Rebecca Freese - Weigh-In-Motion (WIM)-Based Live-Load Fragility Analysis for a Steel Bridge using a Structural Health Monitoring System
In the summer of 2015, I participated in an REU at South Dakota State University. My problem involved using statistics to model the probability that a bridge is damaged as certain five-axle trucks pass over it. Using Weigh-In-Motion (WIM) and structural health data collected at an existing bridge in Iowa, fragility curves were generated from best-fit regression to model the probability that the bridge exceeds a certain limit state when it is subjected to a set of external live loads. Nine significant truck characteristics were looked at in their role in causing a below satisfactory bridge capacity. These truck characteristics correspond to the weight of the five axles and the four spacings between them. These variables were analyzed graphically and statistically to determine which ones most significantly affect its respective fragility curve. These most significant variables must be taken into higher regard than the others in ensuring the structural safety of the bridge subjected to unknown trucks. Key findings reveal that the first two axle weights and the second axle spacing most significantly affect their respective fragility curves.