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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.
Inhyung Kim, HyeonTae Kim, Yonghee Kim
Nuclear Science and Engineering | Volume 194 | Number 1 | January 2020 | Pages 14-31
Technical Paper | doi.org/10.1080/00295639.2019.1654815
Articles are hosted by Taylor and Francis Online.
This paper presents a systematic way to truncate the high-fidelity Monte Carlo (MC) solution to reduce the computational cost without compromising the essential reliability of the solution. Based on the fine-mesh finite difference (FMFD) acceleration for the MC analysis, the deterministic truncation of the Monte Carlo (DTMC) solution method is developed and investigated for a systematic approximation to the MC solution of the reactor eigenvalue problem. This deterministic solution is used for the acceleration of the MC simulation as well as the solution prediction itself. The concept, motivations, and challenges of the DTMC method are described in detail, and theoretical backgrounds of the FMFD method are discussed. In addition, an unbiased ratio estimator for more accurate FMFD parameter generation and a modified particle ramp-up method for the determination of optimal generation size in the MC simulation are also introduced and explained. Both the C5G7 benchmark and a small modular reactor (SMR) core are analyzed to characterize the numerical performance of the DTMC method in this work. Convergence behavior of the fission source distribution is examined, and reactor parameters such as the multiplication factor and three-dimensional pin power distribution are estimated and compared to the reference solution. The stochastic features of the DTMC solutions are also discussed in terms of the apparent and real standard deviations. For the pin power distribution, the root-mean-square error and relative error for the reactor core are also evaluated and compared. The computing time and figure of merit are compared for each method.
