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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.
Quentin Newell, Charlotta Sanders
Nuclear Science and Engineering | Volume 179 | Number 3 | March 2015 | Pages 253-263
Technical Paper | doi.org/10.13182/NSE13-44
Articles are hosted by Taylor and Francis Online.
The Monte Carlo (MC) method is becoming popular for three-dimensional fuel depletion analyses to compute quantities of interest in used nuclear fuel including isotopic compositions. However, there are some questions concerning the effect of MC uncertainties on predicted results in MC depletion calculations. The MC method introduces stochastic uncertainty in the computed fluxes. These fluxes are used to collapse cross sections, estimate power distributions, and deplete the fuel within depletion calculations; therefore, the predicted number densities also contain random and propagated uncertainties due to the MC solution to the neutron transport equation. The linear uncertainty nuclide group approximation (LUNGA) method was developed to calculate the propagated stochastic uncertainty in the nuclear isotopics, using the time-varying flux subjected to the power normalization constraint. Verification of the LUNGA method demonstrated that the standard deviation in the number densities and infinite multiplication factor (kinf) predicted by this method agree well with the uncertainty obtained from the statistical analysis of 100 different simulations performed with coupled MC depletion calculations. Future research includes (a) expanding the LUNGA methodology to include more nuclides, (b) fully automating the methodology, and (c) investigating the use of an axial segmented fuel rod.