Issue |
Radioprotection
Volume 59, Number 4, October - December 2024
|
|
---|---|---|
Page(s) | 296 - 305 | |
DOI | https://doi.org/10.1051/radiopro/2024030 | |
Published online | 13 December 2024 |
Article
Voxel-based Monte Carlo simulation of human external exposure to terrestrial gamma radiation
1
Faculty of Sciences of Tunis, University of Tunis El Manar, 2092 Tunis, Tunisia
2
Research Laboratory on Energy and Matter for Nuclear Science Development (LR16CNSTN02), National Center for Nuclear Science and Technologies, Sidi Thabet Technopark 2020, Tunis, Tunisia
3
National Center for Nuclear Science and Technologies, Sidi Thabet Technopark 2020, Tunis, Tunisia
* Corresponding author: boubaker.askri@cnstn.rnrt.tn
Received:
13
March
2024
Accepted:
31
July
2024
Organ absorbed doses are calculated for human exposure to terrestrial gamma radiation using a two-stage voxel-based Monte Carlo simulation in which the human body is represented by the voxel ICRP110 phantoms integrated in the Geant4 Monte Carlo code. The transport of photons in the soil-air medium is optimised by using a proven optimised geometry that allows tracking only those photons that have a high chance of reaching the standing reference phantom on the ground. For an optimal tracking within the voxel phantom, a nested parameterisation navigation technique implemented in Geant4 is applied. The organ-absorbed doses and the correspondent effective dose are calculated for the natural radioactive series of 238U and 232Th and for the 40K and 137Cs radionuclides. The results are compared to published studies that used the less precise mathematical based MIRD phantoms and to results derived from the ICRP144 report using the most advanced voxel phantom. The degree of agreement and the source of discrepancy between the realistic voxel model of the human body and the mathematical model used in the literature are analysed.
Key words: voxel phantom / Monte Carlo / radioactive series / organ dose conversion factors
© A. Bouzouita et al., Published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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