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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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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
Securing the advanced reactor fleet
Physical protection accounts for a significant portion of a nuclear power plant’s operational costs. As the U.S. moves toward smaller and safer advanced reactors, similar protection strategies could prove cost prohibitive. For tomorrow’s small modular reactors and microreactors, security costs must remain appropriate to the size of the reactor for economical operation.
T. Tambouratzis, M. Antonopoulos-Domis, M. Marseguerra, E. Padovani
Nuclear Science and Engineering | Volume 130 | Number 1 | September 1998 | Pages 113-127
Technical Paper | doi.org/10.13182/NSE98-A1994
Articles are hosted by Taylor and Francis Online.
The use of artificial neural networks (ANNs) for transit time estimation is investigated. ANNs are proposed as an alternative to widely employed traditional techniques such as cross correlation and the cross spectrum, which are sensitive to the presence of noise and require a large volume of data for their calculation. The ANN employed is based on interactive activation and competition and has been found able to correctly estimate the current transit time from short records of signals generated by simulation, quickly follow changes in transit time, and detect when the transit time falls outside a predefined expected range. By appending a backpropagation ANN, the on-line estimation of decimated transit times is also allowed.