Livestock and companion animals are valuable economically and emotionally in the economy of many states and to their citizens. In a radiological emergency situation, the loss of a large amount of livestock could be devastating to a state or national economy. If such an event occurred, there are currently no screening and decontamination protocols for the handling of livestock. This research investigated current policies and procedures for monitoring and decontamination of livestock and companion animals, as well as testing pedestrian portal monitors and a newly designed livestock portal capable of radionuclide identification. It was discovered that only ten states addressed companion animals or livestock anywhere in their emergency planning. Of the ten, only North Carolina, Washington, and a Massachusetts K9 unit had detailed decontamination procedures to report for companion animals. None of the states included detailed procedures for livestock. To address livestock screening, three pedestrian portal monitoring systems were tested in the field and lab trials – the Johnson AM801, TSA TPM903A, and Ludlum 52-1-1. The systems were tested for position and count rate sensitivity with 1 and 5 µCi 137Cs sources placed on four locations on a steer. Factors such as operability and ease of use were also considered. All three systems would alarm when a 5 µCi 137Cs source was used and the occupancy sensor was triggered. The Johnson AM801 system was determined to be the most appropriate for use in livestock screening due to sensitive alarm algorithms, greater position discrimination with four detectors, and ease of adjustment for agricultural purposes. The last phase of this project included designing and constructing a portal system that included radionuclide identification capabilities. An array of six sodium iodide detectors was mounted on a panel and field-tested beside a cattle chute and in a walkway. The custom portal, the Bovine Screening Portal (BSP), observed increased count rates (>10σ) from a 5 µCi 137Cs source in live time. The BSP demonstrated better detection and localization of the source and spectral identification capabilities compared to the commercially available pedestrian systems.

Radiation portal monitors are being deployed at border crossings throughout the world to prevent the smuggling of nuclear and radiological materials; however, a tension exists between security and the free-flow of commerce. Delays at ports-of-entry have major economic implications, so it is imperative to minimize portal monitor screening time. We have developed an algorithm to locate a radioactive source using a distributed array of detectors, specifically for use at border crossings. To locate the source, we formulated an optimization problem where the objective function describes the least-squares difference between the actual and predicted detector measurements. The predicted measurements are calculated by solving the 3-D deterministic neutron transport equation given an estimated source position. The source position is updated using the steepest descent method, where the gradient of the objective function with respect to the source position is calculated using adjoint transport calculations. If the objective function is smaller than a predetermined convergence criterion, then the source position has been identified. To test the algorithm, we first verified that the 3-D forward transport solver was working correctly by comparing to the code PARTISN (Parallel Time-Dependent SN). Then, we developed a baseline scenario to represent a typical border crossing. Test cases were run for various source positions within each vehicle and convergence criteria, which showed that the algorithm performed well in situations where we have perfect knowledge of parameters such as the material properties of the vehicles. We also ran a sensitivity analysis to determine how uncertainty in various parameters-the optical thickness of the vehicles, the fill level in the gas tank, the physical size of the vehicles, and the detector efficiencies-affects the results. We found that algorithm is most sensitive to the optical thickness of the vehicles. Finally, we tested the simplifying assumption of one energy group by using measurements obtained from MCNPX (Monte Carlo N-Particle Extended). These results showed that the one-energy-group assumption will not be sufficient if the code is deployed in a real-world scenario. While this work describes the application of the algorithm to a land border crossing, it has potential for use in a wide array of nuclear security problems.

Trafficking of radioactive material, particularly special nuclear material (SNM), has long been a worldwide concern. To interdict this material the US government has installed radiation portal monitors (RPMs) around the globe. Building materials surrounding an RPM can greatly effect the detector’s background radiation levels due to Naturally Occurring Radioactive Material (NORM). In some cases this effect is so great that the initial RPM setup had to be rebuilt. This thesis develops a methodology for quick and efficient determination of the specific activity and composition of building materials surrounding a RPM to predict background levels, therefore determining the minimum detectable quantity (MDQ) of material. This methodology builds on previous work by Ryan et al by generating material and source cards for a detailed Monte Carlo N-Particle (MCNP) deck, based on an experimental RPM setup to predict the overall gamma background at a site. Gamma spectra were acquired from samples of building materials and analyzed to determine the specific activity of the samples. A code was developed to estimate the elemental composition of building materials using the gamma transmission of the samples. These results were compared to previous Neutron Activation Analysis (NAA) on the same samples. It was determined that densitometry provided an elemental approximation within 5% of that found through NAA. Using the specific activity and material composition, an MCNP deck was used to predict the gamma background levels in the detectors of a typical RPM. These results were compared against actual measurements at the RPM site, and shown to be within 10% of each other.

A large radiological accident will result in the contamination of surrounding people, animal, vegetation etc. In such a situation assessing of the level of contamination becomes necessary to plan for the decontamination. There are plans existing for evaluating contamination on people. However, there are limited to no plans to evaluate animals. It is the responsibility of the United States Department of Agriculture (USDA) to decontaminate animals. So the objective of this thesis work was to design a scalable gamma radiation portal monitor (RPM) which can be used to assess the level of contamination on large animals like cattle. This work employed a Monte Carlo N-Particle (MCNP) radiation transport code for the purpose. A virtual system of cow, radiation source representing the contamination, cattle chute and different detector configurations were modeled. NaI scintillation detectors were modeled for this work. To find the optimal detector size and configuration, different detector orientations were simulated for different source positions using the MCNP code. Also simulations were carried out using different number and size of the detectors. It was found that using 2" x 4" x 16" detector yielded a minimum detectable activity (MDA) value of 0.4 microCi for 137Cs source.

