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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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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.
Carol Braester, Roger Thunvik
Nuclear Technology | Volume 79 | Number 3 | December 1987 | Pages 371-376
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT87-A34026
Articles are hosted by Taylor and Francis Online.
An analysis of the confidence of flow solutions for stochastically generated hard rock formations study was carried out with the aid of a simplified synthetic model. The formation was conceptualized as a fracture network with a known geometric structure intersecting an impervious mass rock while fracture permeability was considered a stochastic process. Safety analysis of radioactive waste repositories includes prediction of travel times of possibly contaminated water particles from the repository to the biosphere. While such calculations require that rock properties, such as permeability, be known over the entire flow domain, only limited information is available in practice, and interpolation methods are called for. An a priori model was constructed as a first step, with fracture permeabilities generated according to a given probability distribution; this a priori model was considered the “true” formation. In a second step, a limited amount of information, similar to that obtained in reality from boreholes, was used to construct a conditioned-by-measurement model. Identical flow tests were performed on formations represented by the two models, and the flow rate ratios resulting from these tests served as the measure of confidence of the stochastically generated formation. Results with a two-dimensional flow domain and a particular data set, show uncertainty values between 46 and 61%, corresponding to borehole spacing from 10 to 100 m intersecting 11 and 2%, respectively, of the total number of fractures in the network. Results with a three-dimensional flow domain show uncertainty values between 17 and 50%, corresponding to borehole spacing from 25 to 100 m intersecting 0.2 and 0.02%, respectively, of the total number of fractures. Calculations indicate that stochastically generated formation properties may lead to nonconservative results. This suggests that overestimation methods such as using permeability values obtained from an envelope passing through the highest values should be employed in order to obtain conservative results.