Infrastructure Inspection During and After Unexpected Events - Phase V

During flooding, hydrodynamic loading on the bridge depends upon several factors, such as surge speed and height, wavelength, wave period, and wave amplitude, in any projected streamway. Additional hydrodynamic forces arise as external perturbations (e.g., due to currents or storm surge) and changes in the effective inertial and damping forces, which alter the resonance conditions of the bridge as inundation occurs. Both types of forces could put the bridge under excessive stress conditions that are different than the normal conditions, and that may reduce the bridge’s operational loading capacity.<br /><br />With weather forecasting showing storms of increasing strength and frequency, this work will develop a tool that will predict the loading capacity of the structure during and after the events which will be essential for emergency responders and the safety and management of the critical routes of the transportation system. The proposed methodology can be integrated with weather- and flood-prediction software in the future to provide a complete picture of the status of critical structures before, during, and after extreme weather events.

The objective of the proposed work is to predict bridge loading capacity during severe flooding events, thereby informing the weight and possibly the velocity of road vehicles that can be allowed to cross the bridge during the events. The proposed research will be composed of the following four tasks: (A) use the commercial software ANSYS to compute Hydraulic Added Mass (HAM), with an emphasis on resonance effects; (B) test/validate HAM effects on a simplified bridge superstructure using lab experiments; (C) explore the possibility of adjusting AASHTO formulas to consider HAM; and (D) write a final report.

The expected outcome of this work will be a physics-based visualization module that can predict bridge loading capacity during dry and wet conditions, including flood events. The module can be integrated with current weather forecasting models such as the Iowa Flood Information System (IFIS), which has the capability to predict the rise in rivers during severe storm events and presents flooded maps across different counties in the state of Iowa.

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