Probabilistic Modules for the RESRAD and RESRAD-BUILD Computer Codes: User Guide (NUREG/CR-6692)

On this page:

• Publication Information
• Abstract

Download complete document

• NUREG/CR-6692 (PDF - 4.76 MB)

Publication Information

Manuscript Completed: October 2000
Date Published: November 2000

Prepared by:
D. LePoire, J. Amish, E. Gnanapragasam, S. Kamboj,
B.M. Biwer, J.-J. Cheng, 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 Applications
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

NRC Job Code Y6112

Availability Notice

Abstract

RESRAD and RESRAD-BUILD codes are part of the RESRAD family of codes developed by the U.S. Department of Energy. For many years these deterministic codes have been used as dose assessment tools for cleanup efforts at sites contaminated with radioactive materials. The RESRAD code applies to the cleanup of soil, and the RESRAD-BUILD code applies to the cleanup of buildings and structures.

RESRAD and RESRAD-BUILD codes are part of the RESRAD family of codes developed by the U.S. Department of Energy. For many years these deterministic codes have been used as dose assessment tools for cleanup efforts at sites contaminated with radioactive materials. The RESRAD code applies to the cleanup of soil, and the RESRAD-BUILD code applies to the cleanup of buildings and structures.

This report includes a user's guide for the probabilistic modules included in RESRAD version 6.0 and RESRAD-BUILD version 3.0. It should be used in conjunction with the technical reference manuals for the deterministic RESRAD and RESRAD-BUILD codes (Yu et al., 1993, 1994, respectively, or future updates of these manuals). These manuals describe the technical basis (models and methods) and the input parameters for the models. This report also includes background information and summaries of the previous tasks accomplished in this project, a description of the software design and requirements, and description of a sample case for probabilistic dose analysis. A detailed discussion of the Latin hypercube sampling method, a summary of parameter distributions, and a "guided tour" that demonstrates the use of the probabilistic modules are included in the appendices.