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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.
H. Y. Khater, W. F. Vogelsang
Fusion Science and Technology | Volume 19 | Number 3 | May 1991 | Pages 864-869
Advanced Reactor | doi.org/10.13182/FST91-A29453
Articles are hosted by Taylor and Francis Online.
Experimental radionuclide production cross sections have been collected for protons with energy similar to those protons produced in a D-3He fusion reactor. Proton energy-dependent cross sections (Ep < 14.7 MeV) were used along with the proton stopping data of Anderson and Ziegler to produce a proton-induced thick-target radionuclide activation yields library. In its present form, the library contains thick-target yield data for 164 radioactive isotopes. The library has been used in an activation analysis study aimed at investigating the effect of proton-induced activity on the total level of radioactivity generated in Apollo-L2 (a D-3He tokamak fusion power reactor). Because protons have a short range in solid targets, their effect has been noticed only within the first wall of the reactor. Results showed that while neutron-induced specific activity generated in the reactor Tenelon first wall is 8.1 × 107 Ci/m3, proton-induced specific activity only amounted to 6.37 × 105 Ci/m3.
