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Conference Spotlight
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.
David Reger, Elia Merzari, Paolo Balestra, Sebastian Schunert, Yassin Hassan, Haomin Yuan, Yu-Hsiang Lan, Paul Fischer, Misun Min
Nuclear Technology | Volume 209 | Number 1 | January 2023 | Pages 90-104
Technical Paper | doi.org/10.1080/00295450.2022.2108688
Articles are hosted by Taylor and Francis Online.
Packed beds play an important role in many engineering fields, with their applications in nuclear energy being driven by the development of next-generation reactors utilizing pebble fuel. The random nature of a packed pebble bed creates a flow field that is complex and difficult to predict. Porous media models are an attractive option for modeling pebble-bed reactors (PBRs), as they provide intermediate fidelity results and are computationally efficient. Porous media models, however, rely on the use of correlations to estimate the effect of complicated flow features on the pressure drop and heat transfer in the system. Existing correlations were developed to predict the average behavior of the bed, but they are inaccurate in the near-wall region where the presence of the wall affects the pebble packing.
This work aims to investigate the accuracy of a porous media model using the Kerntechnischer Ausschuss (KTA) correlation, the most common pressure drop correlation for PBRs compared to the high-fidelity large eddy simulation (LES). A bed of 1568 pebbles is investigated at Reynolds numbers from 625 to 10 000. The bed is divided into five concentric subdomains to compare the average velocity, friction losses, and form losses between the porous media and LES codes. The comparison between the LES simulation and the KTA correlation revealed that the KTA correlation largely underpredicts the form losses in the near-wall region, leading to an overprediction of the velocity near the wall by nearly 30%. An investigation of the form losses across the range of Reynolds numbers in the LES results provided additional insight into how the KTA correlation may be improved to better predict these spatial effects in a pebble bed. These data suggest that the form coefficient near the wall must be increased by 48% while decreasing the form coefficient of the inner bulk region of the bed by 15%. The implementation of these improvements to the KTA correlation in a porous media model produced a radial velocity profile that saw significantly improved agreement with the LES results.