Permafrost underlies a quarter of the Northern Hemisphere and is thawing rapidly due to global warming. This has major consequences for ecosystems, water resources, infrastructure stability and long-term economic costs. Anticipating these changes through numerical modelling is essential for supporting resilient Arctic environments and communities.
The PERMACHANGE project is developing a site-scale hybrid digital twin of permafrost, combining high-performance computing, hybrid modelling and machine-learning-based soil mechanics surrogate models. This approach enables efficient, high-fidelity simulations of subsurface heat and water transfer, as well as terrain stability, under thawing conditions.
This PhD aims at adding soil mechanics (M) simulation capabilities to the TH hybrid twin. The detailed objectives are: (1) simulating the effect of temperature change on geotechnical infrastructures, and (2) building a mechanical surrogate model.
For further information, see the attached [PDF].