Finite element modeling and long-wave infrared imaging for detection and identification of buried objects

Detection of buried improvised explosive devices (IED) represents a complex threat to U.S. forces. This thesis explores the potential use of infrared images combined with finite element models to detect buried objects in soil. Initially, computer simulations using COMSOL Multiphysics software implemented a range of heat transfer dynamics to assess the feasibility of this approach. Then, an experimental setup was constructed to measure the surface temperature profile of a sandbox containing buried objects using a long-wave infrared camera. Images were recorded for several days under ambient conditions to determine detection capability for various attributes describing the buried object (shape, size, material and depth) and correlation to time of day. Best detection of buried objects corresponded to shallow depths for observed intervals where maxima/minima ambient temperatures coincided with expected diurnal cycling effects. Thermal contrast in the sand surrounding the buried object was not distinguishable at depths greater than eight cm. Utilizing a technique that extracted a surface intensity profile and fitted against simulated data for various soft metals (thermal conductivities and densities) indicated the potential ability to estimate a buried object's material composition. The preliminary results of the research indicate that infrared imaging could be used for passive detection of shallowly buried objects.http://archive.org/details/finiteelementmod1094556822Lieutenant, United States NavyApproved for public release; distribution is unlimited