A Boeing 787’s wings being flexed upward approximately 25ft (7.6m) – equaling 150% of the most extreme forces a wing is expected to experience while in service.
Photo credit: The Boeing Co.

A team including National Institute of Standards and Technology (NIST) scientists has found a way to improve simulation of failure onset in materials used to build airplane wings. Understanding this initiation point is critical for predicting when and how wings fail. The method shows designers how to put a sample through a series of stress scenarios to efficiently determine the amount of stretching that will cause it to break.

According to NIST physicist Paul Patrone, the approach could help address a key factor that reduces the effectiveness of simulations – uncertainty in their prediction of the wing’s strength.

“Probably the most dramatic material property that aerospace engineers and the public care about is how far a wing can bend before it breaks,” Patrone says. “Historically, simulations have done a poor job at predicting this because you need detailed information about the material’s atomic structure over large distances. Computers simply aren’t powerful enough to simulate such systems, so we’re hoping that this new approach will provide a workaround.”

One approach has been to directly simulate the force required to bend small samples of material – a few thousand atoms – rather than an entire wing. “It’s possible to run 50 of these simulations a week on a supercomputer,” Patrone says. “In principle, that helps engineers zero-in on the combinations that are worth testing in the lab. The problem is that we have to infer the damage initiation indirectly from the simulated forces, which simply doesn’t work well for such small systems.”

The team hit upon a better way: Simulate deforming a tiny bit of material by increasing amounts, and make it possible to save the state of the simulation at any given point. The advantage of state-saving is that you can see what happens if the material is allowed to relax.

“It’s kind of like taking the material down a road with different forks and looking at what happens down each one,” he says. “We pause the simulation at different points along the way and ask, ‘If I stopped trying to bend this, what would happen? Would it stay bent, or bounce back to its original shape?’ We have the ability to explore all these forks, which allows us to more precisely state when the material was first damaged.”

Because a new jet can run up several billion dollars in development costs, improvements like this can help companies trust the reliability of their modeling approaches before they commit to more expensive steps involving real-world materials.

“Our approach provides a new signal for a material’s breaking point that will hopefully improve the reliability of the simulations,” Patrone says. “It also allowed us to statistically quantify our confidence in their predictions. We need that, if simulations are to be used as a proxy for experiments.”

National Institute of Standards and Technology