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Division Spotlight
Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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.
Steven E. Aumeier, Bulent Alpay, John C. Lee, A. Ziya Akcasu
Nuclear Science and Engineering | Volume 153 | Number 2 | June 2006 | Pages 101-123
Technical Paper | doi.org/10.13182/NSE06-A2599
Articles are hosted by Taylor and Francis Online.
We present probabilistic techniques that make synergistic use of available process information for diagnosis and detection of component fault manifestation in a multicomponent system. We begin by describing the motivation for using probabilistic techniques for systems diagnostics and then define probabilistic expressions that embody the diagnostics knowledge of interest. We show that a combination of a Bayesian expression with the solution to the Chapman-Kolmogoroff equation contains the diagnostic information of interest while explicitly making use of available process information including plant data or measurements, mathematical system models, and individual component reliability data. Given these probabilistic expressions, we introduce a practical means of obtaining the necessary constituent probability density functions corresponding to feasible component transitions via an adaptive Kalman filtering formulation. To demonstrate the consolidated probabilistic technique, we consider a low-order model of a balance of plant of a boiling water reactor, represented by 11 system variables, 9 component characteristics, and 5 observations. We simulate 5 to 10% degradations in two components subject to 1% signal noise in two different transient events. Our test calculations indicate that the proposed algorithm is able to provide correct fault detection and diagnosis of the faulted components and fault magnitudes, together with a rank-ordered likelihood of the binary faults.