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Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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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Fusion Science and Technology
Advanced nuclear to be a focus of reopened Arctic Energy Office
The Department of Energy has announced the reestablishment of the Arctic Energy Office (AEO), to be located on the campus of the University of Alaska Fairbanks. The AEO was originally established in 2001 but failed to receive sufficient funding. Energy Secretary Dan Brouillette had pledged to reopen the office by the close of the current federal fiscal year.
The focus of the AEO, according to the DOE, will include international cooperation on Arctic issues, research on methane hydrates, and the development of advanced microgrids and nuclear power systems, such as small modular reactors.
Technical Session|Sponsored by RPD
Thursday, November 19, 2020|11:15AM–1:00PM (12:15–2:00PM EST)
The session will be available to join at 10:45AM (11:45AM EST).
Pavel V. Tsvetkov
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Verification of the Re-Released ENDF/B VIII.0 Based Thermal Scattering Libraries
Donald K. Parsons (Los Alamos)
Neutron Capture on Stable Fission Product 139La Contribution to Delayed-Photoneutrons in Heavy Water Reactors
Yanuar A. Setiawan (Ulsan National Institute of Science & Technology), Douglas A. Fynan (Ulsan National Institute of Science and Technology)
Application of Machine Learning to Nuclear Data Evaluation
Pedro J. Vicente-Valdez (University of California Berkeley), Lee A. Bernstein (University of California Berkeley), Massimiliano Fratoni (University of California Berkeley)
Improving Resonance Integral Table Based Cross Section Methods Using Lasso Regression
Yuxuan Liu (University of Michigan), Brendan M. Kochunas (University of Michigan)
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