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Conference Spotlight
2025 ANS Winter Conference & Expo
November 8–12, 2025
Washington, DC|Washington Hilton
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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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Japan gets new U for enrichment as global power and fuel plans grow
President Trump is in Japan today, with a visit with new Prime Minister Sanae Takaichi on the agenda. Takaichi, who took office just last week as Japan’s first female prime minister, has already spoken in favor of nuclear energy and of accelerating the restart of Japan’s long-shuttered power reactors, as Reuters and others have reported. Much of the uranium to power those reactors will be enriched at Japan’s lone enrichment facility—part of Japan Nuclear Fuel Ltd.’s Rokkasho fuel complex—which accepted its first delivery of fresh uranium hexafluoride (UF₆) in 11 years earlier this month.
Natalie Gordon, Lindsay Gilkey, Ralph C. Smith, Isaac Michaud, Brian Williams, Vincent Mousseau, Russell Hooper, Chris Jones
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1685-1696
Technical Paper | doi.org/10.1080/00295450.2019.1590073
Articles are hosted by Taylor and Francis Online.
Simulation-based nuclear reactor design requires highly efficient codes that quantify the requisite physics while having the efficiency required for optimization-based design and uncertainty quantification. To achieve the required accuracy and predictive capabilities, phenomenological parameters, often employed in closure relations or to quantify unmodeled or unresolved physics, must be calibrated for considered reactor conditions and designs. When available, experimental data with quantified observation errors are ideally employed for calibration. However, for many thermal-hydraulic, fuel, and Chalk River Unidentified Deposits modeling regimes, experimental data are prohibitively expensive or impossible to collect. For such cases, we demonstrate the use of a mutual information–based experimental design framework to employ validated high-fidelity codes to calibrate parameters in low-fidelity design codes. We demonstrate the use of the high-fidelity computational fluid dynamics package STAR-CCM+ to calibrate the turbulent mixing coefficient β in COBRA-TF (CTF). This includes the construction and verification of a surrogate for CTF, which permits the computationally intensive experimental design and Bayesian calibration steps. We also demonstrate Bayesian inference of parameter distributions for the Dittus-Boelter relation and propagation of these uncertainties through CTF to improve uncertainty bounds for computed maximum fuel temperatures.