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Division Spotlight
Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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Nuclear Science and Engineering
April 2025
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March 2025
Fusion Science and Technology
Latest News
Report spotlights energy sector’s growing nuclear investment
As part of a broader series on the future of global energy markets, S&P Global has released a report on examining the growing interest in nuclear power as the solution to many of the problems the energy sector faces.
To read the full details and conclusions of the report, click here.
12th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies (NPIC&HMIT 2021)
Technical Session
Wednesday, June 16, 2021|4:30–6:15PM EDT
Session Chair:
Brent Shumaker (Analysis and Measurement Services Corp)
Alternate Chair:
Jamie B. Coble (University of Tennessee-Knoxville)
Session Organizer:
Staff Producer:
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)
Paper
Reference
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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