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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.
Gwendolyn J. Chee, Roberto E. Fairhurst Agosta, Jin Whan Bae, Robert R. Flanagan, Anthony M. Scopatz, Kathryn D. Huff
Nuclear Technology | Volume 207 | Number 2 | February 2021 | Pages 182-203
Technical Paper | doi.org/10.1080/00295450.2020.1753444
Articles are hosted by Taylor and Francis Online.
The present U.S. nuclear fuel cycle faces challenges that hinder the expansion of nuclear energy technology. The U.S. Department of Energy identified four nuclear fuel cycle options that make nuclear energy technology more desirable. Successfully analyzing the transitions from the current fuel cycle to these promising fuel cycles requires a nuclear fuel cycle simulator that can predictively and automatically deploy fuel cycle facilities to meet user-defined power demand. This work introduces and demonstrates the demand-driven deployment capabilities in Cyclus, an open-source nuclear fuel cycle simulator framework. User-controlled capabilities such as time-series forecasting algorithms, supply buffers, and facility preferences were introduced to give users tools to minimize power undersupply in a transition scenario simulation. The demand-driven deployment capabilities are referred to as d3ploy. We demonstrate the capability of d3ploy to predict future commodities’ supply and demand, and automatically deploy fuel cycle facilities to meet the predicted demand in four transition scenarios. Using d3ploy to set up transition scenarios saves the user simulation setup time compared to previous efforts that required a user to manually calculate and use trial and error to set up the deployment scheme for the supporting fuel cycle facilities.