The purpose of this project is to establish a correlation between precipitation and background gamma radiation levels at radiation portal monitors (RPM) deployed at various ports worldwide, and to devise a mechanism by which the effects of these precipitation-induced background fluctuations could be mitigated. The task of detecting special nuclear materials (SNM) by passive gamma spectroscopy is very difficult due to the low signal-to-noise ratio observed in an uncontrolled environment. Due to their low activities and the low energies of their characteristic gamma rays, the signals from many types of SNM can easily be obscured by background radiation. While this can be somewhat mitigated by taking regular background radiation measurements, even this cannot resolve the issue if background levels change suddenly and dramatically. Furthermore, any increase in background count rate will increase the statistical uncertainty of the count rate measurement, and thus decrease the minimum quantity of SNM that can be reliably detected. Existing research suggests that the advent of precipitation is the culprit behind many such large and sudden increases in background radiation. The correlation between precipitation and background levels was explored by in-situ testing on a full-scale portal monitor at Oak Ridge National Laboratory, and by comparing previously recorded background radiation and weather data from portal monitors located at ports worldwide. The first was utilized to determine the frequency and magnitude at which precipitation introduces background activity, and the second was used to quantify the effects of various quantities and types of precipitation in various parts of the world. Once this analysis was complete, various methods of mitigating these changes in background radiation were developed based on the collected data. Precipitation was found to be the most common culprit for rapid increases in background count rate, and was attributable to 85.6% of all such events. Based on extensive simulation via the Origen-ARP and MCNP software, a response function for the portal monitor was developed, and an algorithm designed to predict the contribution of the precipitation to the background count rate was developed. This algorithm was able to attenuate the contribution of precipitation to the background count rate by an average of 45% with very minimal over-correction. Such an algorithm could be utilized to adjust the alarm levels of the RPM to better allow it to compensate for the rise and fall in background count rate due to precipitation. Additionally, the relative contribution of precipitation which landed at various distances from the portal monitor to the increase in background count rate was measured via simulation. This simulation demonstrated that 37.2% of all background counts were due to the radon daughters which landed within a 2.76 m radius from the center of the portal monitor. This radius encompasses the area between the two portals. Based on this, several designs for shielding were simulated, the most successful of which was a concrete structure that was able to attenuate 71.3% of the background radiation caused by a given precipitation event at a materials cost of approximately $6,000 per RPM. This method is recommended as the primary means of mitigating this issue.

A hypothetical smuggling of material suitable for a nuclear weapon is known as a threat scenario. There is a considerable effort by the U.S. government to reduce this threat by placing radiation detectors at key interdiction points around the world. These detectors provide deterrence and defense against smuggling attempts by scanning vehicles, ships, and pedestrians for threat objects. Formulating deployment strategies for these detectors within the global transportation network requires an understanding of the complex interactions between the attributes of a smuggler and the detection systems. These strategies are rooted in the continued development of novel detection systems and alarm algorithms. Radiation transport simulation provides a means for characterizing detection system response to threat scenarios. However, this task is computationally expensive with existing radiation transport codes. Furthermore, the degrees of freedom in smuggler and threat scenario attributes create a large, constantly evolving problem space. Previous research has demonstrated that decomposing the scenario into independently simulated components using Green's functions can simulate photon detector signals with coarse energy resolution. This dissertation presents a general form of this approach, applicable to a wide range of threat scenarios through physics enhancements and numerical treatments for high energy resolution photon transport, neutron transport, and time dependent transport. While each Green's function implicitly captures the full transport phase-space within each component, these new methods ensure that this information is preserved between components. As a result, detector signals produced from full forward transport simulations can be replicated within 20% while requiring multiple orders of magnitude less computation time. This capability is presented as a general threat scenario simulation platform which can efficiently model a large problem space while preserving the full radiation transport phase-space. / text

In the event of a nuclear power plant accident, fission products could be released into the atmosphere potentially affecting the health of local citizens. In order to triage the possibly large number of people impacted, a detection device is needed that can acquire data quickly and that is sensitive to internal contamination. The portal monitor TPM-903B was investigated for use in the event of a fission product release. A list of fission products released from a Pressurized Water Reactor (PWR) was generated and separated into two groups--Group 1 (gamma- and beta-emitting fission products) and Group 2 (strictly beta-emitting fission products.) Group one fission products were used in the previously validated Monte Carlo N-Particle Transport Code (MCNP) model of the portal monitor. Two MIRD anthropomorphic phantom types were implemented in the MCNP model--the Adipose Male and Child phantoms. Dose and Risk Calculation software (DCAL) provided inhalation biokinetic data that were applied to the output of the MCNP modeling to determine the radionuclide concentrations in each organ as a function of time. For each phantom type, these data were used to determine the total body counts associated with each individual gamma-emitting fission product. Corresponding adult and child dose coefficients were implemented to determine the total body counts per 250 mSv. A weighted sum of all of the isotopes involved was performed. The ratio of dose associated with gamma-emitting fission products to the total of all fission products was determined based on corresponding dose coefficients and relative abundance. This ratio was used to project the total body counts corresponding to 250mSv for the entire fission product release inhalation--including all types of radiation. The developed procedure sheets will be used by first response personnel in the event of a fission product release.