Principal Investigator: Forrest Masters
Co-PI: Luis Aponte
Start Date: August 8, 2018
End Date: March 7, 2019
Motivated by the extensive damage to Puerto Rico caused by Hurricane Maria’s landfall in September 2017, this EArly-concept Grant for Exploratory Research (EAGER) will study how complex topography can accelerate wind and, ultimately, exacerbate damage to buildings and other constructed civil infrastructure. This research will utilize recent advancements in machine learning and weather forecasting to predict wind speed-up in mountainous terrain and other complex terrestrial environments. The project will leverage the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Terraformer Boundary Layer Wind Tunnel (BLWT) at the University of Florida to characterize the surface wind field over geometrically scaled models of Puerto Rico and the municipal Islands of Vieques and Culebra. This EAGER is a collaboration between the University of Florida (which serves the most hurricane prone state in the U.S.) and the University of Puerto Rico at Mayaguez (a Hispanic-serving institution still recovering from Hurricane Maria), and graduate and undergraduate students from both institutions will be actively involved in the experimental and computational work. Anticipated project outcomes will include important new insights about the influence of topography on the behavior of damaging winds, new scientific tools that fuse experimentation with advanced computing methods to study extreme wind effects on constructed civil infrastructure, and benchmark datasets that will be made available to other researchers in the NHERI Data Depot (https://www.DesignSafe-ci.org). Knowledge created by this project can inform future research studies and wind load provisions to improve the resilience of the U.S. to hurricane impacts, and thus better secure the nation’s welfare and prosperity after windstorm events.
More Information: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841979