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May 31–June 3, 2026
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.
Kazuo Shin, Kagetomo Miyahara, Eiji Tanabe, Yoshitomo Uwamino
Nuclear Science and Engineering | Volume 120 | Number 2 | June 1995 | Pages 136-145
Technical Note | doi.org/10.13182/NSE95-A24114
Articles are hosted by Taylor and Francis Online.
Generalized parameterization of the differential thick-target neutron yield (TTNY) is obtained by studying systematics in the differential TTNY based on moving source parameters deduced from experimentally obtained differential TTNYs for light and heavy ions. The yields of equilibrium neutrons (ENs) and nonequilibrium neutrons (NENs) are expressed by simplified expressions. The variation of the nuclear temperature of the EN is scaled with the excitation energy transferred to the target-like fragment. The nuclear temperature of the NEN is reproduced fairly well by the Fermi gas model. The scaling of the velocity parameter of the EN is considered based on the breakup fusion mechanism. The velocity of the NEN component is compared with the corresponding data for the proton emission. The velocity is related to the relative speed between projectile and target nuclei at contact.