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Division Spotlight
Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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
April 2024
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February 2024
Latest News
Can hydrogen be the transportation fuel in an otherwise nuclear economy?
Let’s face it: The global economy should be powered primarily by nuclear power. And it probably will by the end of this century, with a still-significant assist from renewables and hydro. Once nuclear systems are dominant, the costs come down to where gas is now; and when carbon emissions are reduced to a small portion of their present state, it will become obvious that most other sources are only good in niche settings. I mean, why use small modular reactors to load-follow when they can just produce that power instead of buffering it?
Technical Session|Sponsored by MCD
Wednesday, November 18, 2020|2:40–4:20PM EST
Session Chair:
Kathryn D. Huff
Alternate Chair:
Jeffrey A. Favorite
Session Organizer:
Brian C. Kiedrowski
Staff Producer:
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)
Paper
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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