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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.
L. Wu, H. Momota, G. H. Miley
Fusion Science and Technology | Volume 52 | Number 4 | November 2007 | Pages 1056-1060
Technical Paper | Plasma Engineering and Diagnostics | doi.org/10.13182/FST07-A1635
Articles are hosted by Taylor and Francis Online.
Interactions of charge exchange and ionization of fast, low-charged heavy ions are very important in heavy ion beam inertial confinement fusion. These effects are crucial indetermination of the final focusing in the chamber. However, corresponding cross section data is very limited and/or not accurate over the entire range of energies and ions of interest. This paper reports on our recent studies of cross sections for interactions of heavy ions with noble gases. Since a quantum mechanical treatment encounters a complex many-body problem, a classical trajectory Monte Carlo method is employed. The distribution of inner electrons is estimated by a modified Hartree-Fock model for the purpose of decreasing the number of electron orbits calculated, a micro-canonical ensemble for the initial electron probability distribution is introduced to describe quantum mechanical uncertainty. Cross sections are evaluated over a limited energy range; then scaling laws are developed to reflect the change probability for the beam charge state over a larger energy range.