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The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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2025 ANS Annual Conference
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Chicago, IL|Chicago Marriott Downtown
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Fusion Science and Technology
Latest News
Smarter waste strategies: Helping deliver on the promise of advanced nuclear
At COP28, held in Dubai in 2023, a clear consensus emerged: Nuclear energy must be a cornerstone of the global clean energy transition. With electricity demand projected to soar as we decarbonize not just power but also industry, transport, and heat, the case for new nuclear is compelling. More than 20 countries committed to tripling global nuclear capacity by 2050. In the United States alone, the Department of Energy forecasts that the country’s current nuclear capacity could more than triple, adding 200 GW of new nuclear to the existing 95 GW by mid-century.
M. Santos, A. J. Cantos
Fusion Science and Technology | Volume 58 | Number 2 | October 2010 | Pages 706-713
Selected Paper from the Sixth Fusion Data Validation Workshop 2010 (Part 1) | doi.org/10.13182/FST10-A10895
Articles are hosted by Taylor and Francis Online.
In the analysis and classification of signals from massive databases, it is highly desirable to use automatic mechanisms. The synergy of artificial intelligence and advanced signal processing techniques is becoming very efficient in developing this kind of task. In this work we employ a signal processing strategy based on the wavelet transform and then genetic algorithms for classification purposes. An in-depth analysis of the waveforms has been carried out, and an analytical preprocessing has been applied to prepare the signals for their classification. Each individual of the simulated population represents a classifying rule, composed of an antecedent and a consequent. The codification of the knowledge is one of the main contributions of this paper. This genetic classification system has been applied to six different classes of plasma signals of the TJ-II stellarator database at CIEMAT in Spain with satisfactory results.
