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Denver, CO|Sheraton Denver
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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.
Anthony B. Davis, Alexander Marshak
Nuclear Science and Engineering | Volume 137 | Number 3 | March 2001 | Pages 251-280
Technical Paper | doi.org/10.13182/NSE01-A2190
Articles are hosted by Taylor and Francis Online.
In the atmosphere, multiple scattering matters nowhere more than in clouds, and being a product of its turbulence, clouds are highly variable environments. This challenges three-dimensional (3D) radiative transfer theory in a way that easily swamps any available computational resources. Fortunately, the far simpler diffusion (or P1) theory becomes more accurate as the scattering intensifies, and allows for some analytical progress as well as computational efficiency. After surveying current approaches to 3D solar cloud-radiation problems from the diffusion standpoint, a general 3D result in steady-state diffusive transport is derived relating the variability-induced change in domain-average flux (i.e., diffuse transmittance) to the one-point covariance of internal fluctuations in particle density and in radiative flux. These flux variations follow specific spatial patterns in deliberately hydrodynamical language: radiative channeling. The P1 theory proves even more powerful when the photon diffusion process unfolds in time as well as space. For slab geometry, characteristic times and lengths that describe normal and transverse transport phenomena are derived. This phenomenology is used to (a) explain persistent features in satellite images of dense stratocumulus as radiative channeling, (b) set limits on current cloud remote-sensing techniques, and (c) propose new ones both active and passive.