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2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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NRC issues draft EA/FONSI for Duane Arnold restart
Efforts by NextEra Energy to restart the Duane Arnold nuclear power plant as early as 2029 continue to move forward with the Nuclear Regulatory Commission's preliminary environmental assessment and determination that the restart would have no significant environmental impacts.
On Thursday, the NRC posted a draft environmental assessment and a finding of no significant impact for the Palo, Iowa, facility; the Federal Register notice was published on Monday. The Department of Energy’s Office of Energy Dominance Financing is a cooperating agency on the draft EA, as the DOE is considering providing financial assistance to the restart project.
Robert Lawrence Ives, Michael Read, Jeffrey Neilson, Thuc Bui, David Marsden, Thuy Le, Hien Tran
Fusion Science and Technology | Volume 82 | Number 3 | April 2026 | Pages 561-571
Research Article | doi.org/10.1080/15361055.2025.2523609
Articles are hosted by Taylor and Francis Online.
Recent advancements in fusion power have led to focused research on cost-effective electricity generation. While plasma physics studies continue, researchers are also working on practical challenges, such as protecting the reactor walls, managing tritium fuel, and improving plasma heating devices. It is anticipated that electron cyclotron heating will be a primary heating mechanism and that improved gyrotrons will be required. Economical fusion power will require gyrotrons that are lower cost and more efficient than currently available. Key requirements will be efficiency higher than 60% and a radio frequency (RF) output power in waveguide. This will also require advanced power supply systems.
The research here is focused on the development of gyrotron systems suitable for fusion power plants. Development of a multistage depressed collector capable of 70% efficiency is described, as well as the development of an improved output coupler that improves efficiency with a significant reduction in gyrotron system cost. This paper also describes the development of machine Learning algorithms to control the power supplies and maximize efficiency under all gyrotron operating conditions.