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Division Spotlight
Thermal Hydraulics
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
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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Strong performances across the board
Craig Piercycpiercy@ans.org
Another year, another stellar performance by America’s nuclear plants. We’ve come to expect high capacity factors, and it’s a credit to the men and women of the profession. They’ve made routine something that was unimaginable not so long ago.
The decadal challenge for the nuclear enterprise now is to maintain this high level of operational excellence for the current fleet, while at the same time ushering in a new generation of technologies at scale. It will be a big job—but one that seems more and more likely with each passing day.
Axel Hoefer, Oliver Buss, Michael Schmid
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1578-1587
Technical Paper | doi.org/10.1080/00295450.2018.1560784
Articles are hosted by Taylor and Francis Online.
A general Bayesian framework for best-estimate plus uncertainty predictions of multidimensional continuous observables is presented. Parameterizing uncertainties in terms of multivariate normal distribution models, this Multivariate normal Bayesian model (MNBM) framework allows one to include both measured data and linear constraints in a mathematically consistent way. The resulting updating formulas are generalizations of the updating formulas of the Generalized Linear Least Squares (GLLS) framework, which is widely used for the generation of adjusted nuclear data libraries. While the GLLS methodology is restricted to first-order perturbation theory, there is no such restriction for the considered MNBM framework. This makes it possible to use Monte Carlo uncertainty propagation and to apply the updating formulas directly to the observables of interest without having to first update the input parameter distributions. After a general presentation of the MNBM framework and a brief discussion of its possible applications, the generation of bounding burnup-dependent axial burnup profiles of light water reactor fuel assemblies for the purpose of criticality safety analysis is discussed as an example application.