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A new computer algorithm that helps predict extreme events of land, sea, and air, has been developed by a Greek researcher at the US MIT University.
Many extreme events seem to happen without warning, whether it be a monster wave that from nowhere appears in the ocean to swallow a ship, the unexpected disappearance of an animal species in nature, or the sudden dysfunction of an airplane machine. It is often impossible to predict when such an outbreak of “instability” will emerge, especially in complex systems with many interdependent parts.
However, Themistocles Sapsis, Associate Professor at MIT’s Department of Mechanical Engineering and Naval Engineering, along with his associate postdoctoral researcher Mohammad Farazam, who made the relevant publication in “Science Advances” magazine, devised a way to identify key-signs that precede an extreme event.
The technique can be applied to a wide range of complex systems, which seem to “emit” their own warning messages as long as one can “hear” them. It is no coincidence that the study of the Greek engineer is of interest to the US Armed Forces, so it is funded by the Research Offices of the three Navy (Navy, Air Force and Army).
As Dr. Sapsis said:
Today there is no method to explain when these extreme events will occur. We have applied our new method to chaotic fluid flows, which are the “holy grail” of extreme events. If we can predict these, then we hope that we will be able to implement some control strategies to avoid these extreme events.
Until now, attempts to predict extreme events are based on resolving dynamic equations with incredibly complex mathematical formulas to predict the development of a complex dynamic system over time.
But, according to Dr. Sapsis,
… the physics of several complex systems has not yet been sufficiently understood and their modeling involves serious errors, so the corresponding mathematical equations are not realistic. But, …
as he says,
… even in those systems where their physiology is well understood, there are a huge number of initial conditions with which to feed the relevant dynamic equations, resulting in an equally large number of possible outcomes, which makes it virtually impossible to actually predict an extreme event.
As the Greek engineer points out:
If we just take the equations blindly and start looking for initial conditions that will develop into extreme situations, there is a very good chance that we will end up with initial situations that are too exotic, in other words they will never happen in practice. So the equations contain more data than we actually need.
But if, alternatively, one leaves the equations aside and attempts to search only real world data for characteristic motifs that will warn of an upcoming extreme event, …
as he points out,
… it would take a huge amount of data over a long period of time to be able to locate such a warning sign in time with some certainty.
Dr. Sapsis created a computer algorithm that combines both equations and actual data. This combination helps better to predict extreme events in the real world, says the Athenian agency.
Testing the algorithm in a chaotic fluid dynamics simulation model has shown that it has the ability to predict a future extreme event in 75% to 99% of cases, depending on the complexity of the fluid. Chaotic fluids exist in many forms around us, from cigarette smoke and airflow around an airplane engine to air circulation in the atmosphere, water currents in the oceans, or blood circulation into the body.
Th. Sapsis graduated from the School of Naval Engineering of NTUA in 2005 and received his PhD from the Department of Mechanical Engineering of MIT in 2011, where he also conducted a post-doctoral research. From 2016 he is an associate professor at the same Department of MIT.
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