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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.
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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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Latest News
Can hydrogen be the transportation fuel in an otherwise nuclear economy?
Let’s face it: The global economy should be powered primarily by nuclear power. And it probably will by the end of this century, with a still-significant assist from renewables and hydro. Once nuclear systems are dominant, the costs come down to where gas is now; and when carbon emissions are reduced to a small portion of their present state, it will become obvious that most other sources are only good in niche settings. I mean, why use small modular reactors to load-follow when they can just produce that power instead of buffering it?
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.