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Title: External exposure model used in the RESRAD code for various geometries of contaminated soil.

Abstract

An external exposure model based on the US Environmental Protection Agency's (EPA's) Federal Guidance Report No. 12 (FGR-12) dose conversion factors and the point kernel method has been developed for the residual radioactive (RESRAD) material guideline computer code. This model improves the external ground pathway dose estimation from that in earlier versions of the RESRAD code by extending FGR-12 data applicability to a wider range of source geometries. FGR-12 assumes that sources are infinite in lateral extent. In actual situations, soil contamination sources can have any depth, shape, cover, and size. A depth factor function was developed to express the attenuation of radionuclides by using regression analysis. Three independent, nuclei-specific parameters were determined by using the effective dose equivalent values from FGR-12. The depth factors derived with the new model were within 2% of the FGR-12 values for all depths for most of the radionuclides. A cover-and-depth factor function was derived on the basis of the depth factor function by considering both dose contribution and attenuation from different depths. The cover-and-depth factor was compared with FGR-12 computations for some representative radionuclides and source configurations. For thin cover thicknesses (1 cm), most of the values were within 2%; even for largemore » cover thicknesses (5 to 15 cm), most of the values were within 10%. To further extend this model for actual geometries (finite irregular areas), area and shape factors were derived by using the point kernel method. These factors depend not only on the lateral extent of the contamination but also on source depth, cover thickness, and gamma energies. The area factor increases with source radius and approaches unity for source radii greater than 50 m. To test the integrity of FGR-12 data, effective dose equivalent values at the surface and four soil depths were compared with the Monte Carlo N-Particle (MCNP) transport code calculations for a few radionuclides. MCNP values were within 10% of the FGR values for the four soil depths. Depth and cover factors were also compared with MCNP calculations. Finally, overall comparisons were made between the new RESRAD model (Versions 5.60 and later) and the old RESRAD model (Version 5.44 and earlier).« less

Authors:
; ;
Publication Date:
Research Org.:
Argonne National Lab., IL (US)
Sponsoring Org.:
US Department of Energy (US)
OSTI Identifier:
12038
Report Number(s):
ANL/EAD/TM-84
TRN: AH200119%%241
DOE Contract Number:  
W-31109-ENG-38
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 18 Nov 1998
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; ATTENUATION; COMPUTER CODES; CONTAMINATION; DOSE EQUIVALENTS; POINT KERNELS; RADIOISOTOPES; RECOMMENDATIONS; REGRESSION ANALYSIS; SHAPE; SOILS

Citation Formats

Kamboj, S, LePoire, D J, and Yu, C. External exposure model used in the RESRAD code for various geometries of contaminated soil.. United States: N. p., 1998. Web. doi:10.2172/12038.
Kamboj, S, LePoire, D J, & Yu, C. External exposure model used in the RESRAD code for various geometries of contaminated soil.. United States. doi:10.2172/12038.
Kamboj, S, LePoire, D J, and Yu, C. Wed . "External exposure model used in the RESRAD code for various geometries of contaminated soil.". United States. doi:10.2172/12038. https://www.osti.gov/servlets/purl/12038.
@article{osti_12038,
title = {External exposure model used in the RESRAD code for various geometries of contaminated soil.},
author = {Kamboj, S and LePoire, D J and Yu, C},
abstractNote = {An external exposure model based on the US Environmental Protection Agency's (EPA's) Federal Guidance Report No. 12 (FGR-12) dose conversion factors and the point kernel method has been developed for the residual radioactive (RESRAD) material guideline computer code. This model improves the external ground pathway dose estimation from that in earlier versions of the RESRAD code by extending FGR-12 data applicability to a wider range of source geometries. FGR-12 assumes that sources are infinite in lateral extent. In actual situations, soil contamination sources can have any depth, shape, cover, and size. A depth factor function was developed to express the attenuation of radionuclides by using regression analysis. Three independent, nuclei-specific parameters were determined by using the effective dose equivalent values from FGR-12. The depth factors derived with the new model were within 2% of the FGR-12 values for all depths for most of the radionuclides. A cover-and-depth factor function was derived on the basis of the depth factor function by considering both dose contribution and attenuation from different depths. The cover-and-depth factor was compared with FGR-12 computations for some representative radionuclides and source configurations. For thin cover thicknesses (1 cm), most of the values were within 2%; even for large cover thicknesses (5 to 15 cm), most of the values were within 10%. To further extend this model for actual geometries (finite irregular areas), area and shape factors were derived by using the point kernel method. These factors depend not only on the lateral extent of the contamination but also on source depth, cover thickness, and gamma energies. The area factor increases with source radius and approaches unity for source radii greater than 50 m. To test the integrity of FGR-12 data, effective dose equivalent values at the surface and four soil depths were compared with the Monte Carlo N-Particle (MCNP) transport code calculations for a few radionuclides. MCNP values were within 10% of the FGR values for the four soil depths. Depth and cover factors were also compared with MCNP calculations. Finally, overall comparisons were made between the new RESRAD model (Versions 5.60 and later) and the old RESRAD model (Version 5.44 and earlier).},
doi = {10.2172/12038},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1998},
month = {11}
}

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