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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.
S. Satake, H. Sawamura, M. Kimura, T. Kunugi
Fusion Science and Technology | Volume 68 | Number 3 | October 2015 | Pages 640-643
Technical Paper | Proceedings of TOFE-2014 | doi.org/10.13182/FST14-956
Articles are hosted by Taylor and Francis Online.
In this work, a simulation is presented that plays an important part in estimating the characteristics of cooling in a blanket used for high-temperature plasma in a fusion reactor. The objective of this study is to perform a large-scale direct numerical simulation (DNS) on the heat transfer of turbulent flow of the coolant materials assumed gas flow. The coolant flow conditions in a fusion reactor are assumed to be defined by a Reynolds number of a higher order. To investigate the effect of Reynolds number on the scalar structures, the Reynolds number based on a friction velocity and a pipe radius was set to be Reτ = 1050. The numbers of the computational grid points used for Reτ= 1050 were 2048 × 512 × 768 in the z−, r−, and ϕ-directions, respectively. In this work, details on the turbulent quantities such as the mean flow, turbulent stresses, turbulent kinetic energy budget, and the turbulent statistics were obtained.