Abstract
This study presents a detailed comparison of the dose rate distributions of a dry TN-32 fuel cask with two geometry models and two cross-sectional datasets. The accuracies of radiation dose rate estimation and computational efficiencies of each geometry model with two cross-sectional data-sets are compared. The use of automated variance reduction techniques can significantly improve the computational efficiency of such a realistic, deep penetration problem that involves radiation transport from different volumetric sources, thereby eliciting only a small statistical error. Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) is a computational sequence within the SCALE 6.2 code package based on consistent adjoint driven importance sampling (CADIS), a type of automated variance reduction technique. Homogenous and full fuel assembly models are built herein, and two nuclear cross-section libraries (V7-200N47G and continuous energy) are applied in this work. Based on the detailed comparisons, we found that neutron dose rate estimation is more dependent on geometry modeling than on cross-section data. For neutron-induced gamma rays, the dose rate distribution depends on both the spatial self-shielding effect and the cross-section library. The primary gamma rays respectively contribute to the total dose rate by ∼91% and ∼99% on the side and top surfaces, and the dose rate accuracy is more dependent on the cross-section library than on geometry modeling. In terms of the computation efficiency and efforts spent on geometry modeling, the homogenous fuel assembly model with the MG library can produce an acceptable dose rate distribution, but the detailed fuel assembly model with the continuous-energy library is required for more precise dose rate estimation.
Original language | English |
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Pages (from-to) | 84-97 |
Number of pages | 14 |
Journal | Annals of Nuclear Energy |
Volume | 117 |
DOIs | |
State | Published - Jul 2018 |
Externally published | Yes |
Funding
This publication was supported by the U.S. Department of Energy under the terms of Agreement No. DE-NE0008400. The opinions expressed herein are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy.
Funders | Funder number |
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U.S. Department of Energy | DE-NE0008400 |
Keywords
- Dry cask storage
- Monte Carlo
- Radiation shielding
- SCALE 6.2
- Spent nuclear fuel
- Variance reduction