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 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
May 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
June 2026
Nuclear Technology
Fusion Science and Technology
Latest News
ADP on track to complete major D&D work at Crystal River-3 this summer
Advanced Decommissioning Partners, a joint venture of NorthStar Group Services and Orano USA, is set to complete major decommissioning activities at Crystal River-3 nuclear power plant in Florida this summer, according to the license termination plan (LTP) the company submitted to the Nuclear Regulatory Commission.
Sudipta Saha, Jamil Khan, Travis Knight, Tanvir Farouk
Nuclear Technology | Volume 208 | Number 3 | March 2022 | Pages 414-427
Technical Paper | doi.org/10.1080/00295450.2021.1936863
Articles are hosted by Taylor and Francis Online.
A global model is proposed to simulate the drying process of used nuclear fuel assemblies under vacuum drying conditions. The transient model consists of a coupled mass and energy conservation equation with appropriate source and sink terms. The classic Hertz-Knudsen expression is employed to resolve the evaporation rate and the associated water mass depletion in the system. Both latent heat of vaporization and residual decay heat are considered as sink and source in the energy conservation, respectively. The model is employed to simulate vacuum drying of spent nuclear fuel rod storage systems. Multistage stepwise vacuuming of the system is emulated, and several parametric studies are conducted to identify their role in the drying process. The predicted temporal profiles show that the proposed model is able to capture qualitative trends of the water removal rate, hence the dryness level of the system. The model prediction is also compared against experiments where the amount of residual water after a standard vacuum drying procedure is quantified. The predictions are found to compare favorably with the experimental measurements.