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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.
D. Vezinet, D. Mazon, D. Clayton, R. Guirlet, M. O'Mullane, D. Villegas
Fusion Science and Technology | Volume 63 | Number 1 | January 2013 | Pages 9-19
Selected Paper from Seventh Fusion Data Validation Workshop 2012 (Part 3) | doi.org/10.13182/FST12-475
Articles are hosted by Taylor and Francis Online.
To obtain a fast estimation of the total impurity density distribution in a poloidal cross section from soft X-ray (SXR) measurements during quasi-stationary phases, the possibility that ionization equilibrium may have little influence on the emissivity profile of Ni and Fe in the core region of tokamak plasmas is investigated. Preliminary and encouraging results that support this assumption under certain conditions are found. A simplified approach aimed at computing a satisfactory estimation of the total density of a unique and identified impurity directly from an absolutely calibrated SXR tomographic inversion is implemented. An example of application to a previously and independently performed transport simulation of a Ni injection in Tore Supra is then given.