ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jun 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
July 2026
Nuclear Technology
June 2026
Fusion Science and Technology
May 2026
Latest News
North American construction is back—smaller and faster—at OPG’s Darlington
“The nuclear renaissance is real here,” said Ontario Power Generation’s Subo Sinnathamby on May 8, one year to the day after OPG secured a final investment decision to build the first of four planned BWRX-300 reactors at its Darlington nuclear power plant, and shortly after the new reactor’s foundation was lifted into place. “We got our license to construct in April and our [final investment decision] in May, and we’ve been off to the races since.”
Wadim Jaeger, Victor Hugo Sanchez Espinoza
Nuclear Technology | Volume 184 | Number 3 | December 2013 | Pages 333-350
Technical Paper | Thermal Hydraulics | doi.org/10.13182/NT184-333
Articles are hosted by Taylor and Francis Online.
The validation of computer codes related to the thermal-hydraulic analyses of nuclear reactors is a challenging undertaking because of the complexity of the phenomena involved, e.g., boiling, condensation, and mixing. In the frame of the ongoing validation of the best-estimate system code TRACE, the present paper focuses on the phenomena taking place during the quenching of the hot surface of the fuel rod simulator with cold water. Since TRACE describes the physical phenomena with empirical correlations derived from experiments, it is necessary to ensure that these correlations are valid if applied to similar experiments but different boundary conditions. By means of an uncertainty and sensitivity study, the influence of the empirical models and their associated uncertainties on selected output parameters is quantified and the parameters with the largest sensitivity are evaluated.