The predicted future increase in sea surface temperature will cause more intense and destructive tropical hurricanes. Given the significant impact of future hurricanes on society and ecosystems, characterizing turbulent hurricane winds in the near-surface region is now a global priority. The structure of turbulence in hurricanes profoundly differs from that of conventional atmospheric flows, thus influencing wind loads on both build and natural environments. Current knowledge on these flow phenomena lags behind actual needs, thus introducing a degree of uncertainty on structural and ecosystem reliability that needs to be addressed. The goal of this project is to develop new visualization techniques to identify coherent patterns (the 3-D structure of wind gusts) in hurricane turbulence. A large database from high-fidelity 3-D large-eddy simulations will be leveraged along with techniques from turbulence theory. The student will learn to work with big data and gain fundamental understanding of complex flow phenomena and 3-D visualization techniques.
Direct Supervisor: Marco Giometto
Hours per week: 35
Dates: 6/1/2020 - 8/31/2020
Qualifications: Fluid Mechanics, Python programming, Numerical methods.
Eligibility: SEAS only