Dartmouth engineering professor earns DoD Project-of-the-Year award
November 30, 2011
For technology that could help rid battle sites of unexploded bombs, engineering professor Fridon Shubitidze received a Project-of-the-Year award yesterday at the Department of Defense’s (DoD) 2011 Partners in Environmental Technology Technical Symposium & Workshop in Washington, D.C. Professor Shubitidze was honored as a “partner who has helped DoD achieve its mission while improving its environmental performance.”
Part of Dartmouth’s ongoing Geophysical Sensing Program, the project was submitted in response to DoD’s stated need for “Unexploded ordnance (UXO) technology: Advanced technologies for detection, discrimination, and remediation of munitions and explosives of concern.”
UXO is an enormous problem worldwide. In the U.S. alone, approximately 11,000,000 acres of land hold a potential UXO hazard—from military practice ranges to sites of long passed conflicts. UXO may remain dangerous over many years (Cuba reported the explosion of a projectile in Santiago Harbor some 100 years after it was fired during the Spanish American War). During World War I about 15% of bombs failed to detonate. Near the city of Verdun, France alone, an estimated 12 million unexploded shells still remain in the ground, many in degraded condition and full of toxic materials. In addition, found UXO is used to build improvised explosive devices (IEDs), a.k.a. the devastating roadside bombs often used in our current overseas conflicts.
Although metal detectors are cheap and abundant, the ability to distinguish UXO from harmless metal objects has remained elusive. The conventional method of locating UXO by digging up to 500 holes per acre is costly and ineffective.
Dartmouth researchers—such as Kevin O’Neill, Adjunct Professor of Engineering and Research Civil Engineer at USA-CRREL—have pursued UXO remote sensing technology since the 1980s. Building upon that work, Shubitidze’s project is entitled, “A Complex Approach to UXO Discrimination: Combining advanced electromagnetic induction (EMI) forward and statistical signal processing algorithms.”
"Our approach has consistently performed better than that of other teams during live-site studies where we were the only group to correctly identify all UXO items,” said Shubitidze. “That success is due to the advanced forward models developed at Dartmouth over the last ten years which fully take into account the underlying physics of low-frequency electromagnetic sensing phenomena and are able to utilize all information provided by the sensors.”
Live-site study: 100% UXO found, 95% non-UXO left in ground
To continue this work, DoD-SERDP (Strategic Environmental Research and Development Program) has awarded Shubitidze's team an additional three-year $1.4 million grant for "Advanced EMI Models and Classification Algorithms: The next level of sophistication to improve discrimination of challenging targets." This next phase will aim to further improve the detection and classification of small and deep UXO by integrating advanced EMI models into sensor hardware and software for real-time data collection guidance.