Radiological Assessments for Clearance ofMaterials from Nuclear Facilities: Appendices H–O (NUREG-1640, Volume 4)

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Publication Information

Manuscript Completed: June 2003
Date Published: June 2003

Prepared by:
R. Anigstein,* H.J. Chmelynski,* D.A. Loomis,* S.F. Marschke,** J.J. Mauro,* R.H. Olsher,* W.C. Thurber,* and R.A. Meck

*SC&A, Inc.
6858 Old Dominion Drive, Suite 301
McLean, VA 22101

**Gemini Consulting Company
19 River Run Way
Oak Ridge, TN 38730

Division of Systems Analysis and Regulatory Effectiveness
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

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Abstract

This report provides a complete description of calculations and their results estimating potential annual doses, normalized to a unit concentration, to an individual following the clearance of specific materials. These materials are scrap iron and steel, copper, aluminum, and concrete rubble from licensed nuclear facilities. Clearance means the removal of radiological controls by the licensing authority. The estimated potential doses are calculated probabilistically to account for a large number of possible variations in each of the 86 scenarios. These scenarios encompass the full range of realistic situations likely to yield the greatest normalized doses. Each scenario was analyzed with the 115 radionuclides considered most likely to be associated with materials from licensed nuclear facilities. The design basis of the analyses is to realistically model current processes, to identify critical groups on a nuclide-by-nuclide basis, and to enable the conversion of a dose criterion to a concentration.

Material for recycle or disposal was evaluated using material flow models and dose assessment models. Both models are based on probabilistic methods. This resulted in distributions of nuclide-by-nuclide normalized doses from one year of exposure per mass- or surface-based concentrations. The means and the 5th, 50th, 90th, and 95th percentiles are reported. These percentiles can be used to generically evaluate the likelihood that the derived mean concentration would correspond to a particular dose criterion. Additionally, they can be used to quantify the confidence that a safety goal is not exceeded.