“Wave-height distributions and nonlinear effects” published by M.A. Tayfun and F. Fedele is listed as the most cited article published since 2007, according to SciVerse Scopus. The article appears Ocean Engineering, an Elsiever journal.
Dr. Francesco Fedele is an assistant professor with a joint appointment in the Schools of Civil and Environmental Engineering and Electrical and Computer Engineering at Georgia Tech. He earned his Ph.D. in civil engineering from the University of Vermont and his Laurea (magna cum laude) in civil engineering from the University Mediterranea, Italy. Dr. Fedele joined the faculty at Georgia Tech in 2007 after a postdoctoral research position at the NASA Goddard Space Flight Center. His current research focus is on nonlinear wave phenomena, fluid mechanics, sustainable ocean energy, computational methods and inverse problems. The corresponding research thrusts are: wave turbulence and rogue waves, algorithms for biomedical tomographic imaging, mathematical modeling and experimentation on renewable devices to harness energy from tidal streams.
In that paper he presented a stochastic approach to study nonlinear random waves that not only generalizes well established theoretical wave models such as the Tayfun model, but also provides a new theoretical formulation for the predictions of rogue waves, unusually large waves that suddenly arise in the open ocean. In the scientific literature Fedele’s intellectual contribution on nonlinear water waves is cited and referred to as the third order Tayfun-Fedele model.
To predict the height of crests and the depths of troughs of ocean waves, engineers rely on the well-known Gaussian distribution from the work of German mathematician and scientist Johann Carl Friedrich Gauss. Unfortunately, such model is not enough to address the problem of predicting extreme ocean waves. The work of Dr. Fedele presents a new statistical distribution that is able to predict unusually large wave heights and crests observed in experiments. The Tayfun-Fedele model may be able to provide a statistical approach for the prediction of rogue waves, the key element for the design of ocean-based oil and gas platforms. Underestimation of the height of waves may lead to failure of the structure under extreme conditions.