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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.
Y. Sawada, M. Toma, Y. Homma, W. Sato, T. Furuta, S. Yamoto, A. Hatayama
Fusion Science and Technology | Volume 63 | Number 1 | May 2013 | Pages 352-354
doi.org/10.13182/FST13-A16952
Articles are hosted by Taylor and Francis Online.
Understanding and control of impurity transport is one of the important issues to reduce the impurity in fusion plasmas. Being based on the Binary Collision Monte-Carlo Model (BCM), a numerical model for classical/neo-classical cross field transport of impurity ions in magnetic fusion devices is being developed. The purpose of the present study is to examine, step by step, whether our proposed model correctly reproduces 1) classical and 2) neo-classical transport processes of impurity ions. The numerical results agree well with theoretical values by classical theory. Not only self-diffusion, but also impurity flow in the direction along the background density gradient has been reproduced. In addition, good agreement of diffusion coefficient with neoclassical theory has been obtained in the wide range of collisionality parameter in a simple tokamak magnetic configuration.