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The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Latest News
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Y. F. Chen, R. J. Sheu, S. H. Jiang, J. N. Wang, U. T. Lin
Nuclear Technology | Volume 175 | Number 1 | July 2011 | Pages 343-350
Technical Paper | Special Issue on the 16th Biennial Topical Meeting of the Radiation Protection and Shielding Division / Radiation Transport and Protection | doi.org/10.13182/NT11-A12306
Articles are hosted by Taylor and Francis Online.
Based on the Consistent Adjoint Driven Importance Sampling (CADIS) methodology, MAVRIC is a new computational sequence in the SCALE6 code package that is designed to perform efficient Monte Carlo simulation for a complicated and difficult shielding problem. This study aimed to evaluate the performance of MAVRIC with the latest cross-section library in calculating the surface dose rates of a realistic spent-fuel storage cask. Detailed dose rate profiles over the cask side and top surfaces were calculated, and the results were compared with our previous work using SAS4 and MCNP. In order to duplicate the same source model, the MAVRIC code has been modified to accommodate a user-defined axial source distribution. The comparison among the three codes was evaluated in terms of their accuracies and computational efficiencies. For the gamma-ray sources, the MAVRIC-calculated results are more accurate than SAS4 and consistent with those predicted by the continuous-energy MCNP calculations. Meanwhile, its computational efficiencies are comparable to the performance of the TORT-coupled MCNP calculations. For the fuel neutron source, the MAVRIC calculation with broad-group cross sections cannot give satisfactory result, and its computational performance is also a factor of [approximately]10 less efficient than that of TORT-coupled MCNP. With a fine-group cross-section library, MAVRIC can provide a better prediction but still underestimates the surface dose rates of the cask by 15 to 30%.