Infrastructure Inspection During and After Unexpected Events - Phase I

During and after natural disasters, cities will experience chaos when emergency responders have difficulty localizing and quantifying the intensity of damage to civil infrastructures at a time when citizens’ safety and wellbeing are in danger. The goal of this research is to develop, test, and refine a probabilistic damage-detection methodology to determine structural health conditions during/following extreme wind conditions and use it as a decision-making tool to minimize the disaster’s effect by improving the ability to respond to and recover from the disaster. The research for developing a damage-detection method comprises four steps. First, a probabilistic hybrid damage-detection algorithm, based on the integration of strain and acceleration data, will be developed. Second, the damage-detection method will be tested on a scaled highway bridge under seismic loading conditions using a shaking table. Third, the damage-detection method will be tested and refined under extreme wind conditions using a wind tunnel that simulates high-wind conditions. Finally, the damage-detection method will be tested and refined inside the wind tunnel with bridges that have different damage scenarios. This research will provide emergency responders an instantaneous image of the severity and distribution of damage across the city in a timely fashion and will thus provide a tool to prioritize response planning. The method will also guide maintenance and repair teams to the specific locations in the structure where damage is most critical.

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Final Data: https://doi.org/10.13014/K2VX0DRZ