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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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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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The last days of Hallam
The Hallam nuclear power plant, about 25 miles southwest of Lincoln, Neb., was an important part of the Atomic Energy Commission’s Reactor Power Demonstration Program. But in the end, it operated for only 6,271 hours and generated about 192.5 million kilowatt-hours of electric power during its short, 15-month life.
Matthew D. Sweitzer, Thushara Gunda
Nuclear Technology | Volume 210 | Number 9 | September 2024 | Pages 1706-1721
Research Article | doi.org/10.1080/00295450.2023.2229566
Articles are hosted by Taylor and Francis Online.
The siting of nuclear waste is a process that requires consideration of concerns of the public. This report demonstrates the significant potential for natural language processing techniques to gain insights into public narratives around “nuclear waste.” Specifically, the report highlights that the general discourse regarding “nuclear waste” within the news media has fluctuated in prevalence compared to “nuclear” topics broadly over recent years, with commonly mentioned entities reflecting a limited variety of geographies and stakeholders. General sentiments within the “nuclear waste” articles appear to use neutral language, suggesting that a scientific or “facts-only” framing of “waste”-related issues dominates coverage; however, the exact nuances should be further evaluated. The implications of a number of these insights about how nuclear waste is framed in traditional media (e.g., regarding emerging technologies, historical events, and specific organizations) are discussed. This report lays the groundwork for larger, more systematic research using, for example, transformer-based techniques and covariance analysis to better understand relationships among “nuclear waste” and other nuclear topics, sentiments of specific entities, and patterns across space and time (including in a particular region). By identifying priorities and knowledge needs, these data-driven methods can complement and inform engagement strategies that promote dialogue and mutual learning regarding nuclear waste.