Mathematical models offer clues
to greater efficiency for glider pilots
Date: August 1, 2016
Source: University of California
- San Diego
Migratory birds often use warm,
rising atmospheric currents to gain height with little energy expenditure when
flying over long distances.
It's a behavior known as thermal
soaring that requires complex decision-making within the turbulent environment
of a rising column of warm air from the sun baked surface of the earth.
But exactly how birds navigate
within this ever-changing environment to optimize their thermal soaring was
unknown until a team of physicists and biologists at the University of
California San Diego took an exacting computational look at the problem.
In this week's online version of
the journal Proceedings of the National Academy of Sciences, the
scientists demonstrated with mathematical models how glider pilots might be
able to soar more efficiently by adopting the learning strategies that birds
use to navigate their way through thermals.
"Relatively little is known
about the navigation strategies used by birds to cope with these challenging
conditions, mainly because past computational research examined soaring in
unrealistically simplified situations," explained Massimo Vergassola, a
professor of physics at UC San Diego.
To tackle the problem, he and his
colleagues, including Terrence Sejnowski, a professor of neurobiology at the
Salk Institute and UC San Diego, combined numerical simulations of atmospheric
flow with "reinforcement learning algorithms" -- equations originally
developed to model the behavior and improved performance of animals learning a
new task. Those algorithms were developed in a manner that trained a glider to
navigate complex turbulent environments based on feedback on the glider's
soaring performance.
