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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.
Hiroshige Kumamaru
Fusion Science and Technology | Volume 77 | Number 3 | April 2021 | Pages 235-249
Technical Paper | doi.org/10.1080/15361055.2021.1874767
Articles are hosted by Taylor and Francis Online.
Numerical calculations have been performed on liquid-metal magnetohydrodynamic flows through a rectangular channel in the magnetic field inlet region and magnetic field outlet region. The conservation equations of fluid mass and fluid momentum and the Poisson equation for electrical potential have been solved numerically. The numerical calculations have been carried out for Hartmann (Ha) numbers up to the order of 10 000 and a rectangular channel with electrically conducting channel walls. Attention is focused on pressure drops along the flow channel in the magnetic field inlet region and outlet region. The loss coefficients ζ can be represented by for both the magnetic field inlet region and outlet region, where k is a coefficient, and Ha, Re, and β are the Hartmann number, the Reynolds number, and the channel aspect ratio, respectively. The coefficient k depends on the gradient of applied magnetic field in the magnetic field inlet region and outlet region. However, the coefficient k does not change with the Ha number, the Re number, the wall conductivity number, and the aspect ratio very much.