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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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Latest News
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.
R. S. Keshavamurthy, R. S. Geetha
Nuclear Science and Engineering | Volume 162 | Number 2 | June 2009 | Pages 192-199
Technical Note | doi.org/10.13182/NSE162-192
Articles are hosted by Taylor and Francis Online.
Steffensen's inequality is used to obtain new properties of nuclear Doppler broadening functions. We apply the inequality on subinterval integrals of these functions to obtain bounds that provide new approximations for the Doppler broadening functions. The Taylor series is used to further simplify the analytic approximations for the bounds to sums of terms of elementary transcendental functions. The approximations for bounds are able to reproduce the functions with any desired decimal place accuracy. The average of the lower and upper bounds provide better approximations to achieve the same level of decimal place accuracy and are much more efficient computationally. The method is capable of computing the functions to arbitrary accuracy as the inequality essentially gives the bounds of the functions.