LYNX
LYNX (Lithosphere dYnamics Numerical toolboX) is another multiphysics modelling solution developed within the group of Basin Modelling at GFZ. Lynx is also based on the flexible, object-oriented numerical framework MOOSE (developed at the Idaho National Laboratories).
Lynx is a novel numerical simulator for modelling thermo-poromechanical coupled processes driving the deformation dynamics of the lithosphere. The formulation adopted in Lynx relies on an efficient implementation of a thermodynamically consistent visco-elasto-plastic rheology with anisotropic porous-visco-plastic damage feedback. The main target is to capture the multiphysics coupling responsible for semi-brittle and semi-ductile behaviour of porous rocks as also relevant to strain localization and faulting processes. More information on the governing equations, their derivation and their implementation together with a list of synthetic and real case applications can be found in two publications by Jacquey and Cacace (2019, a,b).
User group
International user community from geosciences
Features
- Object-orientation: flexible modular structure within easy to be extended modules by the user
- Geometric agnosticism: 1D/2D/3D Finite Elements from the user required
- Hybrid parallelism: multi-threading and MPI
- Proved scalability on HPC architectures - JUWELS cluster Module at JSC
Realistic physics-based rheological description of lithosphere deformation dynamics based on:
- Explicit incorporation of the lithosphere visco-elasto-plastic rheology including nonlinear feedback effects from the energetics of the system
- its extension to account for time-dependent brittle behavior via an overstress (viscoplastic) formulation
- Thermodynamically consistent formulation of semi-brittle semi-ductile deformation modes - brittle deformation via damage mechanics and for ductile deformation via a rate-dependent viscoplastic formulation
- Poro-damage feedback via dynamic porosity (volumetric mechanical response)
- Implicit and efficient numerical implementation within a limited amount of internal iterations
- Use of Automatic Differentation techniques to compute the full Jacobian contribution of the system matrix
