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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.
Gary L. Wilson, Roger A. Rydin, Seppo Orivuori
Nuclear Technology | Volume 82 | Number 1 | July 1988 | Pages 94-105
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT88-A34120
Articles are hosted by Taylor and Francis Online.
Two highly efficient nonlinear time-dependent heat conduction methodologies, the nonlinear time-dependent nodal integral technique (NTDNT) and IVO-HEAT, developed by Imatran Voima Oy, are compared using one- and two-dimensional time-dependent benchmark problems. The NTDNT is completely based on newly developed time-dependent nodal integral methods, whereas IVOHEAT is based on finite elements in space and Crank-Nicolson finite differences in time. IVOHEAT contains the geometric flexibility of the finite element approach, whereas the nodal integral method is constrained at present to Cartesian geometry. For test problems where both methods are equally applicable, the nodal integral method is approximately six times more efficient per dimension than IVOHEAT when a comparable overall accuracy is chosen. This translates to a factor of 200 for a three-dimensional problem having relatively homogeneous regions, and to a smaller advantage as the degree of heterogeneity increases.