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.
Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
2020 ANS Virtual Winter Meeting
November 16–19, 2020
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
Brouillette: Nuclear should be part of California’s energy problem solution
In an op-ed published on September 25 in the Orange County Register, Energy Secretary Dan Brouillette decryed the state of California’s handling of its energy crisis.
Brouillette criticized state leaders for championing a 100 percent renewable energy plan that ignores nuclear and natural gas. He also found fault with the plan to prematurely close the Diablo Canyon nuclear power plant.
Technical Session|Sponsored by MCD
Wednesday, November 18, 2020|1:40–3:20PM (2:40–4:20PM EST)
The session will be available to join at 1:10PM (2:10PM EST).
Kathryn D. Huff
Jeffrey A. Favorite
Brian C. Kiedrowski
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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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