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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.
M. M. R. Williams
Nuclear Science and Engineering | Volume 160 | Number 2 | October 2008 | Pages 253-260
Technical Paper | doi.org/10.13182/NSE160-253
Articles are hosted by Taylor and Francis Online.
The resonance integrals and associated temperature coefficients in a mixture of graphite and randomly dispersed grains of ThO2 are calculated. Two methods of dealing with the random distribution of grains are used. The first is one developed by Lane, Nordheim, and Sampson, which is based upon a random Dancoff factor, and the second uses the dichotomic Markov process. The numerical results are compared for a range of grain sizes and ranges of temperature. The differences in the two methods do not exceed 4% for resonance integrals and 2.5% for temperature coefficients. Bearing in mind the radically different stochastic procedures involved, it is remarkable and useful to know that the results are so insensitive to the stochastic model used. In addition we give a measure of the variance in the results.