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2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
Ivars Neretnieks, Helen Winberg-Wang
Nuclear Technology | Volume 205 | Number 6 | June 2019 | Pages 819-829
Technical Paper | doi.org/10.1080/00295450.2018.1537460
Articles are hosted by Taylor and Francis Online.
In geologic repositories for nuclear waste located in crystalline rocks, the waste is surrounded by a bentonite buffer that in practice is not permeable to water flow. The nuclides must escape by molecular diffusion to enter the seeping water in the fractures of the rock. At high water-seepage rates, the nuclides can be carried away rapidly. The seepage rate of the water can be driven by the regional hydraulic gradient as well as by buoyancy-driven flow. The latter is induced by thermal circulation of the water by the heat produced by radionuclide decay. The circulation may also be induced by salt exchange between buffer and water in the fractures. The main aim of this paper is to explore how salt exchange between the backfill and mobile water in fractures, by buoyancy effects, can increase the escape rate of radionuclides from a repository.
A simple analytical model has been developed to describe the mass transfer rate induced by buoyancy. Numerical simulations support the simple solution. A comparison is made with the regional gradient-driven flow model. It is shown that buoyancy-driven flow can noticeably increase the release rate.