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2026 Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Can AI deliver nuclear on time and on budget? These companies think so.
AI for energy, and energy for AI: that is the new refrain. But can nuclear power plants be deployed at the pace needed for substantial and timely contributions to the energy infrastructure? For Westinghouse, delivering its AP1000 on time and on budget in the United States is a challenge not yet accomplished, while newcomers like Aalo Atomics are turning to AI to speed design, permitting, and construction.
Joe L. Ratigan
Nuclear Technology | Volume 67 | Number 2 | November 1984 | Pages 228-244
Technical Paper | Radioactive Waste Management | doi.org/10.13182/NT84-A33513
Articles are hosted by Taylor and Francis Online.
Emplacement of commercial high-level radioactive waste in an underground repository in salt may result in the transport of brine from the rock salt to the metal surfaces of the waste package. The input parameters necessary to examine this phenomena are not precisely known; however, ranges in the input parameters can be estimated. Using a coupled finite element model for brine transport, the input parameters are treated as stochastic quantities to obtain the range in brine quantities that may come in contact with the waste package. The range in brine quantities is broad, but a major portion of the range can be attributed to the range in only three input quantities.