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Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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
January 2026
Nuclear Technology
December 2025
Fusion Science and Technology
November 2025
Latest News
AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
Technical Session
Wednesday, October 6, 2021|1:20–3:00PM EDT
Session Chair:
Patrick Brantley (LLNL)
Session Organizer:
Ryan G. McClarren (University of Notre Dame)
Student Producer:
Joseph Fustero (NC State Univ.)
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Advanced Transient Diagnostic with Ensemble Digital Twin Modeling
1:20–1:45PM EDT
Edward Chen (NC State Univ.), Linyu Lin (NC State Univ.), Nam T. Dinh (NC State Univ.)
Paper
Integration of Neural Networks With Numerical Solution of PDEs to Uncover Hidden Physics
1:45–2:10PM EDT
A.S. Iskhakov (NC State Univ.), N. T. Dinh (NC State Univ.)
Application of Deep Learning Networks to Surrogate Modeling of Crud Deposition
2:10–2:35PM EDT
B. Andersen (NC State Univ.), A. Godfrey (ORNL), J. Hou (NC State Univ.), D. Kropaczek (ORNL)
A Multi-Level Feature Extraction and Denoising Approach to Detect Subtle Variations in Industrial Control Systems
2:35–3:00PM EDT
Arvind Sundaram (Purdue Univ.), Yeni Li (Purdue Univ.), Hany S. Abdel Khalik (Purdue Univ.)
Presentation Video (Visible to Attendees)
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