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The DOE’s plan for AI in NRC licensing
The Department of Energy announced the completion of a proof-of-concept demonstration of the use of Everstar’s AI tool to generate chapter 5 of an NRC license application from preliminary safety documents.
The 208-page document was created by the AI tool in approximately one day. According to the DOE, it would typically take a team of people between four and six weeks to complete this work.
Frederick A. Haas, Anantanarayanan Thyagaraja
Fusion Science and Technology | Volume 31 | Number 2 | March 1997 | Pages 159-168
Technical Paper | Plasma Engineering | doi.org/10.13182/FST97-A30818
Articles are hosted by Taylor and Francis Online.
An important issue infusion power plant design involves the effect of sawteeth on power transients and ash removal. A model was previously presented for sawtooth oscillations in tokamaks based on a thermal instability mechanism mediated by turbulence in the q < 1 core. This model has been validated against current machines such as the Joint European Torus (JET) and the Tokamak Experiment for Technol.ogy-Oriented Research (TEXTOR). Here, it is adapted to include effects of alpha particle heating in a reacting plasma. The goal is to study the interaction between fusion reactions and the sawtooth turbulence dynamics. The alpha particle heating rate function is sensitive to temperature variations and could possibly result in a thermal instability mechanism for amplifying sawtooth temperature fluctuations under typical conditions. Taking International Thermonuclear Experimental Reactor (ITER)-like conditions as an example, calculations are performed to illustrate this generic behavior. These conditions suggest that while the sawteeth are effective in helium ash removal from the q < 1 region, they can produce significant spikes in the alpha power.