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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Deep geologic repository progress—2025 Update
Editor's note: This article has was originally published in November 2023. It has been updated with new information as of June 2025.
Outside my office, there is a display case filled with rock samples from all over the world. It contains a disk of translucent, orange salt from the Waste Isolation Pilot Plant near Carlsbad, N.M.; a core of white-and-bronze gneiss from the site of the future deep geologic repository in Eurajoki, Finland; several angular chunks of fine-grained, gray claystone from the underground research laboratory at Bure, France; and a piece of coarse-grained granite from the underground research tunnel in Daejeon, South Korea.
Ahmad Al Rashdan, Vivek Agarwal
Nuclear Technology | Volume 205 | Number 8 | August 2019 | Pages 1053-1061
Technical Paper – Special section on Big Data for Nuclear Power Plants | doi.org/10.1080/00295450.2019.1601469
Articles are hosted by Taylor and Francis Online.
The migration of paper-based work packages to an electronic version for the nuclear power industry results in opportunities for work optimization through data analytics and integration. This can only be achieved if the work package is broken into its data elements and stored in a structured data form. The contribution of this paper is the development of a set of guidelines that enables creating a data model from breaking the work package into its data elements. The data model can be used to create a common information model for work packages at nuclear power plants. The results presented and discussed in this paper highlight distinctive data model characteristics regarding the work element properties and associations; work package topology; properties cascade; elements and properties function; templates and instances; and steps flow. In total, 13 guidelines were identified as part of this work. The resulting benefits from the extracted data model are enabling step-level review of the work, reducing planning effort, and automating work package creation and formatting. In addition, coupling work process data with other data sources at the plant improves overall maintenance activity efficiency by enabling capabilities such as real-time schedule update and automatic allocation and release of work resources.