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2026 ANS Annual Conference
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.
David Hanlon, Nigel Smith, Jim Gulliford
Nuclear Science and Engineering | Volume 145 | Number 1 | September 2003 | Pages 120-131
Technical Paper | doi.org/10.13182/NSE03-A2368
Articles are hosted by Taylor and Francis Online.
Modern nuclear criticality safety analysis places great reliance on calculations performed using computer codes, in particular, those employing the Monte Carlo method of solution. In the United Kingdom the acknowledged standard Monte Carlo code for criticality safety assessment is MONK. The accuracy achievable with MONK is ultimately governed by the accuracy of the nuclear data employed and their representation within the code nuclear data library. The U.K. industry uses JEFF-based libraries, taking advantage of modern nuclear data evaluations. Following the release of a frozen version of the library (JEF2.2), a program of work was undertaken in the United Kingdom to develop nuclear data libraries for use in reactor physics, shielding, and criticality application codes and to provide benchmark evidence to support their use. For criticality, this involved developing a hyper-fine-group energy library for the MONK code and undertaking a large program of comparison calculations for selected international experiments. A significant contribution to this validation effort has been the high-quality experimental data from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) International Handbook of Evaluated Critical Safety Benchmark Experiments. This paper summarizes the work involved in arriving at the current stage whereby the use of MONK in conjunction with a JEF2.2-based library is accepted within the U.K. nuclear industry. Specific examples are given, where ICSBEP has provided experimental evaluations for application areas previously unsupported by more traditional experimental data sources.