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Division Spotlight
Operations & Power
Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
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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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.
Albert Kreuser, Jörg Peschke
Nuclear Technology | Volume 136 | Number 3 | December 2001 | Pages 255-260
Technical Paper | Reactor Safety | doi.org/10.13182/NT01-A3243
Articles are hosted by Taylor and Francis Online.
The quantification of common-cause failures (CCFs) is often connected with uncertainties in how to interpret observed CCF events and with how far they are applicable to the specific group of components in question. A method has been developed that allows consideration of these kinds of uncertainties on the basis of a modification of the Binomial-Failure-Rate model. The quantification of interpretation uncertainties by means of interpretation alternatives is discussed as well as their effects on the estimation of the coupling parameter of the underlying CCF model. The estimation of the coupling parameter under consideration of the aforementioned uncertainties is performed by a Bayesian approach. To facilitate the specification of interpretation uncertainties, a default proposal of the interpretation vector is automatically generated on the basis of component fault states gained by expert judgment. Modification of the default vector is possible depending on engineering judgment of technical or operational differences between the observed and the target group of components.