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Division Spotlight
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.
Meeting Spotlight
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
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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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.
Robert W. Rice, John C. Walton
Nuclear Technology | Volume 163 | Number 1 | July 2008 | Pages 15-23
Technical Paper | High-Level Radioactive Waste Management | doi.org/10.13182/NT08-A3965
Articles are hosted by Taylor and Francis Online.
A numerical experiment was performed in order to examine the ability of multiple Monte Carlo realizations of a numerical model to reproduce the risk from a hypothetically known waste disposal situation. In the analysis, the risk was summarized by several risk metrics that could be chosen by a regulatory agency to set a risk standard. In the numerical experiment, the parameters in the numerical model are systematically varied to adjust bias (conservative or nonconservative) and to increase uncertainty relative to the hypothetically known future. The influence of parameter bias and uncertainty on the accuracy of each risk metric in predicting the nominal risk was evaluated and presented graphically. These analyses concluded that the peak-of-the-mean metric provides the least stable and least accurate risk predictions, whereas the cumulative release metric and mean of the peaks are more stable and accurate. The peak-of-the-mean and peak-of-the-median metrics exhibit risk dilution (i.e., a decrease in the predicted risk with increased uncertainty) and tend to underpredict risk. Additionally, these results illustrated how risk predictions that are made using what may be considered "conservative" assumptions can be moved in a direction that may or may not be expected or intended. Simulation relative to a hypothetical future (i.e., the nominal case) provides insight into the numerical behavior and potential accuracy of our risk assessment tools and potential issues with setting regulatory standards.