PI: James Ricles
Co-PI(s): Liang Cao
University: Lehigh University
Unexpected natural hazard events (high-to-extreme wind, earthquake, etc.) and operational natural hazard (low-to-high winds) can cause economic, human, and cultural losses due to structural or nonstructural damage and temporary or long-term inoperability of a building. Energy dissipation systems can be used to enhance the performance of civil structures to these multi-hazard events. In general, there are three types of supplemental control strategies: passive, semi-active, and active. Of these, semi-active devices offer some of the greatest benefits for increasing resiliency because they can modulate their responses to a particular hazard, and unlike active systems, they do not require large energy inputs and do not have the potential to destabilize the structure.
The proposed project will outfit a new generation friction damper, called a Banded Rotary Friction Damper (BRFD), with semi-active control features to enhance the performance of buildings subjected to natural hazards that includes forces from wind and earthquake ground motions. Buildings of different geometries and configurations will be outfitted with BRFDs. Using real-time hybrid simulations, these structures will then be subjected to wind and earthquake loading to systematically investigate the effectiveness of the BRFD towards improving the resilience of buildings to natural hazards. Real-time machine learning will be used to tune control algorithms that enable the control law to be self-tuning to provide optimal control, making the BRFD autonomous. The proposed project will utilize the resources that exist at the Natural Hazards Engineering Research Infrastructure (NHERI) Lehigh Real-Time Multi-Directional (RTMD) Experimental Facility (EF) housed in the Advanced Technology for Large Structural Systems (ATLSS) Engineering Research Center.