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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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NNSA awards BWXT $1.5B defense fuels contract
The Department of Energy’s National Nuclear Security Administration has awarded BWX Technologies a contract valued at $1.5 billion to build a Domestic Uranium Enrichment Centrifuge Experiment (DUECE) pilot plant in Tennessee in support of the administration’s efforts to build out a domestic supply of unobligated enriched uranium for defense-related nuclear fuel.
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.