After a Radiological Dispersal Device (RDD) event, there will not be time to transport people to a whole-body-counter (WBC), since it is a specialized instrument. This work will assess the feasibility of using handheld spectrometers for measuring the radioactivity that may have been inhaled by a victim as a consequence of an RDD event. Measurements were made with a handheld isotope identifier using a slab phantom and several radioactive point sources. A Lawrence Livermore National Laboratory (LLNL) Realistic Torso Phantom and a set of phantoms based on Medical Internal Radiation Dose (MIRD) reports were also used in this work. These phantoms include the human skeleton and have tissue-equivalent organs. Computational models were developed of all of the phantoms using the Monte Carlo Transport code MCNP. After validation of the computer model, MCNP runs were conducted using other sources that are likely to be used in a RDD. Calculations were then done to find the Minimum Detectable Activity (MDA) of all sources used. The Minimum Detectable Dose (MDD) was then calculated for the MIRD phantoms at various times after inhalation.

A Radiological Dispersal Device (RDD) is any device that releases radioactive material into the environment (e.g. Dirty Bomb). Depending on the size of the explosion, location, and the weather conditions the affected area could be several city blocks. In such an event there could be hundreds, even thousands of contaminated victims seeking medical treatment. One concern in the healthcare industry is the uncertainty of the level of radiation exposure to the healthcare providers from these contaminated patients. The intention of this study is to estimate the levels of skin contamination for victims arriving at the hospital needing conventional medical treatment. Given a skin contamination of the victim the effective dose rate to the healthcare providers can be estimated in certain scenarios. The effective dose rate will determine how long the healthcare provider would be able to care for the victims.

As radiation specialists, one of our primary objectives in the Navy is protecting people and the environment from the effects of ionizing and non-ionizing radiation. Focusing on radiological dispersal devices (RDD) will provide increased personnel protection as well as optimize emergency response assets for the general public. An attack involving an RDD has been of particular concern because it is intended to spread contamination over a wide area and cause massive panic within the general population. A rapid method of triage will be necessary to segregate the unexposed and slightly exposed from those needing immediate medical treatment. Because of the aerosol dispersal of the radioactive material, inhalation of the radioactive material may be the primary exposure route. The primary radionuclides likely to be used in a RDD attack are Co-60, Cs-137, Ir-192, Sr-90 and Am-241. Through the use of a MAX phantom along with a few Simulink MATLAB programs, a good anthropomorphic phantom was created for use in MCNPX simulations that would provide organ doses from internally deposited radionuclides. Ludlum model 44-9 and 44-2 detectors were used to verify the simulated dose from the MCNPX code. Based on the results, acute dose rate limits were developed for emergency response personnel that would assist in patient triage.

It remains unlikely that a terrorist organization could produce or procure an actual nuclear weapon. However, the construction of a radiological dispersal device (RDD) from commercially produced radioactive sources and conventional explosives could inflict moderate human casualties and significant economic damage. The vast availability of radioactive sources and the nearly limitless methods of dispersing them demand an inclusive study of the acquisition pathways for an RDD. A complete network depicting the possible acquisition pathways for an RDD could be subjected to predictive modeling in order to determine the most likely pathway an adversary might take. In this work, a comprehensive network of RDD acquisition pathways was developed and analyzed utilizing the Bayesian network analysis software, Netica. The network includes variable inputs and motivations that can be adjusted to model different adversaries. Also, the inclusion of evidence nodes facilitates the integration of real-time intelligence with RDD plot predictions. A sensitivity analysis was first performed to determine which nodes had the greatest impact on successful completion of RDD acquisition. These results detail which portions of the acquisition pathways are most vulnerable to law enforcement intervention. Next, a series of case studies was analyzed that modeled specific adversarial organizations. The analysis demonstrates various features of the constructed Bayesian RDD acquisition network and provides examples of how this tool can be utilized by intelligence analysts and law enforcement agencies. Finally, extreme cases were studied in which the adversary was given the maximum and minimum amount of resources in order to determine the limitations of this model. The aggregated results show that successful RDD acquisition is mostly dependent on the adversary’s resources. Furthermore, the network suggests that securing radiological materials has the greatest effect on interdicting possible RDD plots. Limitations of this work include a heavy dependence on conditional probabilities that were derived from intuition, as opposed to actual historical data which does not exist. However, the model can be updated as attempted or successful RDD plots emerge in the future. This work presents the first probabilistic model of RDD acquisition pathways that integrates adversary motivations and resources with evidence of specific RDD threats.

