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Division Spotlight
Reactor Physics
The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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X-energy, Dow apply to build an advanced reactor project in Texas
Dow and X-energy announced today that they have submitted a construction permit application to the Nuclear Regulatory Commission for a proposed advanced nuclear project in Seadrift, Texas. The project could begin construction later this decade, but only if Dow confirms “the ability to deliver the project while achieving its financial return targets.”
Ruixian Fang, Dan G. Cacuci (Univ of South Carolina)
Proceedings | 2018 International Congress on Advances in Nuclear Power Plants (ICAPP 2018) | Charlotte, NC, April 8-11, 2018 | Pages 451-459
The “predictive modeling for coupled multi-physics systems (PM_CMPS)” methodology is applied in this work to the numerical simulation model of the mechanical draft cooling tower (MDCT) located in the F-area at Savannah River National Laboratory (SRNL) in order to improve the predictions of this model by combining computational information with measurements of outlet air humidity, outlet air and outlet water temperatures. At the outlet of this cooling tower, where measurements of the quantities of interest are available, the PM_CMPS reduces the predicted uncertainties for these quantities to values that are smaller than either the computed or the measured uncertainties. The PM_CMPS has also been applied to reduce the uncertainties for quantities of interest inside the tower’s fill section, where no direct measurements are available. The maximum reductions of uncertainties occur at the locations where direct measurements are available. At other locations, the predicted response uncertainties are reduced by the PM_CMPS methodology to values that are smaller than the modeling uncertainties arising from the imprecisely known model parameters.