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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.
Edward W. Larsen, J. E. Morel, John M. McGhee
Nuclear Science and Engineering | Volume 123 | Number 3 | July 1996 | Pages 328-342
Technical Paper | doi.org/10.13182/NSE123-328
Articles are hosted by Taylor and Francis Online.
The multigroup P1 and simplified PN (SPN) equations are derived by an asymptotic expansion of the multigroup transport equation with anisotropic scattering. The P1 equations are the leading-order approximation in this expansion; the SPN equations for N = 2,3,… are increasingly higher order approximations. The physical assumptions underlying these approximations are that the material system is optically thick, the probability of absorption is small, and the mean scattering angle is not close to unity. For multigroup isotropic scattering transport problems, a dispersion analysis is given that verifies the accuracy of the SPN approximations. Numerical comparisons of P1, SPN, and SN solutions are also given. These comparisons show that for low N, SPN solutions are significantly more accurate (transportlike) than P1 solutions and are obtained at a significantly lower computational cost than SN solutions.
