abutments considerably contributes to the variation in frequencies because of changes in the support conditions and ultimately in the global stiffness of the structure. In addition, mathematical models in the state space description are identified from the recorded response and excitation measurements. The state space models successfully replicate the bridge measured response to the earthquake from which it is constituted. The models also provide a reasonable prediction of the bridge response to a different earthquake. Copyright © 2012 John Wiley & Sons, Ltd.