After decades of focusing on disposal of radioactive waste in unsaturated fractured tuff, the United States’ interest has shifted to alternative host rocks (e.g., clay, crystalline, salt), hydrogeologic conditions (i.e., saturated, reducing), and repository designs (e.g., bentonite backfill and seals). These alternatives are similar to those that have been investigated by international geologic disposal programs in Europe and Asia. Close collaboration with these programs allows U.S. researchers (1) to benefit from a deep knowledge base with regards to alternative repository solutions developed over decades, and (2) to participate in valuable field experiments conducted in operating underground research laboratories (URLs) not currently available in the U.S. To advance international collaboration, the United States disposal program has joined five multinational cooperation initiatives as a formal partner (e.g., the Mont Terri Project, the DECOVALEX Project, the FEBEX-DP Project, the SKB Task Forces), and has established a balanced portfolio of selected R&D projects collaborating with international peers. These projects cover a range of relevant R&D fields like near-field perturbation, engineered barrier integrity, radionuclide (RN) transport, and integrated system behavior.
This presentation gives a brief overview of current R&D activities in the United States disposal research program involving international collaboration, with specific focus on activities that allow participation in field experiments conducted in underground research laboratories (URLs). The joint R&D with international researchers and the access to relevant data/experiments from a variety of URLs and host rocks has significantly improved the current technical basis for disposal in a range of potential host rock environments available in the United States. Comparison with experimental data has contributed to testing and validating predictive computational models for evaluation of disposal system performance in a variety of disposal system concepts. Comparison of model results with other international modeling groups, using their own simulation tools and conceptual understanding, has enhanced confidence in the robustness of predictive models used for performance assessment.