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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.
Sheida Saeidi, Sergey Smolentsev, Mohamed Abdou
Fusion Science and Technology | Volume 68 | Number 2 | September 2015 | Pages 282-287
Technical Paper | Proceedings of TOFE-2014 | doi.org/10.13182/FST14-964
Articles are hosted by Taylor and Francis Online.
The present study addresses corrosion of RAFM steel in the flowing eutectic alloy PbLi in a special case of the 1-D magnetohydrodynamic Hartmann flow, where the liquid metal flows in a wall-normal magnetic field. For this flow, the effect of a magnetic field on corrosion and transport of corrosion products are studied analytically, using a self-similar mass transfer model, and numerically. The results are presented in the form of the dimensionless mass transfer coefficient (the Sherwood number, Sh) as a function of dimensionless flow parameters, the Reynolds (Re) and the Hartmann (Ha) numbers. In turbulent flows, Sh decreases as Ha increases due to turbulence suppression by a magnetic field. In laminar flows, Sh slightly increases with the magnetic field due to formation of steep velocity gradients at the Hartmann wall. The obtained results are then applied to analysis of corrosion for a family of PbLi blankets.