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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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International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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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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Argonne’s METL gears up to test more sodium fast reactor components
Argonne National Laboratory has successfully swapped out an aging cold trap in the sodium test loop called METL (Mechanisms Engineering Test Loop), the Department of Energy announced April 23. The upgrade is the first of its kind in the United States in more than 30 years, according to the DOE, and will help test components and operations for the sodium-cooled fast reactors being developed now.
M. T. Pigni, M. Herman, P. Oblozinsky
Nuclear Science and Engineering | Volume 162 | Number 1 | May 2009 | Pages 25-40
Technical Paper | doi.org/10.13182/NSE162-25
Articles are hosted by Taylor and Francis Online.
We generated, for the first time, a very comprehensive set of estimates of cross-section covariance data in the neutron energy range of 5 keV to 20 MeV. The covariance matrices were obtained for 307 materials, from 19F to 209Bi, covering structural materials, fission products, and heavy nonfissile nuclei. These results offer model-based, consistent assessments of covariance data for nuclear criticality safety applications. The evaluation methodology combines the nuclear reaction model code EMPIRE, which calculates the sensitivity of the cross sections to nuclear reaction model parameters, and the Bayesian code KALMAN, which propagates uncertainties of the model parameters to these cross sections. Taking into account the large number of materials studied, we refer only marginally to experimental data. The covariances were derived from the perturbation of several key model parameters selected by the sensitivity analysis. These parameters refer to the optical model potential, the level densities, and the strength of the preequilibrium emission. Our work represents the first attempt to generate neutron cross-section covariances on such a large scale.