Our society is using the geological subsurface both as a source of different natural resources as well as for storage and deposit of different types of human waste like nuclear waste. However, a complete picture of the subsurface is often not available, since boreholes or geophysical surveys only reveal some aspects of the subsurface. Therefore, complementary physics-based simulations are indispensable to reconstruct the complete picture of thermo-fluid-mechanically coupled processes like groundwater flow or temperature distribution in the subsurface. The simulations offer a pathway to predict possible future behaviors of the analyzed system, for example, the distribution of potentially contaminated groundwater in the future. Such simulation models have to be calibrated with observations and measured data. But it is not clear, which data are best suited for this calibration. Moreover, the fully complexity physical models could require substantial computational time to assess the variety of possible outcomes.
With respect to the search for a nuclear waste deposit, we want to find answers to this question for optimal data acquisition and smart-monitoring strategies. At the end of the project, new methods and approaches should be available that allow to systematically evaluate different data acquisition strategies regarding their value add-on for a specific requirement, like the quantification of radioactive contamination within a region of the subsurface due to contaminated water, and to develop smart-monitoring strategies based on these results. The latter is of eminent importance to ensure the safety of nuclear waste deposits.
Within this project, we have three main goals:
The collaborative research project "Improvement of the predictive quality of simulations related to permanent disposal sites for nuclear waste by optimal data acquisition and smart monitoring" is conducted by the chairs of "Applied Geophysics and Geothermal Energy" and "Methods of Model-based Development in Computational Engineering" of RWTH Aachen University as well as the chair of Stochastic Simulation and Safety Research for Hydrosystems at the University of Stuttgart.