DTN

The high complexity of deep geological repositories as a consequence of the interplay of chemical, physical, and geological boundary conditions and processes, combined with stringent safety requirements and long time scales, poses a major challenge for the safety case. Both the cross-scale simulation of various coupled processes and the visualization and communication of the results must be adequately addressed. Approaches from artificial intelligence, and in particular the “digital twin” (DT) technology, are well-suited for this purpose. The transfer and further development of existing approaches for holistic close-to-reality descriptions of the evolution of repository systems in the form of DTs offer a wide range of applications, e.g. with regard to consequence analyses, optimisation of repository systems, uncertainty and sensitivity analyses, and the reduction of uncertainties in safety analyses, as well as for identifying knowledge gaps and prioritizing future research efforts.

The focus of the exploratory project DTN is on selected subsystems of a deep geological repository, specifically examining the host rock formation clay rock (Excavation Damaged Zone and repository far field) and the geotechnical barrier bentonite in contact with (metallic) waste containers. The work carried out at IFN-2 focuses on accelerating geochemical models and reactive transport simulations using various surrogate models, which is necessary for the implementation of DTs.