Abstract: This paper presents a methodology on prioritizing deployment of scour sensors at high-risk bridges using a holistic approach. Specifically, stream geomorphic data, bridge design information, and bridge scour ratings are used to intelligently identify and prioritize bridge sites for remote scour monitoring. Scour is the leading cause of bridge failure, with 309 bridges in the State of Vermont rated as scour critical. Using Vermont as a case study, this work looks to correlate bridge structural design data with hydraulic and stream geomorphic information to identify bridges at high risk of scour processes, and specifically for bridges more structurally susceptible to scour damage. Including additional stream and hydraulic indicators in the analysis, rather than relying on structural evaluations alone, enables areas of geomorphic instability to be identified; and bridges in these areas can be outfitted with scour monitoring devices. Lowcost monitoring devices are proposed to monitor at-risk bridges and to provide additional information in scour-prone areas. A sensor under development would allow for direct installment into stream beds at existing bridges, and incorporate accelerometer-based monitoring, with wireless data transmission. The device would allow for real-time measurement of streambed degradation and aggradation during high flow events, thereby providing timely information regarding critical scour events. This work aims to aid State transportation engineers in identifying, which bridges in the transportation network are at risk, of scour processes, provides useful insight into scour rating systems, and assesses the value of the geomorphic assessments to improve our existing bridge rating system. The compilation of results from geomorphic assessments, scour ratings, and bridge design information will be presented.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).