Jim McElwaine, Institute of Hazard Risk and Resilience, Durham University, UK – Clark 507
This will be a hybrid seminar held in Clark 507. If you wish to join virtually, you can access the Zoom link here: https://whoi-edu.zoom.us/j/93697037824?pwd=aVk1L0ZERmdqU1JLTkNsMnJ2SUxOUT09
Meeting ID: 936 9703 7824
Passcode: Q%Aq2!

Abstract: Turbidity currents are among the largest flows on Earth and are important for many reasons including their role as agents of sediment transport into the oceans and their impact on human infrastructure such as undersea cables. They have been observed to propagate for very long distances, longer than one would expect based on the current knowledge of mixing and evolution of gravity currents, and their behavior is poorly predicted by current models. This talk describes the results of recent experiments and DNS which suggest that when in steady state, gravity currents presents a much more stable interface, reducing the mixing with ambient waters and hence enable them to survive and propagate for longer distances.

Bio: The underlying theme of Jim McElwaine’s research is to observe complex fluid dynamical phenomena and to develop experiments that test the mathematical models that describe and predict their behavior.  His background is in applied mathematics, which he studied at Cambridge for seven years. He then worked at the institute of Low Temperature Science at the University of Hokkaido in Japan for five years on snow avalanches and wind transport, with brief spells in Grenoble and Colorado. He returned to Cambridge in 2001, with a Royal Society University Research Fellowship followed by an EPSRC Advanced Research

Fellowship, and we worked there for 12 years followed by a year at the Swiss Federal Institute for Snow and Avalanche Research in Davos. He is currently Professor of Geohazards in the Department of Earth Sciences at the University of Durham.  Much of his work is concerned with closure problems: how can detailed small scale phenomena be included in large scale models? This is critical for modelling many phenomena including those in the ocean environment and climate science.