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Tech giants and nuclear leaders make news at CERAWeek
Microsoft and Nvidia have formed an “AI for nuclear” partnership intended to streamline the permitting, design, and operations of nuclear power plant facilities, and highlighted the collaboration at CERAWeek 2026 in Houston earlier this week.
Microsoft said in an announcement that the collaboration will build a “connected, AI-powered foundation” of AI tools that energy developers will be able to use to make work “repeatable, traceable, secure, and predictable,” all the while reducing work timelines and maintaining safety.
Kevin R. Robb, Judith M. Cuta, L. Paul Miller
Nuclear Technology | Volume 199 | Number 3 | September 2017 | Pages 289-298
Technical Paper | doi.org/10.1080/00295450.2017.1346446
Articles are hosted by Taylor and Francis Online.
In the United States, approximately 2500 casks are loaded with commercial spent nuclear fuel (SNF) that has transitioned from wet storage (spent fuel pools) to dry storage. The number of loaded dry storage casks is increasing by approximately 200 each year. Over time, cask designs have evolved to enhance safety and to accommodate more fuel and higher heat loads. Also, higher burnup fuel is being transitioned into dry storage. The SNF is being stored in dry casks for longer times than specified in the original certification period. Several degradation mechanisms related to fuel assemblies and canisters are affected by temperature. For the cladding, temperature-dependent phenomena include creep and annealing, hydride reorientation and embrittlement, and the ductile-to-brittle transition. Temperature can also influence phenomena that affect the long-term integrity of the storage system, including deliquescence, corrosion, and stress-corrosion cracking. Therefore, accurate determination of the temperatures of various components is needed to evaluate potential safety-related issues during transportation after extended storage and to ensure SNF retrievability. The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is being developed for the U.S. Department of Energy Office of Nuclear Energy to streamline analyses for the waste management system [Nucl. Technol., Vol. 195, p. 124 (2017)]. The thermal analysis capability within UNF-ST&DARDS and example results are discussed herein.