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Conference Spotlight
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.
John A. Andersen
Nuclear Technology | Volume 72 | Number 1 | January 1986 | Pages 75-83
Technical Paper | Radioactive Waste Management | doi.org/10.13182/NT86-A33755
Articles are hosted by Taylor and Francis Online.
A method is presented for correlating a tracer gas leakage rate to the potential particulate radioactive material (RAM) release from packages for the shipment of RAM, for those cases where a gas leak measurement is used and there is no measurable particulate release. The correlation method involves a calculational technique relating the measured gas leakage to capillary flow, then to the design and dimensions of the actual seal, and then to the minimum size of the particulate material being contained. Numerous examples are cited. This method is useful both in the evaluation of results obtained during regulatory-required testing, and in the process of applying for package certification or licensing. It is indicated that relatively large measured leaks in containment vessels may be analogous to extremely small defects in the actual seal, and to minute releases of RAM.