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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.
Utility Working Conference and Vendor Technology Expo
August 8–11, 2021
Marco Island, FL|JW Marriott Marco Island
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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DOE puts $9.35 million toward high-energy-density plasma research
The Department of Energy’s Office of Science (DOE-SC) and the National Nuclear Security Administration (NNSA) on July 27 announced $9.35 million for 21 research projects in high-energy-density laboratory plasmas. High-energy-density (HED) plasma research, originally developed to support the U.S. nuclear weapons program, has applications in astrophysics, fusion power plant development, medicine, nuclear and particle physics, and radioisotope production.
12th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies (NPIC&HMIT 2021)
Technical Session|Sponsored by Instrumentation and Controls
Wednesday, June 16, 2021|3:30–5:15PM (4:30–6:15PM EDT)|Room 4
Brent Shumaker (Analysis and Measurement Services Corp)
Jamie B. Coble (University of Tennessee-Knoxville)
Janet Davis (ANS)
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Physics-Based Automated Reasoning for Health Monitoring: Sensor Set Selection
R. Vilim (ANL), T. Nguyen (ANL), R. Ponciroli (ANL), H. Wang (ANL)
A Parallel Capability Using Genetic Algorithm for Sensor Assignment Optimization with Process-Constrained Data-Analytic Diagnosis
Yuxuan Liu (Univ. of Michigan), Brendan Kochunas (Univ. of Michigan), Tat Nghia Nguyen (ANL), Hubert Ley (ANL), Richard Vilim (ANL)
A Model-Based Symbolic Inference for Sensor Deployment Optimization for Fault Detection of the EBR-II Reactor
Xiaoxu Diao (The Ohio State Univ.), Pavan Kumar Vaddi (The Ohio State Univ.), Boyuan Li (The Ohio State Univ.), Wei Gao (The Ohio State Univ.), Carol Smidts (The Ohio State Univ.)
Physics-Informed Machine Learning-Aided System Space Discretization
Junyung Kim (Rensselaer Polytechnic Institute), Asad Ullah Amin Shah (Rensselaer Polytechnic Institute), Hyun Gook Kang (Rensselaer Polytechnic Institute), Xingang Zhao (ORNL)
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