Probabilistic Dose Analysis Using Parameter Distributions Developed for RESRAD and RESRAD-BUILD Codes (NUREG/CR-6676)

NRC Report Number: NUREG/CR-6676

Availability Notice

Manuscript Completed: May 2000

Date Published: July 2000

Prepared by
S. Kamboj, D. LePoire, E. Gnanapragasam,
B.M Biwer, J. Cheng, J. Arnish, C. Yu, S. Y. Chen

Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439

T. Mo, NRC Project Manager

Prepared for
Division of Risk Analysis and Application
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

NRC Job Code Y6112



The existing RESRAD 6.0 and RESRAD-BUILD 3.0 codes for site-specific radiation dose modeling applications are being developed and adapted for use with the U.S. Nuclear Regulatory Commission's (NRC's) Standard Review Plan for decommissioning and as tools for demonstrating compliance with the license termination rule in a risk-informed manner. Computer interfaces and software modules have been developed under NRC sponsorship to perform the probabilistic simulation of dose. RESRAD and RESRAD-BUILD are part of the RESRAD family of codes that have been developed by the U.S. Department of Energy (DOE) and for many years have been successfully applied to cleanup efforts at sites contaminated with radioactive materials. Specifically, the RESRAD code applies to cleanup of soil, and RESRAD-BUILD applies to the cleanup of buildings and structures at a site. This report describes the use of these codes to perform probabilistic dose analysis. The dose analysis presented in this report has fully demonstrated the process of using the integrated system of RESRAD 6.0 and RESRAD-BUILD 3.0 codes and the probabilistic modules, together with distributions of input parameters, for dose assessment at a relatively complex site. This demonstration enables site-specific application of the codes for dose analysis where pertinent parameters and their distributions are available or can be developed. Results of the uncertainty analysis and sensitivity analysis of dose to input parameter values indicated that because the dependence of dose on the input parameters is complex, no single correlation or regression coefficient can be used alone to identify sensitive parameters in all cases. However, the results could give an indication of the degree of sensitivity of the calculated dose to changes in input parameter values for each exposure situation. Therefore, the coefficients are useful guides, but they have to be used in conjunction with the other aids, such as scatter plots and further analysis, to accurately identify the sensitive parameters.