ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
2021 Student Conference
April 8–10, 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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DOE lists five stories to watch in 2021
Despite all the challenges of the COVID-19 pandemic, the U.S. nuclear energy community pulled out some big wins in 2020, and this year could be even bigger, according to the Department of Energy’s Office of Nuclear Energy.
From deep space exploration on Mars to a historic new reactor coming online in Waynesboro, Ga., 2021 will be a record-breaking year for the industry—both good and potentially bad.
Find the full details on the DOE-NE website.
Technical Session|Sponsored by MCD
Wednesday, November 18, 2020|1:40–3:20PM (2:40–4:20PM EST)
Kathryn D. Huff
Jeffrey A. Favorite
Brian C. Kiedrowski
Ashley Jiminian (American Nuclear Society)
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Applying Constrained Bayesian Optimization to the Design of Criticality Experiments
Daniel J. Siefman (LLNL), Catherine M. Percher (LLNL), Jesse Norris (LLNL)
Deep Surrogate Models for Multi-dimensional Regression of Reactor Power
Akshay Dave (Massachusetts Institute of Technology), Jarod Wilson (Massachusetts Institute of Technology), Kaichao Sun (Massachusetts Institute of Technology)
Assembly Combinatorial Optimisation with Deep Reinforcement Learning
Majdi I. Radaideh (University of Illinois Urbana Champaign), Benoit Forget (Massachusetts Institute of Technology), Koroush Shirvan (Massachusetts Institute of Technology)
Analysis of Reactor Simulations with Deep Learning Surrogate Models
Majdi I. Radaideh (University of Illinois Urbana Champaign), Tomasz Kozlowski (University of Illinois)
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