Editorial: Sorption processes in nuclear waste management: data knowledge management and new methodologies for data acquisition/prediction

Journal Article · 02 August 2023 · Frontiers in Nuclear Engineering

DOI: https://doi.org/10.3389/fnuen.2023.1185038 · OSTI ID:2202537

García, David ^[1]; Dagnelie, Romain V. H. ^[2]; Zavarin, Mavrik ^[3]

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1. Amphos 21, Barcelona (Spain)
2. Alternative Energies and Atomic Energy Commission (CEA), Paris (France)
3. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

A fundamental approach to Nuclear Waste Repository research involves the collection of experimental data in a laboratory setting, development of empirical and/or mechanistic numerical models representing those observations, and application of these models (or Reduced Order Models) into reactive transport and performance assessment models as predictive tools for informing society of impacts and risks associated with nuclear waste repository scenarios (Stevens et al., 2020). Therefore, the assimilation and interpretation of experimental data must take advantage of both new data and the rich historical data available in the literature and apply novel modeling approaches to improve predictive tools, particularly from the standpoint of uncertainty quantification, for nuclear waste repository performance assessment (Zavarin et al., 2022).

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Nuclear Energy (NE), Office of Spent Fuel and Waste Disposition. Office of Spent Fuel and Waste Science and Technology
• Grant/Contract Number: AC52-07NA27344
• OSTI ID: 2202537
• Report Number(s): LLNL--JRNL-846216; 1070465
• Journal Information: Frontiers in Nuclear Engineering, Journal Name: Frontiers in Nuclear Engineering Vol. 2; ISSN 2813-3412
• Publisher: Frontiers Media S.A.Copyright Statement
• Country of Publication: United States
• Language: English