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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.
J. S. Hendricks, R. C. Brockhoff
Nuclear Science and Engineering | Volume 116 | Number 4 | April 1994 | Pages 269-277
Technical Paper | doi.org/10.13182/NSE94-A18986
Articles are hosted by Taylor and Francis Online.
The performance of seven computer platforms is evaluated with the widely used and internationally available MCNP4A Monte Carlo radiation transport code. All results are reproducible and are presented in such a way as to enable comparison with computer platforms not in the study. We observe that the HP/9000–735 workstation runs MCNP 50% faster than the Cray YMP 8/64. Compared with the Cray YMP 8/64, the IBM RS/6000–560 is 68% as fast, the Sun Sparc10 is 66% as fast, the Silicon Graphics ONYX is 90% as fast, the Gateway 2000 model 4DX2–66V personal computer is 27% as fast, and the Sun Sparc2 is 24% as fast. In addition to comparing the timing performance of the seven platforms, we observe that changes in compilers and software over the past 2 yr have resulted in only modest performance improvements, hardware improvements have enhanced performance by less than a factor of ∼3, timing studies are very problem dependent, MCNP4A runs about as fast as MCNP4.