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.”
Constantine P. Tzanos
Nuclear Technology | Volume 174 | Number 1 | April 2011 | Pages 41-50
Technical Paper | Heat Transfer | doi.org/10.13182/NT11-A11678
Articles are hosted by Taylor and Francis Online.
In liquid-metal flows, the predictions of the Nusselt number (heat transfer) by Reynolds-averaged Navier-Stokes models of turbulence that use the assumption of a constant turbulent Prandtl number can be significantly off. Heat transfer analyses were performed with a number of turbulence models for flows in a triangular rod bundle and in a pipe, and model predictions were compared with experimental data. Emphasis was placed on the low Reynolds (low-Re) number k- model that resolves the boundary layer and does not use "logarithmic wall functions." The high Reynolds (high-Re) number k- model underpredicts the Nusselt number up to 30%, while the low-Re number model overpredicts it up to 34%. For high Peclet number values, the low-Re number model provides better predictions than the high-Re number model. For Peclet numbers higher than 1500, the predictions of the Reynolds stress model (RSM) are in very good agreement with experimental measurements, but for lower Peclet number values its predictions are significantly off. A relationship was developed that expresses the turbulent Prandtl number as a function of the ratio of the turbulent viscosity to the molecular viscosity. With this modified turbulent Prandtl number, for the flow in the rod bundle the predictions of the low-Re number model are well within the spread of the experimental measurements. For pipe flow, the model predictions are not as sensitive to the correction of the turbulent Prandtl number as they are in the case of the flow in a bundle. The modified low-Re number model underpredicts the limited experimental data by 4%.