Doctor of Philosophy / Department of Mechanical and Nuclear Engineering / William L. Dunn / The signature-based radiation scanning (SBRS) technique can be used to rapidly detect nitrogen-rich explosives at standoff distances. This technique uses a template-matching procedure that produces a figure-of-merit (FOM) whose value is used to distinguish between inert and explosive materials. The present study develops a tiered-filter implementation of the signature-based radiation scanning technique, which reduces the number of templates needed. This approach starts by calculating a normalized FOM between signatures from an unknown target and an explosive template through stages or tiers (nitrogen first, then oxygen, then carbon, and finally hydrogen). If the normalized FOM is greater than a specified cut-off value for any of the tiers, the target signatures are considered not to match that specific template and the process is repeated for the next explosive template until all of the relevant templates have been considered. If a target’s signatures match all the tiers of a single template, then the target is assumed to contain an explosive. The tiered filter approach uses eight elements to construct artificial explosive-templates that have the function of representing explosives cluttered with real materials. The feasibility of the artificial template approach to systematically build a library of templates that successfully differentiates explosive targets from inert ones in the presence of clutter and under different geometric configurations was explored. In total, 10 different geometric configurations were simulated and analyzed using the MCNP5 code. For each configuration, 51 different inert materials were used as inert samples and as clutter in front of the explosive cyclonite (RDX). The geometric configurations consisted of different explosive volumes, clutter thicknesses, and distances of the clutter from the neutron source. Additionally, an objective function was developed to optimize the parameters that maximize the sensitivity and specificity of the method.

Every year, the ports of entry of the continental United States receive millions of containers from container ships for processing. These containers contain everything that the country imports, and sometimes regulated items can be hidden inside them in attempt to smuggle them illegally into the country. Some of these items may be radioactive material meant for criminal purposes and represent a threat to national security. The containers are currently being scanned for radioactivity as they leave the port, but before leaving the port, containers can sit inside the port for weeks. It can be beneficial to scan these containers before they are picked up to catch the illegal material sooner and reduce the risk of danger to those nearby. Uncrewed Aerial Systems can be useful for scanning container stacks in container fields since they can be attached with sensors and reach heights that are difficult for humans. They can also scan autonomously, requiring less over watch from people. This thesis attempts to solve the problem of autonomous search by using an initial 3D scan of the search area to input into a 3D path planning algorithm to generate a flight path that will sufficiently scan the search area while minimizing flight time. Coverage is a main area of concern, as well is computational complexity and time. In order to maintain security of the aircraft, the path must be generated on-board the aircraft, and as such use on-board, lightweight, computers. The approach taken in this thesis is by breaking the problem down into 2D layers, and then developing paths on each layer based on where the obstacles are. In order to maximize coverage, contours are generated around the obstacles. The vertices of the contours are then treated like points to visit in a Travelling Salesman Problem. To incentivize paths that run alongside the obstacles for better radiation detection, paths that do not run close to the obstacles are given a higher cost than those that do, resulting in a cost-minimizing path planning algorithm yielding paths that stay close to obstacles. The Travelling Salesman Problem algorithm then yields the most time effective path to cover the area while maintaining a distance healthy for radiation scanning from the obstacles. / Master of Science / Every year, the ports of entry of the continental United States receive millions of containers from container ships for processing. These containers contain everything that the country imports, and sometimes regulated items can be hidden inside them in attempt to smuggle them illegally into the country. Some of these items may be radioactive material meant for criminal purposes and represent a threat to national security. It can be beneficial to scan these containers before they are picked up to catch the illegal material sooner and reduce the risk of danger to those nearby. Uncrewed Aerial Systems can be useful for scanning container stacks in container fields since they can be attached with sensors and reach heights that are difficult for humans. They can also scan autonomously, requiring less over watch from people. This thesis attempts to solve the problem of autonomous search by using an initial 3D scan of the search area to input into a 3D path planning algorithm to sufficiently scan the search area while minimizing flight time.

Master of Science / Department of Mechanical and Nuclear Engineering / William L. Dunn / The signature-based radiation-scanning (SBRS) technique relies on radiation detector responses, called “signatures,” and compares them to “templates”, to differentiate targets containing nitrogen-rich explosives from those that do not. This investigation utilizes nine signatures due to inelastic-scatter and prompt-capture gamma rays from hydrogen, carbon, nitrogen, and oxygen (HCNO) as well as two neutron signatures, produced when a target is interrogated with a 14.1 MeV neutron source beam. One hundred and forty three simulated experiments were conducted using MCNP5. Signatures of 42 targets containing explosive samples (21 of RDX and 21 of Urea Nitrate), and 21 containing inert samples were compared with the signatures of 80 artificial templates through figure-of-merit analysis. A density filter, comparing targets with templates of similar average density was investigated. Both high and low-density explosives (RDX-1.8 g cm-3 and Urea Nitrate-0.69 g cm-3) were shown to be differentiated from inert materials through use of neutron and gamma-ray signature templates with sensitivity of 90.5% and specificity of 76.2%. Density Groups were identified, in which neutron signature templates, gamma-ray signature templates or the combination of neutron and gamma-ray signature templates were capable of improving inert-explosive differentiation. figure-of -merit analysis, employing the best Density Group specific templates, differentiated explosive from inert targets with 90.5% sensitivity and specificity of over 85%.