Abstract
A current area of research interest in national security is to effectively and efficiently determine the contents of the many shipping containers that enter ports in the United States. This interest comes as a result of the 9/11 Commission Act passed by Congress in 2007 that requires 100% of inbound cargo to be scanned by 2012. It appears that this requirement will be achieved by 2012, but as of February of 2009 eighty percent of the 11.5 million inbound cargo containers were being scanned. The systems used today in all major U.S. ports to determine the presence of radioactive material within cargo containers are Radiation Portal Monitors (RPM). These devices generally exist in the form of a gate or series of gates that the containers can be driven through and scanned. The monitors are effective for determining the presence of radiation, but offer little more information about the particular source. This simple pass-fail system leads to many false alarms as many everyday items emit radiation including smoke detectors due to the Americium-241 source contained inside, bananas, milk, cocoa powder and lean beef due to the trace amounts of Potassium-40, and fire brick and kitty litter due to their high clay content which often contains traces of uranium and thorium. In addition, if an illuminating source is imposed on the boundary of the container, the contents of the container may become activated. These materials include steel, aluminum and many agricultural products. Current portal monitors also have not proven to be that effective at identifying natural or highly enriched uranium (HEU). In fact, the best available Advanced Spectroscopic Portal Monitors (ASP) are only capable of identifying bare HEU 70-88% of the time and masked HEU and depleted uranium (DU) only 53 percent of the time. Therefore, a better algorithm that uses more information collected from better detectors about the specific material distribution within the container is desired. The work reported here explores the inverse problem of optical tomography applied to heterogeneous domains. The neutral particle transport equation was used as the forward model for how neutral particles stream through and interact within these heterogeneous domains. A constrained optimization technique that uses Newtons method served as the basis of the inverse problem. Optical tomography aims at reconstructing the material properties using (a) illuminating sources and (b) detector readings. However, accurate simulations for radiation transport require that the particle (gamma and/or neutron) energy be appropriate discretize in the multigroup approximation. This, in turns, yields optical tomography problems where the number of unknowns grows (1) about quadratically with respect to the number of energy groups, G, (notably to reconstruct the scattering matrix) and (2) linearly with respect to the number of unknown material regions. As pointed out, a promising approach could rely on algorithms to appropriately select a material type per material zone rather than G2 values. This approach, though promising, still requires further investigation: (a) when switching from cross-section values unknowns to material type indices (discrete integer unknowns), integer programming techniques are needed since derivative information is no longer available; and (b) the issue of selecting the initial material zoning remains. The work reported here proposes an approach to solve the latter item, whereby a material zoning is proposed using one-group or few-groups transport approximations. The capabilities and limitations of the presented method were explored; they are briefly summarized next and later described in fuller details in the Appendices. The major factors that influenced the ability of the optimization method to reconstruct the cross sections of these domains included the locations of the sources used to illuminate the domains, the number of separate experiments used in the reconstruction, the locations where measurements were collected, the optical thickness of the domain, the amount of signal noise and signal bias applied to the measurements and the initial guess for the cross section distribution. All of these factors were explored for problems with and without scattering. Increasing the number of source and measurement locations and experiments generally was more successful at reconstructing optically thicker domains while producing less error in the image. The maximum optical thickness that could be reconstructed with this method was ten mean free paths for pure absorber and two mean free paths for scattering problems. Applying signal noise and signal bias to the measured fluxes produced more error in the produced image. Generally, Newtons method was more successful at reconstructing domains from an initial guess for the cross sections that was greater in magnitude than their true values than from an initial guess that was lower in magnitude.
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