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Reactor Physics
The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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DOE issues final RFQ for WIPP clean energy initiative
The Department of Energy’s Office of Environmental Management has issued a request for qualifications for interested parties and prospective offerors looking to enter into a realty agreement for carbon-pollution-free electricity (CFE) projects at the department’s Waste Isolation Pilot Plant site in southeastern New Mexico.
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.