Developing Bridge Weigh-in-Motion (B-WIM) Health Monitoring Systems for Bridge Infrastructure Safety

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This grant provides funding for research on the Next Generation Bridge Weigh-in-Motion (B-WIM) system. This system addresses the bridge safety problem using a two-fold approach: the control of overloaded trucks and the safety assessment/monitoring of bridges. The research will be based on the mathematical modeling of a coupled system of differential equations that represent the dynamic interaction of a moving truck with a bridge while accounting for uncertainties that are due to the unknown road profile and dynamic truck properties. The road profile can be measured but, as it is likely to change over time and the exact transverse location of the truck in its lane is unknown, there is a stochastic component of the system. Therefore, the spring and damping properties of the truck tire and suspension will be treated probabilistically, using a Bayesian Updating approach for the properties of the truck fleet. The difficulties associated with this system when it detects the presence of other smaller vehicles that interfere with the signal will be addressed using a new field of statistics known as the "Classification with a Reject Option". In this way, fleets of vehicles can be simulated to represent a range of situations and the simulations will be complemented by independent field trials for validation purposes. This project seeks to develop a bridge monitoring and protection system that is effective without being manpower intensive. This project, jointly funded by UK and Ireland funding agencies that leverage the NSF investment, will generate a broad spectrum of spin-off technologies. The potential payoff of this program could be the rapid technology insertion into existing bridge maintenance systems that are needed for much of the bridge stock in the USA and Europe. Moreover, wide deployment of this system has the potential to greatly improve the effectiveness of overload enforcement and to increase road safety for all users.