Smoke from a controlled mine detonation in Angola in 1995. Courtesy of the International Committee of the Red Cross and Paul Grabhorn.

Getting a good three-dimensional picture of dirt and seeing how different kinds of waves penetrate the surface and bounce through and out of the column let El-Shenawee move to the next step, simulating buried targets.

Large, metal anti-tank mines are no problem, Rappaport says. Finding them doesn't even require a sophisticated sensing process. "That's a solved problem," he says. "Go down to Radio Shack, buy a metal detector, and you're in business." In contrast El-Shenawee's model is designed to help the team detect cheaper and more prevalent plastic anti-personnel mines. These mines can be quite small, as little as three inches in diameter, and they're often buried unmarked and forgotten.

"These are the ones that are tough to find," Rappaport says. "The plastic and the soil background look the same. Electromagnetically, the explosive in the mine looks like the soil." Often these mines contain only as much metal as a BB, rendering useless the conventional, Radio Shack methods.

Mines found on Afghanistan border in 1994. Courtesy of the International Committee of the Red Cross.

To start finding these tiny targets, El-Shenawee used NCSA's Origin2000 system to complete hundreds of runs that held just soil and hundreds that contained a buried mine. Side by side, images from the two types of runs looked remarkably similar. But subtracting the dirt from the model with a mine and using the model of just the ground as a reference caused the hidden explosive to suddenly pop into view. This simple subtraction began to give El-Shenawee a perfect picture of the mine itself. Using this information, she's started measuring and cataloging the distinguishing features of the waves that scatter when they collide with a mine.

The idea, Rappaport says, is that this will ultimately help develop sensors that can find the little mines and unveil some clues about where to look for the mines in the first place. But there's still a fly in the ointment. Unlike modeled dirt, real dirt isn't very clean.

"The natural state of soil is so complex," Rappaport said. "There're lots of rocks and roots and vegetation, all sorts of junk is thrown in."

The team is beginning to combat this problem as well by modeling earth that has other buried objects in it. Simulations like these will help the team discern between a buried mine and the false positive of a buried rock.

Even with such a model, however, there's a long way to go between these still-in-development models and the current state of the art. The U.S. Army, which uses the best available detection equipment, is still using systems based on 50-year-old metal-detector technology, according to Rapapport. Further, the world's most common detection method, used by the cash-poor countries that are riddled with mines, is still crawling belly-down on the ground, poking a sharp stick into the dirt, feeling for resistance.

In such a world, the smallest advance would be great step forward. The Northeastern team is already on its way to finding a new, sophisticated way to dig through the dirt—and save lives.

This research is supported by the Army Research Office and the Department of Defense.