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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.
M. B. Chadwick, P. G. Young, R. E. MacFarlane, M. C. White, R. C. Little
Nuclear Science and Engineering | Volume 144 | Number 2 | June 2003 | Pages 157-173
Technical Paper | doi.org/10.13182/NSE144-157
Articles are hosted by Taylor and Francis Online.
This paper describes model calculations and nuclear data evaluations of photonuclear reactions on isotopes of C, O, Al, Si, Ca, Fe, Cu, Ta, W, and Pb for incident photon energies up to 150 MeV. The calculations, using the GNASH code, include giant-dipole resonance and quasi-deuteron models for photoabsorption. The emission of secondary particles and gamma rays is computed using preequilibrium theory, together with an open-ended sequence of compound nucleus decays using the Hauser-Feshbach theory. The accuracy of the calculated and evaluated cross sections is assessed through extensive comparisons with measured cross sections, average neutron multiplicities, and energy-dependent emission spectra. The evaluated nuclear data files (ENDF) facilitate radiation transport studies of the importance of photonuclear reactions in a number of technologies including photoneutrons produced in electron/photon accelerators, shielding studies, and nondestructive detection of nuclear materials. A companion paper describes developments in the MCNP and MCNPX codes to utilize these data in transport simulations.