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Securing radioactive sources has become increasingly important given the rising threat of radiological terrorism. While radiation safety has long been established in most applicable industries, the importance of nuclear and radiological source security has lagged behind in nonnuclear material specific industries, such as academic institutions and medical facilities. To evaluate the attitudes and behaviors regarding nuclear security culture, an assessment of nuclear and radiological material practices was developed and conducted on 73 radioactive material users at a university. The survey portion of the assessment was comprised of a series of questions segregated into four categories: policy, enforcement, leadership, and behavior. Nuclear security awareness questions formed a subset of the questionnaire. Users were classified by their radioactive material experience and work classification: student, faculty, or other staff. Of the users surveyed, 9% were also interviewed face-to-face to further expand on their views of nuclear security culture. Results of the assessment showed that students from the work classification group as well as the cohort of radioactive material users with 2-5 y of experience possessed a greater degree of awareness towards nuclear security compared to faculty and other more experienced radioactive material users. Relative to students and faculty, other staff from the work classification group faced some difficulty judging the enforcement of policies, adequacy of inspection, and job performance review related to nuclear security. The response from all three groups emphasized the need to enhance threat-response preparedness and greater communication among stakeholders.

Here, excavations of radiological material were performed within confined structures with known operational parameters, such as a filtered exhaust system with known filtration efficiency. Given the known efficiency, the assumption could be made that the air concentrations of radioactivity measured outside the structure would be proportional to the air concentrations measured inside the structure. To investigate this assumption, the inside concentration data was compared with the outside concentration data. The correlation of the data suggested that the inside concentrations were not a good predictor of the outside concentrations. This poor correlation was deemed to be a result of operational unknowns within the structures.

The purpose of this study was to measure mass and activity distributions from the aerosols generated during the demolition of surface contaminated concrete. Air samples were collected using a cascade impactor during the mechanical hammering and dismantlement of radiologically contaminated high level waste process vaults from which the piping and components had been previously removed. The experimentally determined distribution parameters were compared with the 5.0-μm particle size referenced in the U.S. Department of Energy (U.S. DOE) regulations pertaining to internal deposition (10CFR835 and ICRP66). Mass distribution parameters were compared with their activity distribution counterparts. The Mass Median Aerodynamic Diameter (MMAD) was determined to be 4.2 μm with a Mass Geometric Standard Deviation (GSDM) of 2.3 μm, and the Co Activity Median Aerodynamic Diameter (AMAD) was determined to be 3.9 μm with an Activity Geometric Standard Deviation (GSDA) of 2.3 μm. These results are consistent with the ICRP66 5.0-μm reference particle size and the Derived Air Concentration (DAC) values referenced in 10CFR835 and utilized throughout the U.S. DOE complex.

Commercial nuclear power plants release gaseous and liquid radiological effluents into the environment as by-products of electrical generation. In the U.S. these releases are monitored by the Nuclear Regulatory Commission (U.S. NRC) and Environmental Protection Agency (U.S. EPA). Traditionally these releases have always been well below the regulatory limits. However, the tracking and analysis of nuclear power radiological effluents was stopped in 1994 by several government agencies. The purpose of this study was to compile the entire U.S. industry effluent data, identify trends, and calculate average population dose commitments since that time. Data were taken from radioactive material release reports submitted by each nuclear power plant. Industry trends were identified using the Mann-Kendall non-parametric test. Total collective effective and population doses were estimated using UNSCEAR and U.S. NRC methodologies. Overall, industry releases have been level over the study time period. Public doses continue to be well below 1% of the regulatory limits.

A new computational model has been developed using the Monte Carlo (MC) technique to simulate in vivo measurements with the objective of understanding the most precise measurement location with respect to quantifying the activity of Am in the bones. To benchmark the model, in vivo measurements were performed on the U.S. Transuranium and Uranium Registries (USTUR) case 0846 leg. Front and lateral measurements of the knee of the USTUR case 0846 leg in a bent position and the same measurements with the leg in a straight position using a HP(Ge) detector were completed. Experimental results concluded that the front measurement of the knee in a bent leg position gave the highest count rate, which is an indication of optimal detection efficiency. Therefore, this geometry and knee-detector position were considered as the most appropriate position for knee monitoring. A computational model using MCNPX version 2.6.0 was used to simulate the experimental measurements by using a leg voxel phantom. The mean value and standard deviation (SD) of peak efficiency due to an isotropic 59.5-keV photon from Am were calculated in four different counting geometries. An extra sum of squares F-test was performed on the mean values of the simulated detection efficiencies. The p-value obtained from this statistical test indicates that the differences among the mean values for different counting geometries were significant. These results suggest that the front measurement of a knee in a bent leg position is the optimal counting geometry for in vivo measurement of Am deposited in the bones. The computational model was validated through comparison of the measured and simulated detection efficiencies. It was observed that there is no difference at the 0.1 significant levels between the simulated and measured detection efficiencies in assessment of Am within the bones.