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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.
2021 ANS Virtual Annual Meeting
June 14–16, 2021
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
Fusion Science and Technology
How the NRC modernized its digital I&C infrastructure and where it goes from here
The Nuclear Regulatory Commissiona first formally developed infrastructure for the review of digital instrumentation and control (I&C) systems in the 1990s. Although the current fleet of nuclear power plants in the United States was originally designed and constructed with analog systems, the U.S. nuclear industry has for more than 30 years been working to upgrade these older systems with modern digital equipment.
Saturday, April 10, 2021|1:00–2:30PM (2:00–3:30PM EDT)
Andy Rivas (NC State Univ.)
Edward Chen (NC State Univ.)
Grayson Gall (NC State Univ.)
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Expansion of the Monte Carlo Integrated Tiger Series Validation Suite
Rowdy Davis (University of New Mexico), Christopher M. Perfetti (University of New Mexico), Aaron J. Olson (Sandia National Laboratories), Ronald P. Kensek (Sandia National Laboratories), Brian C. Franke (Sandia National Laboratories)
Frequency Transform Method for Transient Analysis of Nuclear Reactors
Miriam A. Kreher (Massachusetts Institute of Technology), Samuel C. Shaner (Massachusetts Institute of Technology), Benoit Forget (Massachusetts Institute of Technology), Kord S. Smith (Massachusetts Institute of Technology)
Machine Learning in Probabilistic Risk Assessment and Management: A Review and Path Forward
Alp Tezbasaran (North Carolina State University), Mihai A. Diaconeasa (North Carolina State University)
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