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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
IAEA again raises global nuclear power projections
Noting recent momentum behind nuclear power, the International Atomic Energy Agency has revised up its projections for the expansion of nuclear power, estimating that global nuclear operational capacity will more than double by 2050—reaching 2.6 times the 2024 level—with small modular reactors expected to play a pivotal role in this high-case scenario.
IAEA director general Rafael Mariano Grossi announced the new projections, contained in the annual report Energy, Electricity, and Nuclear Power Estimates for the Period up to 2050 at the 69th IAEA General Conference in Vienna.
In the report’s high-case scenario, nuclear electrical generating capacity is projected to increase to from 377 GW at the end of 2024 to 992 GW by 2050. In a low-case scenario, capacity rises 50 percent, compared with 2024, to 561 GW. SMRs are projected to account for 24 percent of the new capacity added in the high case and for 5 percent in the low case.
Grégory Perret, Damar Wicaksono, Ivor D. Clifford, Hakim Ferroukhi
Nuclear Technology | Volume 208 | Number 4 | April 2022 | Pages 711-722
Technical Paper | doi.org/10.1080/00295450.2021.1936879
Articles are hosted by Taylor and Francis Online.
Best estimate plus uncertainty for the safety assessment of nuclear power plant transient requires, among others, estimating the probability density function (PDF) of physical model parameters in thermal-hydraulic system codes. In that context, Bayesian calibration based on experimental data from separate-effect test facilities are increasingly popular to inform the PDF of a single thermal-hydraulic phenomenon. These calibrations are, however, time intensive, especially when considering multiple time-dependent outputs. Calibrating on many tests with different boundary conditions and potentially different phenomena to derive PDFs applicable to complex transients appears intractable, even using hierarchical modeling. In this paper, we start investigating this problem by considering a set of Flooding Experiments with Blocked Arrays reflood tests with different boundary conditions. We use TRACE v5.0p3 to model time- and space-dependent temperature profiles, pressure drops, and liquid carry-over. Global sensitivity analysis helps screen out noninfluential parameters and gain a detailed understanding of the modeled physics of reflood. The analysis shows that, for all tests, the outputs were sensitive to a similar set of influential model parameters. In turn, Bayesian calibration yields similar posterior PDFs for the influential parameters, and forward propagation of these posterior PDFs yields similar confidence intervals. As such, the information of the investigated tests can well be represented by a unique posterior PDF. Such simplifications, although not general, are welcome to help manage the intensive calibration effort necessary for dealing with complex thermal-hydraulic transients encountered in nuclear power plants.