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Operations & Power
Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
2024 ANS Annual Conference
June 9–12, 2024
Las Vegas, NV|The Mirage
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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The Sodium Reactor Experiment
In February 1957, construction was completed on the Sodium Reactor Experiment (SRE), a sodium-cooled, graphite-moderated reactor with an output of 20 MWt. The design of theSRE had begun three years earlier in 1954, and construction started in April 1955. On April 25, 1957, the reactor reached criticality, and the SRE operated until February 1964.
Advances in Thermal Hydraulics (ATH 2022)
Wednesday, June 15, 2022|3:15–5:00PM PDT|San Simeon B
Xingang Zhao (ORNL)
Yang Liu (ANL)
In the past few years, reactor thermal-hydraulic (T-H) study has advanced with the support of machine learning (ML) in many aspects, including automated experimental data analysis, data-driven prediction for important reactor thermal-fluid phenomena, and surrogate modeling and uncertainty quantification for reactor system codes. ML also showed promising potential to expand reactor T-H to a wider range of applications to better support advanced reactor deployment, such as integrated multi-physics modeling and digital twin. On the other hand, ML in T-H study has its unique challenges, from data availability and quality to model transparency and interpretability.
In this panel session, experts from different institutes with a diverse background will share their experience and perspectives on ML for T-H study, including recent progresses, existing challenges and potential solutions, and future opportunities.
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