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Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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
Can hydrogen be the transportation fuel in an otherwise nuclear economy?
Let’s face it: The global economy should be powered primarily by nuclear power. And it probably will by the end of this century, with a still-significant assist from renewables and hydro. Once nuclear systems are dominant, the costs come down to where gas is now; and when carbon emissions are reduced to a small portion of their present state, it will become obvious that most other sources are only good in niche settings. I mean, why use small modular reactors to load-follow when they can just produce that power instead of buffering it?
C. van der Hoeven, E. Schneider, L. Leal
Nuclear Science and Engineering | Volume 179 | Number 1 | January 2015 | Pages 1-21
Technical Paper | doi.org/10.13182/NSE13-78
Articles are hosted by Taylor and Francis Online.
There is a need for improved molybdenum isotope covariance data for use in modeling a new uranium-molybdenum fuel form to be produced at the Y-12 National Security Complex (Y-12). Covariance data correlate the uncertainty in an isotopic cross section at a particular energy to uncertainties at other energies. While high-fidelity covariance data exist for key isotopes, the low-fidelity covariance data available for most isotopes, including the natural molybdenum isotopes considered in this work, are derived from integral measurements without meaningful correlation between energy regions. This paper provides a framework for using the Bayesian R-matrix code SAMMY to derive improved isotopic resonance region covariance data from elemental experimental cross-section data. These resonance-wise covariance data were combined with integral uncertainty data from the Atlas of Neutron Resonances, uncertainty data generated via a dispersion method, and high-energy uncertainty data previously generated with the Empire-KALMAN code to produce an improved set of covariance data for the natural molybdenum isotopes. The improved covariance data sets, along with the associated resonance parameters, were inserted into JENDL4.0 data files for the molybdenum isotopes for use in data processing and modeling codes. Additionally, a series of critical experiments featuring the new U(19.5%)-10Mo fuel form produced at Y-12 was designed. Along with existing molybdenum sensitive critical experiments, these were used to compare the performance of the new molybdenum covariance data against the existing low-fidelity evaluation. The new covariance data were found to result in reduced overall bias, reduced bias due to the molybdenum isotopes, and improved goodness of fit of computational to experimental results.