Project Name :
Study of Soil’s Roughness Effect in the Unexploded Ordnances (UXO) Problem (Detection and Discrimination) Using Electromagnetic Modeling, Based on the Method of Auxiliary Sources (MAS)
Donor Organization :
GNSF, President Grants for Young Scientists
Budget:
15000 GEL
Grant number :
GNSF/PRES08/5-326
Research Direction :
9 Earth Sciences and Environment
Sub Direction :
9-210 Pollution and Remediation
Keyword(s) :
UXO, MAS
Description :
The proposed research into Electromagnetic forward and inverse modeling approaches that is based on the Method of auxiliary sources, is aimed at developing efficient methodologies to enhance detection and discrimination of subsurface objects.
In particular, the proposal develops new forward and inverse modeling approaches to address today’s most pressing environmental problem: detection and discrimination a buried subsurface objects, such as landmines, unexploded ordnances (UXO), geophysical deposits, and etc. The landmines and UXOs cleanup problems are not only well-defined issues for Georgia, (Note: in last decade several ethnic conflicts took place in Georgia) these are as one of most urgent problem around the world as well. The high costs that are associated of excavating all geophysical anomalies are well known and are one of the greatest impediments to efficient clean-up of landmines and UXO contaminated lands at former military sites. Recently, low frequency electromagnetic induction sensing has been identified as one of most promising technologies for both detection and discrimination; however, classifying between an object of interests and metallic clutter continues to be a major environmental cleanup problem. For example, field experiences indicate that 75% of the costs to clean up UXO sites are currently spent on excavating targets that pose no threat. Innovative discrimination techniques that can reliably distinguish between object of interests and non-important metallic items are required, particularly in areas where the geological background causes a measurable response in the sensor.
Duration :
01/01/2009 - 31/12/2009
Project Leader :
Giorgi Ghvedashvili
Project manager :
Project participant(s) :
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