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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.
Hangbok Choi, Chang Je Park
Nuclear Science and Engineering | Volume 159 | Number 2 | June 2008 | Pages 153-168
Technical Paper | doi.org/10.13182/NSE159-153
Articles are hosted by Taylor and Francis Online.
Benchmark calculations of Canada deuterium uranium (CANDU) reactor physics design and analysis codes have been performed for a lattice code WIMS-AECL, a supercell code DRAGON, and a core analysis code RFSP by using the physics measurement data of Wolsong nuclear power plants. In this study, the lattice and reactivity device models were examined based on Wolsong-2 measurement data for the criticality and reactivity device worth. Sensitivity calculations were also performed for the number of energy groups and the cross-section library. Using the lattice and reactivity device models obtained from the Wolsong-2 calculation, the benchmark calculations were extended to the Wolsong-3 and Wolsong-4 plants. Compared to a previous study, this study showed that the results of the criticality and reactivity device worth calculations were improved when the material data were updated and the exact two-group cross sections were used. For the three nuclear power plants, the calculated core reactivity was within 0.2% k of criticality. The zone controller unit reactivity worth was estimated to have a maximum error of ~8%. The total reactivity worth of other reactivity control devices was consistent with the measurement data within 13%. The root-mean-square error of the flux distribution calculation was <12% when compared with flux scans performed during Phase B physics tests. In conclusion, the CANDU physics design and analysis codes used in this benchmark study predicted the physics parameters within the allowed uncertainty level of the measurement data.