ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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
June 2025
Nuclear Technology
May 2025
Fusion Science and Technology
Latest News
EnergySolutions to help explore advanced reactor development in Utah
Utah-based waste management company EnergySolutions announced that it has signed a memorandum of understating with the Intermountain Power Agency and the state of Utah to explore the development of advanced nuclear power generation at the Intermountain Power Project (IPP) site near Delta, Utah.
Advances in Thermal Hydraulics (ATH 2024)
Technical Session
Tuesday, November 19, 2024|10:00–11:45AM EST|Coral C
Session Chair:
Subash Sharma (UML)
Alternate Chair:
Ethan Wong (Imperial College London)
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Assessment of Physics-Informed Neural Networks (PINNs) with Transfer Learning (TL) for Incompressible Turbulent Flows
10:00–10:20AM EST
Y.H. Wong (Imperial College London), Y. Duan (Imperial College London), L. Lampunio (Imperial College London), M.D. Eaton (Imperial College London), M.J.Bluck (Imperial College London)
Paper
Prediction and Uncertainty Quantification of Critical Heat Flux -- A Comparison Between Generative Conditional VAEs and DNNs
10:20–10:40AM EST
Farah Alsafadi (NCSU), Aidan Furlong (NCSU), Xu Wu (NCSU)
Quantifying Model Uncertainty of Neural-Network Based Turbulence Closures
10:40–11:00AM EST
Cody Grogan (Utah State), Som Dutta (Utah State), Mauricio Tano (INL), Somayajulu L.N. Dhulipala (INL), Izabela Gutowska (Oregon State)
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