Image to right: Iteration computer art displaying the methodology to analyze, predict, and prevent wing drop.

The call came from the Department of Defense. One of their multi-billion dollar aircraft programs had a problem. Their F/A-18/EF Super Hornet jets exhibited a tendency for "wing drop," a phenomenon when either the left or right wing panel stalls before the other, resulting in significant rolling motion.

NASA's Abrupt Wing Stall (AWS) project swung into action, partnering with the Department to develop a technology to predict the undesirable flight characteristic, and to test for the defect using NASA's research wind tunnels. Such technology did not exist before, and NASA had to develop a new system of predictive metrics for the wind tunnel, as well as be sure its computational tools could tackle the complex patterns of air flows that cause wing drop. The predictive technologies are now in use by the Joint Strike Fighter program.

AWS Team
NASA Langley Research Center, NASA Ames Research Center, Naval Air Systems Command, Office of Naval Research, U.S. Air Force Research Laboratory, The Boeing Company, Lockheed Martin Aero, Ball Aerospace, U.S. Air Force Academy