to map out a search plan, or regions where teams should concentrate their search.


But the ocean is a complicated space of unsteady, ever-changing flow patterns. Coupled with the fact that a missing person has likely been continuously floating through this unsteady flow field for some time, Peacock and his colleagues say that significant errors can accumulate in predicting where to look first, when using a simple approach that directly predicts the trajectories of a few drifting objects.


Instead, the team developed a method to interpret the ocean’s complex flows using advanced, data-driven ocean modeling and prediction systems. They used a novel “Eulerian” approach, in contrast to more commonly used “Lagrangian” approaches — mathematical techniques that


involve integrating snapshots of the ocean velocity due to waves and currents to slowly generate an uncertain trajectory for where a missing person or object may have been carried.


The new Eulerian approach uses the most reliable velocity forecast snapshots, close to the point where a missing person or object was last seen, and quickly uncovers the most attracting regions of the ocean at a given time. These Eulerian predictions are then continuously updated when the next batch of updated velocity information becomes available.


The team has named their approach TRAPS, for its goal of identifying TRansient Attracting Profiles, or short-lived regions where water may converge and be likely to pull objects or people. The method is based on a recent mathematical


theory, developed by Serra and Haller at ETH Zurich, to uncover hidden attracting structures in highly unsteady flow data.


“We were a bit skeptical whether a mathematical theory like this would work out on a ship, in real time,” Haller says. “We were all pleasantly surprised to see how well it repeatedly did.”


“We can think of these ‘traps’ as moving magnets, attracting a set of coins thrown on a table. The Lagrangian trajectories of coins are very uncertain, yet the strongest Eulerian magnets predict the coin positions over short times,” Serra says.


“The key thing is, the traps may not have any signature in the ocean current field,” Peacock adds. “If you do this processing for the traps, they might pop up in very different


Image courtesy of the researchers/http://news.mit.edu/


A new MIT-developed search-and-rescue algorithm identifies hidden “traps” in ocean waters. The method may help quickly identify regions where objects — and missing people — may have converged.


64 | The Report • September 2020 • Issue 93


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