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Division Spotlight
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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Fusion Science and Technology
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.
D. Elbèze, D. van Houtte, E. Delchambre
Fusion Science and Technology | Volume 75 | Number 5 | July 2019 | Pages 405-411
Technical Paper | doi.org/10.1080/15361055.2019.1603534
Articles are hosted by Taylor and Francis Online.
In the Reliability, Availability, Maintainability, and Inspectability (RAMI) engineering approach used in nuclear fusion research, criticality identifies the failure modes that have the greatest impact on the availability of the studied system. Criticality is expressed as the product of the occurrence level with the severity level of failure modes. The analytical calculation shows that this formulation is equivalent to their availability provided that the duty cycle of basic functions is introduced to adjust the occurrence and the scales of occurrence and severity are homogeneous.
To consolidate the results obtained with a Reliability Block Diagram analysis, we performed a probabilistic study using an advanced Monte Carlo simulation code: the Primavera® Quantitative Schedule Risk Analysis. This method associates failure modes with conditional activities in a schedule and provides the density distribution of failures and tornado graphs to identify the highest criticality failures.
Statistical tests were performed for two operational systems, and we showed that the criticality evaluated with the RAMI approach was in good agreement with the results of the other methods. Thus, in many cases, the analytical formulas can be used during the Failure Mode, Effects, and Criticality Analysis to quickly assess availability by using a spreadsheet.