This presentation deals with the question of which essential information about a repository for radioactive waste should be delivered to future generations to understand the repository system and support them to fulfill any needs related to the repository. Therefore, a procedure developed during a recent NEA initiative has been applied to the various numbers of records produced during the repository program Konrad. Different tools and approaches to identify essential records have been tested.

The work explores modelling challenges in fractured crystalline rock formations. Addressing safety criteria requires integrating intact rock and fracture properties accurately. The intricate 3D nature of fractures complicates numerical models. Various methods exist, but assumptions lead to uncertainties. The study evaluates modelling approaches with a special focus on their accuracy and efficiency. Comparative calculations aid in understanding their impact.

In the research project presented here, the use of multiple-criterion decision analysis (MCDA) in the German site-selection procedure is discussed. The aim is to explore the applicability for the decision problem to the emplacement concept of high-level radioactive waste (HLW) packages regarding German safety investigations. The expected outcome is a basic decision model that can provide decision support and increase transparency, understanding, and acceptance in the site-selection procedure.

Crystalline rock is a potential candidate for storing nuclear waste in the deep geological underground in Germany. However, fractures within these rocks pose a challenge, as they can create pathways for fluids that might corrode barriers and release radioactive materials into the environment. The exact configuration of these fracture networks is often unknown. Our study aims to better understand and predict these networks by combining existing data with advanced modelling techniques.

Based on the German site selection process for a deep geological repository for high-level radioactive waste, we propose a site-prioritization method based on a multi-criteria decision-making approach and risk estimates for each sub-region. The method takes into account the geological factors as well as the uncertainty associated with the heterogeneous nature of subsurface data quality and quantity, in order to enable stakeholders to make informed decisions during the site selection process.