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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. Segev
Nuclear Science and Engineering | Volume 40 | Number 3 | June 1970 | Pages 424-437
Technical Paper | doi.org/10.13182/NSE70-A20194
Articles are hosted by Taylor and Francis Online.
The relation is proposed as an approximate solution to the asymptotic slowing down equations in an infinite, homogenous, and weakly absorbing mixture of elements, in the energy range of fast-reactor neutrons. q(E) is the slowing down density; a is the absorption ratio Σa/Σt/; sλ(E) and Qλ are, respectively, the scattering ratio Σs,λ/Σt and the excitation energy of the λ'th level; ξ is equal to the average logarithmic energy loss per elastic scattering with the element containing the λ'th level; the sum extends over all elastic (Qλ = 0) and inelastic (Qλ > 0) levels. The above relation is constructed to reduce to the approximate solutions both in the limit of purely elastic scattering and in the limit of inelastic scattering by infinitely heavy scatterers. The relation is shown to be an approximate solution also in intermediate cases, where both target recoil and level excitation are important, provided that the mixture contains a substantial amount of medium-mass or light scatterers. Higher order terms may be included in the relation to better account for the effects of absorption.