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Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2021)
February 9–11, 2021
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Fusion Science and Technology
Former NRC chairs issue vaccine timeline recommendation to CDC
Five former chairmen of the U.S. Nuclear Regulatory Commission—Stephen Burns, Allison Macfarlane, Nils Diaz, Richard Meserve, and Dale Klein—signed a letter to José Romero, Arkansas health secretary and chair of the Centers for Disease Control and Prevention (CDC) immunization advisory committee, requesting that the advisory committee update its recommendation for COVID-19 vaccine allocation guidance for the energy workforce (including nuclear energy workers).
Currently, the CDC has four phases for the COVID-19 vaccine rollout. Those phases are numbered:
Scott W. Mosher, Stephen C. Wilson
Fusion Science and Technology | Volume 74 | Number 4 | November 2018 | Pages 263-276
Technical Paper | dx.doi.org/10.1080/15361055.2018.1496691
Articles are hosted by Taylor and Francis Online.
Neutronics analyses of the ITER experimental fusion reactor rely on increasingly complex geometry models and estimates of energy-dependent neutron flux and radiation dose-rate distributions generated at ever higher resolutions. There are significant practical challenges with applying the Monte Carlo N-Particle (MCNP) continuous-energy transport code to high-resolution analyses. For models consisting of more than 100 000 surfaces and cells, geometry initialization can take several hours, thus slowing down model integration and transport analysis efforts. In multithreaded simulations, the amount of memory consumed by superimposed mesh tally data increases in proportion to the number of threads. This behavior limits either the tally resolution or the number of processor cores that can be utilized in the simulation. This paper describes algorithmic improvements that were implemented in a modified version of MCNP5 to overcome these limitations. These improvements are referred to as the Oak Ridge National Laboratory Transformative Neutronics (ORNL-TN) upgrade. A comparison of the performance and memory usage of both MCNP5 and ORNL-TN on several relevant fusion neutronics models is presented. In these tests and in actual high-resolution neutronics analyses, ORNL-TN reduces geometry processing times from hours to a few seconds and increases in-memory mesh tally capacity from the order of 108 to 1010 space-energy bins.