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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.
R. D. M. Garcia
Nuclear Science and Engineering | Volume 177 | Number 1 | May 2014 | Pages 35-51
Technical Paper | doi.org/10.13182/NSE13-45
Articles are hosted by Taylor and Francis Online.
The analytical discrete ordinates (ADO) method is used to develop an approximate, but accurate, solution to a one-dimensional model of neutral particle transport in ducts proposed originally by Prinja and Pomraning. The implementation of the ADO method is facilitated by a variable transformation that is used to rewrite the Prinja-Pomraning equation in a form very similar to that of the Bhatnagar-Gross-Krook model equation in rarefied gas dynamics. Techniques of linear algebra are used to find an analytical solution for the linear system that has to be solved for the superposition coefficients of the ADO method in the case of a semi-infinite duct. Numerical results for the reflection and transmission probabilities that illustrate the capability of the method are tabulated for semi-infinite and finite ducts of circular cross section and two types of particle incidence: isotropic incidence and incidence described by the Dirac delta distribution. It is concluded that the ADO method can achieve a desired precision in the reflection and transmission probabilities with a much lower quadrature order than previously used numerical implementations of the discrete ordinates method and consequently is much more efficient.