Greek MIT scientist creates model that may help predict precursor conditions to

first_img Facebook Twitter: @NeosKosmos Instagram Themistoklis Sapsis, Associate Professor of Mechanical and Ocean Engineering at the Massachusetts Institute of Technology has co-authored a Science Advances paper that might be able to use engineering models to plot a hurricane’s course with reasonable levels of accuracy.Using a series of engineering formulas, the research lead to the development of an algorithm for computing the precursors of extreme events, in complicated systems with lots of turbulence.“Currently, there is no method to explain when these extreme events occur,” said Sapsis in a news release clarifying that extreme weather events happen so rarely that there’s just not much data about them, at least not enough to come up with predictive technology.“We have applied this framework to turbulent fluid flows; which are the ‘Holy Grail’ of extreme events. If we can predict the occurrence of these extreme events, hopefully we can apply some control strategies to avoid them,” he continued.He says the best tools scientists have for predicting when turbulent fluid flows will form are equations meant to predict the behaviour of a complex system over time, but they simply don’t have enough data about extreme weather events to plug into them.An algorithm was created to replace the equations, combining exactly those equations previously used to predict the events with existing weather data to pinpoint conditions that qualify as “precursors” to turbulent flow. Sapsis and co-author Mohammad Faeazmand then tested its accuracy by running simulations of turbulent flows looking for the precursors that the algorithm had created. The precursors were accurate predictors of extreme events between 75 and 99 per cent of the time. Many extreme events, from a rogue wave that rises up from calm waters, to an instability inside a gas turbine, to the sudden extinction of a previously hardy wildlife species seem to occur without warning. It’s often impossible to predict when such bursts of instability will strike.Now, as Sapsis confirms, the framework of their study is generalisable enough to apply to a wide range of systems in which extreme events may occur, separating the exotic. He plans to apply the technique to scenarios in which fluid flows against a boundary or wall. Examples, he says, are air flows around jet planes, and ocean currents against oil risers.“This happens in random places around the world,” Sapsis says. “If you can predict where these things occur, maybe you can develop some control techniques to suppress them.”last_img

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