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Division Spotlight
Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
Meeting Spotlight
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
Countering the nuclear workforce shortage narrative
James Chamberlain, director of the Nuclear, Utilities, and Energy Sector at Rullion, has declared that the nuclear industry will not have workforce challenges going forward. “It’s time to challenge the scarcity narrative,” he wrote in a recent online article. “Nuclear isn't short of talent; it’s short of imagination in how it attracts, trains, and supports the workforce of the future.”
Ioannis A. Papazoglou, Elias P. Gyftopoulos
Nuclear Science and Engineering | Volume 73 | Number 1 | January 1980 | Pages 1-18
Technical Paper | doi.org/10.13182/NSE80-A18703
Articles are hosted by Taylor and Francis Online.
A methodology for the assessment of uncertainties about reliability of nuclear reactor systems described by Markov models is developed, and the uncertainties about the failure probability of the shutdown system of the Clinch River Breeder Reactor (CRBR) are assessed. Failure and repair rates and all other inputs of reliability analysis are taken as random variables with known probability distribution functions (pdf's). The pdf of reliability is calculated by both a Monte Carlo simulation and a Taylor series expansion approximation. Three techniques are developed to reduce the computational effort: (a) ordering of system states, (b) merging of Markov processes, and (c) judicious choice of time steps. A Markov model has been used for reliability analysis under uncertainty of the shut- down system of the CRBR. It accounts for common-cause failures, interdependences between unavailability of the system and occurrence of transients, and inspection and maintenance procedures that depend on the state of the system and that include possibility of human errors. Under these conditions, the failure probability of the shutdown system differs significantly from that computed without common-cause failures, human errors, and input uncertainties.