This report analyzes the impact of some important factors on the prediction of detection probabilities for radiation portal monitors (RPMs). The application of innovative detection technology to improve operational sensitivity of RPMs has received increasing attention in recent decades. In particular, two alarm algorithms, gross count and energy windowing, have been developed to try to distinguish between special nuclear material (SNM) and naturally occurring radioactive material (NORM). However, the use of the two detection strategies is quite limited due to a very large number of unpredictable threat scenarios. We address this problem by implementing a new Monte Carlo radiation transport simulation approach to model a large set of threat scenarios with predefined conditions. In this report, our attention is focused on the effect of two important factors on the detected energy spectra in RPMs, the mass of individual nuclear isotopes and the thickness of shielding materials. To study the relationship between these factors and the resulting spectra, we apply several advanced statistical regression models for different types of data, including a multinomial logit model, an ordinal logit model, and a curvilinear regression model. By utilizing our new simulation technique together with these sophisticated regression models, we achieve a better understanding of the system response under various conditions. We find that the different masses of the isotopes change the isotopes’ effect on the energy spectra. In analyzing the joint impact of isotopes’ mass and shielding thickness, we obtain a nonlinear relation between the two factors and the gross count of gamma photons in the energy spectrum. / text

The dissolution of the Soviet Union coupled with the growing sophistication of international terror organizations has brought about a desire to ensure that a sound infrastructure exists to interdict smuggled nuclear material prior to leaving its country of origin. To combat the threat of nuclear trafficking, radiation portal monitors (RPMs) are deployed around the world to intercept illicit material while in transit by passively detecting gamma and neutron radiation. Portal monitors in some locations have reported abnormally high gamma background count rates. The higher background data has been attributed, in part, to the concrete surrounding the portal monitors. Higher background can ultimately lead to more material passing through the RPMs undetected. This work is focused on understanding the influence of the concrete surrounding the monitors on the total gamma ray background for the system. This research employed a combination of destructive and nondestructive analytical techniques with computer simulations to form a model that may be adapted to any RPM configuration. Six samples were taken from three different composition concrete slabs. The natural radiologcal background of these samples was determined using a high-purity germanium (HPGe) detector in conjunction with the Canberra In-Situ Object Counting System (ISOCS™) and Genie™ 2000 software packages. The composition of each sample was determined using thermal and fast neutron activation analysis (NAA) techniques. The results from these experiments were incorporated into a Monte Carlo N-Particle (MNCP) photon transport simulation to determine the expected gamma ray count rate in the RPM due to the concrete. The results indicate that a quantitative estimate may be possible if the experimental conditions are optimized to eliminate sources of uncertainty. Comparisons of actual and simulated count rate data for 137Cs check sources showed that the model was accurate to within 15%. A comparison of estimated and simulated count rates in one concrete slab showed that the model was accurate to within 4%. Subsequent sensitivity analysis showed that if the elemental concentrations are well known, the carbon and hydrogen content could be easily estimated. Another sensitivity analysis revealed that the small fluctuations in density have a minimal impact on the gamma count rate. The research described by this thesis provides a method by which RPM end users may quantitatively estimate the expected gamma background from concrete foundations beneath the systems. This allows customers to adjust alarm thresholds to compensate for the elevated background due to the concrete, thereby increasing the probability of intercepting illicit radiological and nuclear material.

In the event of a radioactive dispersal device (RDD), the assessment of the internal contamination level of victims is necessary to determine if immediate medical follow-up is necessary. Thermo Scientific's TPM-903B Portal Monitor was investigated to determine if it is a suitable first cut screening tool for internal contamination assessment of victims. A portal monitor was chosen for this study because they are readily accessible, transportable, easy to assemble, and provide whole body count rates due to the detector size. The TPM-903B was modeled in Monte Carlo N-Particles Transport Code Version 5 (MCNP). This computational model was validated against the portal monitor's response to a series of measurements made with four point sources in a polymethyl methacrylate (PMMA) slab box. Using the validated MCNP5 model and models of the MIRD male and female anthropomorphic phantoms, the response of the portal monitor was simulated for the inhalation and ingestion radionuclides from an RDD. Six representative phantoms were considered: Reference Male, Reference Female, Adipose Male, Adipose Female, Post-Menopausal Adipose Female, and 10-Year-Old Child. The biokinetics via Dose and Risk Calculation Software (DCAL) was implemented using both the inhalation and ingestion pathways to determine the radionuclide concentrations in the organs of the body which were then used to determine the count rate of the portal monitor as a function of time. Dose coefficients were employed to determine the count rate of the detector associated with specific dose limits. These count rates were then compiled into procedure sheets to be used by first responders during the triaging of victims following an RDD.