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Mathematical Modeling Helps Make Smart Weapons Smarter

Researchers' Analysis Helps Improve Performance

Fighter jet releasing a bunker buster
An F-15E Strike Eagle fighter jet releases a GBU-28 “bunker buster,” a 4,700-pound laser-guided bomb. Conventional smart bombs and guided missiles were first used during the 1991 Gulf War and, more recently, in Iraq, Afghanistan and Syria.

04/14/2016
By Edwin L. Aguirre

For full version of this story, please see Engineering Solutions Spring 2016 pdf.
Destroying an enemy target that is heavily fortified or buried deep underground requires a special type of bomb or missile. The so-called “bunker buster” delivered by aircraft is designed to penetrate steel-reinforced concrete or granite bedrock before exploding, thereby maximizing its effectiveness.

A team of researchers from the university’s Structural Dynamics and Acoustic Systems Laboratory (SDASL) led by mechanical engineering Prof. Peter Avitabile recently received more than $425,000 in funding from Eglin Air Force Base (AFB) in Florida to help improve the efficiency of the bunker buster’s conventional fuze, which detonates the bomb once it has penetrated deeply enough to destroy the target.

The four-year project — entitled “Nonstationary System State Identification Using Complex Polynomial Representations” — utilizes mathematical modeling and analyses to develop the design tools.

“Current missile-penetration strategies need to be augmented with ‘smart fuzes’ that quickly assess the structural health of a missile in real time as it penetrates barriers and very rapidly make decisions regarding the mission profile,” says Avitabile, who is the SDASL co-director and the project’s principal investigator. “The damage detection that provides the missile’s current condition needs to be identified at an extremely fast pace.”
Bunker exploding
Bunker busters are designed to destroy hardened military targets such as underground command centers and missile silos as well as aircraft shelters (as shown in this bomb test conducted at Eglin Air Force Base in Florida).


Previous work by Avitabile for Eglin AFB, which was funded by an earlier three-year contract for $380,000), had identified highly efficient methodologies to predict a missile’s state of health. “Basically all the previous analytical modeling methodologies are being completely revamped and repurposed for this unique damage-detection program. The approaches we are taking in the new project are a radical departure from the conventional ones that are often taken by many researchers in the field,” he says.

In addition to Avitabile, other members of the team include mechanical engineering graduate students Tina Dardeno ’14 and Patrick Logan ’14, who are pursuing their Ph.D. research at SDASL.