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2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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AI and productivity growth
Craig Piercycpiercy@ans.org
This month’s issue of Nuclear News focuses on supply and demand. The “supply” part of the story highlights nuclear’s continued success in providing electricity to the grid more than 90 percent of the time, while the “demand” part explores the seemingly insatiable appetite of hyperscale data centers for steady, carbon-free energy.
Technically, we are in the second year of our AI epiphany, the collective realization that Big Tech’s energy demands are so large that they cannot be met without a historic build-out of new generation capacity. Yet the enormity of it all still seems hard to grasp.
or the better part of two decades, U.S. electricity demand has been flat. Sure, we’ve seen annual fluctuations that correlate with weather patterns and the overall domestic economic performance, but the gigawatt-hours of electricity America consumed in 2021 are almost identical to our 2007 numbers.
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.