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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
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Fusion Science and Technology
Latest News
Former Exelon CEO Chris Crane remembered for “transformational milestones”
Crane
Exelon announced that Chris Crane, the company’s former chief executive, passed away on Saturday in Chicago at the age of 65.
Crane served as the company’s president and CEO from 2012 until his retirement in December 2022. During his tenure, he steered the energy company through several transformational milestones, including the successful mergers with Constellation Energy in 2012 and Pepco Holdings in 2016, creating the largest utility business by customer count in the United States.
In 2022, with the spin-off of Constellation as the generation and retail side of energy business (with the largest U.S. nuclear fleet), Crane led the creation of a stand-alone transmission and delivery energy company.
Stefano Carli, Roberto Bonifetto, Tiago Pomella Lobo, Laura Savoldi, Roberto Zanino
Fusion Science and Technology | Volume 68 | Number 2 | September 2015 | Pages 336-340
Technical Paper | Proceedings of TOFE-2014 | doi.org/10.13182/FST14-986
Articles are hosted by Taylor and Francis Online.
In a tokamak with superconducting magnets, the operation of the cryoplant requires the knowledge of the heat load coming from the cryogenic loops that cool the different magnet systems.
Artificial Neural Networks (ANNs) are applied for the first time to the ITER Toroidal Field (TF) magnets. Two different models are developed: 1) a simpler one, aiming at checking the effects of the different operating scenarios on the cryoplant; 2) a more complex one, aiming at helping in the design of suitable control strategies for the magnet operation, to reduce the variation of the heat load to the cryoplant.
The developed ANNs are suitably trained based on results obtained with the state-of-the-art thermal-hydraulic code 4C, that simulates the TF magnet response when subject to a broad spectrum of heat load variations. The predictive capability of the resulting ANN models is tested in different operating scenarios.