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Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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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Survey says . . . Emotional intelligence important in nuclear industry
The American Nuclear Society’s Diversity and Inclusion in ANS (DIA) Committee hosted a workshop social at the 2024 Winter Conference & Expo in November that brought dozens of attendees together for an engaging—and educational—twist on the game show Family Feud.
Jiro Wakabayashi, Shin-Ichi Tashima, Akio Gofuku
Nuclear Technology | Volume 70 | Number 3 | September 1985 | Pages 343-353
Technical Paper | Fission Reactor | doi.org/10.13182/NT85-A15961
Articles are hosted by Taylor and Francis Online.
Two kinds of identification techniques for the diagnosis of disturbances in nuclear power plants have been proposed, and the applicability of these techniques to actual plants has been verified by computer experiments. In both techniques, a set of the observed signals (observed vector) obtained from an actual plant is identified with one of the categories representing a normal state, several anticipated anomalous situations, and an unanticipated anomalous state, in which the categories corresponding to the anticipated anomalous situations are classified by the kind and approximate magnitude of the anomaly source (the disturbance). The maximum likelihood technique is used in method 1. It applies to the identification of multiple anticipated disturbances that happen sequentially with some time interval, even if a plant has some nonlinear characteristics. The projective operator technique is used in method 2. It applies to the identification of any kind of multiple anticipated disturbances under the conditions of the plant having approximately linear characteristics and the observed vectors corresponding to the anticipated disturbances are linearly independent of each other.