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Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
2023 ANS Winter Conference and Expo
November 12–15, 2023
Washington, D.C.|Washington Hilton
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Nuclear Science and Engineering
Fusion Science and Technology
New TRIGA fuel delivered to a U.S. university reactor for the first time in a decade
Penn State’s Radiation Science and Engineering Center (RSEC) has received the first new TRIGA fuel shipped to the United States since 2012, the university announced on September 28. The fuel reached University Park, Pa., on September 27 and is destined for RSEC’s Breazeale Reactor, the nation’s longest continuously operating university research reactor.
Technical Session|Sponsored by IRD
Tuesday, June 9, 2020|12:00–2:10PM EDT
James Bowen (PNNL)
Igor Jovanovic (Univ. of Michigan)
Paul LaTour (American Nuclear Society)
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Betavoltaic Nuclear Microbattery Based on Graphene/Si Schottky Junction
Xiaoyu Wang (Univ. of Science and Technology of China), Weiping Liu (Chinese Academy of Sciences), Jiachen Zhang (Univ. of Science and Technology of China), Yuncheng Han (Chinese Academy of Sciences), Taosheng Li (Chinese Academy of Sciences), Chunjing Li (Chinese Academy of Sciences)
Correlation of Absolute 238U Bioavailability (238U-ABA) and 238U Bioaccessibility Fraction (238U-BAF) Using IAEA-312 Standard Reference Soil
Nur Shahidah Abdul Rashid (Pohang Univ. of Science and Technology), Wooyong Um (Pohang Univ. of Science and Technology), Khoo Kok Siong (The Nat'l Univ. of Malaysia), Nur Syamimi Diyana Rodzi (The Nat'l Univ. of Malaysia)
Neutronics Analysis for Designing a Low Activation Heated Test Cell
Michael Buratynski (Penn State Univ.), William J. Walters (Penn State Univ.)
Predicting Background Count Rate of a Mobile Detector using an Optimal Linear Ensemble of Learning Kernel Machines
Miltiadis Alamaniotis (Univ. of Texas, San Antonio)
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