In the event that a radiological dispersal device (RDD) is detonated in the U.S. or near U.S. interests overseas, it will be crucial that the actors involved in the event can be identified quickly. If irradiated nuclear fuel is used as the dispersion material for the RDD, it will be beneficial for law enforcement officials to quickly identify where the irradiated nuclear fuel originated. One signature which may lead to the identification of the spent fuel origin is the isotopic composition of the RDD debris. The objective of this research was to benchmark a forward model methodology for predicting isotopic composition of spent nuclear fuel used in an RDD while at the same time optimizing the fidelity of the model to reduce computational time. The code used in this study was Monteburns-2.0. Monteburns is a Monte Carlo based neutronic code utilizing both MCNP and ORIGEN. The size of the burnup step used in Monteburns was tested and found to converge at a value of 3,000 MWd/MTU per step. To ensure a conservative answer, 2,500 MWd/MTU per step was used for the benchmarking process. The model fidelity ranged from the following: 2-dimensional pin cell, multiple radial-region pin cell, modified pin cell, 2D assembly, and 3D assembly. The results showed that while the multi-region pin cell gave the highest level of accuracy, the difference in uncertainty between it and the 2D pin cell (0.07% for 235U) did not warrant the additional computational time required. The computational time for the multiple radial-region pin cell was 7 times that of the 2D pin cell. For this reason, the 2D pin cell was used to benchmark the isotopics with data from other reactors. The reactors from which the methodology was benchmarked were Calvert Cliffs Unit #1, Takahama Unit #3, and Trino Vercelles. Calvert Cliffs is a pressurized water reactor (PWR) using Combustion Engineering 14??14 assemblies. Takahama is a PWR using Mitsubishi Heavy Industries 17??17 assemblies. Trino Vercelles is a PWR using non-standard lattice assemblies. The measured isotopic concentrations from all three of the reactors showed good agreement with the calculated values.

Numerous scenarios exist whereby radioactive particulates are transported between spatially separated points of interest. An example of this phenomenon is, in the aftermath of a Radiological Dispersal Device (RDD) detonation, the resuspension of radioactive particulates from the resultant fallout field. Quantifying the spatial distribution of radioactive particulates allow for the calculation of potential radiation doses that can be incurred from exposure to such particulates. Presently, there are no simulation techniques that link radioactive particulate transport with subsequent radiation field determination and so this thesis develops a coupled Computational Fluid Dynamics (CFD) and Monte Carlo (MC) Radiation Transport approach to this problem. Via particulate injections, the CFD simulation defines the spatial distribution of radioactive particulates and this distribution is then employed by the MC Radiation Transport simulation to characterize the resultant radiation field. GAMBIT/FLUENT are employed for the CFD simulations while MCNPX is used for the MC Radiation Transport simulations. / UOIT

This research investigates the use of G-M counters to triage the individuals who have been exposed to a Radiological Dispersal Device (RDD). Upon being exposed to an RDD, inhalation of the airborne radionuclide is a method which someone can receive a considerable amount of dose. Bioassay via analysis of excreta is a commonly used method of determining the dose received, yet it would be cumbersome if there are a large number of people needing to be screened. An in vivo method must be considered so that a non-intrusive and more efficient triaging method can be implemented. Whole body counters are commonly used in counting facilities as an in vivo bioassay method, yet they are limited in number and not easily portable. Therefore, a more portable and more common detection device should be considered. G-M survey meters are common devices that are highly portable, making them ideal candidates to fulfill this necessity. The ease of use contributes to the viability of the device as a portable, in vivo screening device. To analyze this detector, a Monte Carlo model of the detector was created to be used in simulations with the Medical Internal Radiation Dose phantoms. The detector was placed in a few locations on the phantoms. Four locations were strategically chosen for detector placement: the posterior upper right torso, the anterior upper right torso, the lateral upper thigh, and the anterior of the neck. Six phantoms were considered: Reference Male, Female, Adipose Male, Adipose Female, Post Menopausal Adipose Female, and a Child. Six radionuclides were investigated: Am-241, Co-60, Cs-137, I-131, Ir-192, and Sr-90. The nuclides were distributed throughout the phantoms according to Dose and Risk Calculation Software, a code that determines how a radionuclide is distributed over time upon inhalation, ingestion, or injection. A set of time dependent guidelines were developed, determining the count rate per unit dose inhaled for each detector location and phantom type.

The detonation of a radiological dispersion device (RDD) may result in a situation where many individuals are exposed to contamination due to the inhalation of radioactive materials. Assessments of contamination may need to be performed by emergency response personnel in order to triage the potentially exposed public. The feasibility of using readily available standard 2x2-inch sodium-iodide detectors to determine the committed effective dose to a patient following the inhalation of a radionuclide has been investigated. The 2x2-NaI(Tl) detector was modeled using the Monte Carlo simulation code, MCNP-5, and was validated via a series of experimental benchmark measurements using a polymethyl methacrylate (PMMA) slab phantom. Such validation was essential in reproducing an accurate detector response. Upon verification of the detector model, six anthropomorphic phantoms, based on the MIRD-V phantoms, were modeled with nuclides distributed to simulate inhaled contamination. The nuclides assessed included Am-241, Co-60, Cs-137, I-131, and Ir-192. Detectors were placed at four positions on the phantoms: anterior right torso, posterior right torso, anterior neck, and lateral left thigh. The detected count-rate varied with respect to detector position, and the optimal detector location was determined on the body. The triage threshold for contamination was set at an action level of 250-mSv of intake. Time dependent biokinetic modeling was employed to determine the source distribution and activity in the body as a function of post-inhalation time. The detector response was determined as a function of count-rate per becquerel of activity at initial intake. This was converted to count-rate per 250-mSv intake for triage use by first responders operating the detector to facilitate triage decisions of contamination level. A set of procedure sheets for use by first responders was compiled for each of the phantoms and nuclides investigated.