Improving the predictive quality of repository-relevant simulations

Project information
Improving the predictive quality of repository-relevant simulations
  • Bundesgesellschaft für Endlagerung mbH (BGE)
  • 2022/01
  • 3 years
  • In progress
More information
Contact person
Nino Menzel's profile picture
Nino Menzel
PhD researcher
+49 241 / 80 98273

During the last decades, the subsurface below our feet served as source for a variety of natural resources, but also as a storage and deposit medium for waste materials. In 2020, the Bundesgesellschaft für Endlagerung (BGE) founded a project centered around the selection of a final repository site for radioactive waste. The research cluster is composed of six subgroups, each handling different uncertainties in the site selection process. Within the research group SmartMonitoring chairs of RWTH Aachen University and the University of Stuttgart collaborate and follow the overall goal of improving the predictive quality of repository-relevant simulations through optimal data acquisition and monitoring. The main research questions GIM is addressing are:

Which field measurements provide the largest information content for the studies process and where and when should these measurements be acquired?

To answer these questions, SmartMonitoring is expected to develop one benchmark scenario for each possible host rock (rock salt, claystone and crystalline rock) and optimize its predictive quality. While the project partners focus on the development of surrogate modeling techniques, we contribute with process-based monitoring concepts based on those reference cases. Here, we use process predictions to simultaneously optimize monitoring setups using both conventional (e.g., temperature) sensors as well as geophysical source and receiver positions.

In the end, SmartMonitoring will provide a modular computational workflow that is adaptable to any possible host rock scenario in Germany for the evaluation and optimization of processes and measurements.

Project partners
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