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Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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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.
Junhao Zhang, Weiwei Chen, Bingyu Ni, Jing Zheng, Kaixin Zhao, Wanyi Tian, Chao Jiang
Nuclear Science and Engineering | Volume 198 | Number 8 | August 2024 | Pages 1668-1681
Research Article | doi.org/10.1080/00295639.2023.2257508
Articles are hosted by Taylor and Francis Online.
During the decommissioning process of nuclear facilities, workers are exposed to radiation and face the risk of exceeding safe dose limits. Ensuring the safety of personnel requires not only enhancing radiation protection measures but also optimizing work paths to minimize exposure time and avoid high-radiation areas. This paper proposes a nested optimization algorithm that combines an ant colony optimization (ACO) with an improved A* algorithm for the decommissioning of a nonradiation source. The algorithm aims to minimize the total radiation dose and transforms the original path optimization problem into an equivalent traveling salesperson problem. The improved A* algorithm is employed in the inner layer to calculate the path with the lowest radiation dose for any given sales order. The ACO operates in the outer layer to determine a set of optimal working paths that traverse all target points. The provided solution example demonstrates that the proposed path optimization algorithm effectively integrates the radiation field and obstacles. It successfully identifies a sequence for dismantling with the lowest dose and corresponding optimal work path while ensuring the completion of the dismantling task. These findings are expected to offer valuable insights for optimizing personnel work paths during the subsequent decommissioning process of nuclear facilities.