SOURCE-LINKED INTELLIGENCE

Pore Scale Multiphase Dynamics Redefining Cyclic Hydrogen Storage from Pores to Reservoir

CORDIS · observation · Publication date unknown

d Tomography will generate unprecedented multi-cycle hydrogen-brine datasets under realistic boundary conditions. These datasets will be analyzed using morphology- and topology-aware descriptors with machine learning methods to capture interfacial memory, stability, and flow regime transitions. Insights will underpin new hysteresis-energy coupling models and dynamic flow functions, enabling reservoir-scale simulations that account for path dependence and dissipation. The project addresses Horizon Europe MSCA priorities on climate action, clean energy transition, and innovation-driven growth. Scientifically, it will deliver open-access benchmark datasets, reproducible workflows, and transferable methods for porous media research. Technologically, it will provide cycle-aware modelling tools for direct integration into industrial simulators, reducing risk and improving operational efficiency. Societally, this project directly supports the European Green Deal, Hydrogen Strategy, and REPowerEU, enabling reliable renewable integration, reducing fossil fuel reliance, and strengthening Europ

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recordType

award

status

SIGNED

region

EU

value

263393.28

unit

EUR