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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.
Robert P. Martin
Nuclear Technology | Volume 193 | Number 1 | January 2016 | Pages 96-112
Technical Paper | Special Issue on the RELAP5-3D Computer Code | doi.org/10.13182/NT14-143
Articles are hosted by Taylor and Francis Online.
This paper reviews the historical and contemporary precedence regarding the development of knowledge, its reformulation in computer codes, and subsequent application in decision making. It highlights the practical challenges of this process as it applies to the investigation of engineered systems to deliver on both promised benefits and protection from postulated failures. A model for demonstrating model content, completeness, and consistency is described, invoking and extending a knowledge/content model attributed to Popper. While the specific example examining the evolution of the thermal-hydraulic knowledge base applied for nuclear power plant safety analysis and its capture in the RELAP series of computer analysis codes is presented, the framework is general, true to the scientific method, and thus broadly applicable. It concludes that while content of our knowledge base is perpetually increasing, completeness and consistency are fundamentally unattainable; however, within a well-designed evaluation methodology, measurable proof, sufficient for regulatory deliberation, is possible.