Importance of the global sensitivity analysis in development of metamodels for geotechnical back analysis

This paper investigates the use of global sensitivity analysis during the development of metamodels for back-analysis of geotechnical problems. Variance-based global sensitivity analysis was combined with Particle swarm optimization algorithm and POD-ERBF metamodel to backcalculate the hypothetic (synthetic) problem of anchor-supported excavation. PLAXIS 2D FE code was used for numerical simulations. The results of the back analysis for different sets of model parameters were compared to emphasize the importance of global sensitivity analysis before performing the back analysis and the recommendations for the robust modeling of presented geotechnical problem were given

Compressed air energy storage in porous geological formations: Investigation of storage characteristics and induced impacts

With the rapid growth of energy production from intermittent renewable sources like wind and solar power plants, large-scale energy storage options are required to compensate for fluctuating power generation on different time scales. Compressed air energy storage (CAES) in porous geological formations is seen as a promising underground storage option for balancing short-term diurnal fluctuations. CAES is a power-to-power energy storage, which converts electricity to mechanical energy, i.e. highly pressurized air, and stores it in the subsurface. This thesis aims at investigating the feasibility, dimensioning the storage capacity, and assessing the induced hydraulic, thermal and geochemical impacts of a large-scale CAES operation in porous formations. For this, scenario based numerical simulations are used