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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.
Stephen H. Howden, Bin Lin (Univ of South Carolina), Poh-Sang Lam (SRNL), Travis Knight, Lingyu Yu (Univ of South Carolina)
Proceedings | 2018 International Congress on Advances in Nuclear Power Plants (ICAPP 2018) | Charlotte, NC, April 8-11, 2018 | Pages 706-713
After being placed into storage pools to allow for radioactive decay and cooling, spent nuclear fuel (SNF) is then transferred into bolted or weld-sealed stainless steel canisters and stored in designated facilities, known as Independent Spent Fuel Storage Installations (ISFSIs). These canisters normally are complex in features and large. As the U.S. Department of Energy (DOE) and the U. S. Nuclear Regulatory Commission (NRC) are evaluating the options for fuel cycle strategy, it is expected that the SNF-loaded canisters remain under the dry storage conditions for extended amounts of time. During this time the dry storage cask systems may degrade and lose structural integrity to release hazardous radioactive materials. The concern has prompted the interest in structural health monitoring (SHM) system that can constantly monitor the system.
This paper describes the groundwork of exploring the sensing capabilities of using piezoelectric acoustic emission (AE) sensors to provide real time monitoring for canisters. When a crack is forming and developing, the energy it releases will generate stress waves to propagate around known as the AE in the solids. Those waves, once recorded by sensing instrument, can be used to indicate the location as well as the significance of crack development as previously studied by many researchers. In this study, the AE sensors will be used to perform a proof-of-concept study of AE sensing on a selected facility with complex geometry and structures. The AE events by cracking were simulated using an impact hammer with stainless steel and plastic tips as well as using standard pencil lead breaks (PLB). The AE system was successful in detecting excitation generated with both hammer striking and PLB from which further frequency analysis was performed.