Nebraska Engineering Fall, 2005
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The Science of Prediction

David H Allen
David Allen creates mathematical models that predict how tank armor will react to ballistic impact.

Galileo said if we can understand nature, we can predict the future. While that may seem more like science fiction than scientific fact, the father of modern physics was right. And David Allen, dean of the College of Engineering, is working to prove it. An expert in blast mitigation, Allen creates mathematical models that predict how tank armor will react to a ballistic impact. This predictive methodology could have far-reaching applications, including medicine and the meat industry.

“One way to predict the response of tank armor to ballistics is to design armor of different thicknesses and materials, then shoot projectiles at it to see what happens,” Allen says. Firing real ballistics at real tanks is cost prohibitive, so the army relies on models to keep costs down.

When designing models, Allen first decides what he wants to know about the thing he will be modeling. He then constructs a well-posed mathematical model, incorporating a set of equations that are sufficient to answer the problem. The key, he says, is using fundamental physics and keeping things simple. The models can predict the propagation of hundreds of cracks at the same time within a matter of microseconds.

Allen tests his tank armor models at Aberdeen Testing Grounds in Aberdeen, Md. The models predict the response of hypothetical armor to hypothetical ballistic impacts. From this he and other researchers determine how to design armor that better deflects ballistic impacts—and is lightweight.

“In the first Gulf War, many tanks were lost to the sand,” Allen said. “At 80 tons each, the armor was simply too massive.” The cost to the Army was exorbitant.

The objective is to find lightweight materials to get the weight down to 30 tons so tanks won’t bog down in desert warfare, but will still protect soldiers.

The same premise can be applied to certain medical problems. For example, Allen says, a good predictor of an aneurysm could be used to save a person’s life.

“Right now doctors can determine by direct observation if a person has an aneurysm through an MRI. But they really don’t understand he physics of how it works when it kills a patient or when it will reach a critical point and burst.”

If doctors could predict when the fracture of the aneurysm will occur, they could do a local procedure or find another method to treat it.

“Good predictors allow us to develop new inventions to treat patients.”

—Constance Walter