Feb 1, 2019 | By Cameron

Mathematicians at New York University 3D printed 15 generations of algorithmically-bred wing designs to determine what shapes were best for flapping. When a wing flaps, vortices are generated at the leading edge and the tail edge of the wing and the interaction of those vortices determine the efficiency of the wing. To come up with the best design, the team looked to biological evolution.

"We can simulate biological evolution in the lab by generating a population of wings of different shapes, have them compete to achieve some desired objective, in this case, speed, and then have the best wings 'breed' to make related shapes that do even better," said Leif Ristroph, an assistant professor at NYU’s Courant Institute of Mathematical Sciences and the paper's senior author.

The experiments took place in NYU's Applied Math Lab, where the researchers started with 10 different 3D printed wings. Cavities were modeled into each wing that hold and dispense two fluorescent dyes: red in the front and green in the back. When the wing is flapped in the flow tank, the dyes reveal the eddies and vortices. For their tests, each wing was “raced” against the others by measuring their speed. On short wings, the vortex that forms on the leading edge crashes into the rear vortex, causing turbulence and slowing the wing. Longer wings diffuse the leading vortex before it reaches the rear edge, resulting in a faster wing.

Traits of the winning/faster wings were “bred” (combined) with the traits of other faster wings, creating 3D printed “daughter” wings that were then raced against each other. The process was repeated for 15 generations, yielding faster and faster wing offspring. "This 'survival of the fastest' process automatically discovers a quickest teardrop-shaped wing that most effectively manipulates the flows to generate thrust," explained Ristroph. "Further, because we explored a large variety of shapes in our study, we were also able to identify exactly what aspects of the shape were most responsible for the strong performance of the fastest wings."

Their data can be used to improve airfoils on planes as well as submarine designs, but Ristroph believes there’s potential for energy capturing, "We think this could be used, for example, to optimize the shape of a structure for harvesting the energy in water waves." 3D printing makes these kinds of iterative, generational designs incredibly affordable; the costs of fabricating these wings with subtractive manufacturing methods would have limited the team to only a couple iterations, drastically reducing the optimization that was achieved with multiple iterations.

Posted in 3D Printing Application

Maybe you also like: