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Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
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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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Bowman & Smith on NRC security programs
Greg Bowman and George Smith work for the Nuclear Regulatory Commission in implementing programs that deal with risk, whether to nuclear power plants or from nuclear materials, such as radiological sabotage and theft or diversion of materials. Bowman is the director of the NRC’s Division of Physical and Cybersecurity Policy in the Office of Nuclear Security and Incident Response. Smith is the senior project manager for security in the Source Management & Protection Branch of the Division of Materials Safety, Security, State, and Tribal Programs in the Office of Nuclear Material Safety and Safeguards.
The three initiatives Bowman and Smith discussed with Nuclear News editor-in-chief Rick Michal are the Insider Threat Program, the Cybersecurity Program, and the Domestic Safeguards Program.
Man Gyun Na, Seungrohk Oh
Nuclear Technology | Volume 140 | Number 2 | November 2002 | Pages 178-197
Technical Paper | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies | doi.org/10.13182/NT02-A3332
Articles are hosted by Taylor and Francis Online.
A neuro-fuzzy inference system combined with the wavelet denoising, principal component analysis (PCA), and sequential probability ratio test (SPRT) methods has been developed to monitor the relevant sensor using the information of other sensors. The parameters of the neuro-fuzzy inference system that estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The wavelet denoising technique was applied to remove noise components in input signals into the neuro-fuzzy system. By reducing the dimension of an input space into the neuro-fuzzy system without losing a significant amount of information, the PCA was used to reduce the time necessary to train the neuro-fuzzy system, simplify the structure of the neuro-fuzzy inference system, and also, make easy the selection of the input signals into the neuro-fuzzy system. By using the residual signals between the estimated signals and the measured signals, the SPRT is applied to detect whether the sensors are degraded or not. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level, the pressurizer pressure, and the hot-leg temperature sensors in pressurized water reactors.