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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.
Ion Munteanu, Tunc Aldemir
Nuclear Technology | Volume 144 | Number 1 | October 2003 | Pages 49-62
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT03-A3428
Articles are hosted by Taylor and Francis Online.
While techniques have been developed to tackle different tasks in accident management, there have been very few attempts to develop an on-line operator assistance tool for accident management and none that can be found in the literature that uses probabilistic arguments, which are important in today's licensing climate. The state/parameter estimation capability of the dynamic system doctor (DSD) approach is combined with the dynamic event-tree generation capability of the integrated safety assessment (ISA) methodology to address this issue. The DSD uses the cell-to-cell mapping technique for system representation that models the system evolution in terms of probability of transitions in time between sets of user-defined parameter/state variable magnitude intervals (cells) within a user-specified time interval (e.g., data sampling interval). The cell-to-cell transition probabilities are obtained from the given system model. The ISA follows the system dynamics in tree form and braches every time a setpoint for system/operator intervention is exceeded. The combined approach (a) can automatically account for uncertainties in the monitored system state, inputs, and modeling uncertainties through the appropriate choice of the cells, as well as providing a probabilistic measure to rank the likelihood of possible system states in view of these uncertainties; (b) allows flexibility in system representation; (c) yields the lower and upper bounds on the estimated values of state variables/parameters as well as their expected values; and (d) leads to fewer branchings in the dynamic event-tree generation. Using a simple but realistic pressurizer model, the potential use of the DSD-ISA methodology for on-line probabilistic accident management is illustrated.