Luisa Fernanda Orozco
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GrainLearning
GrainLearning is a Bayesian uncertainty quantification and propagation toolbox for simulations of granular materials. It is primarily used to infer and quantify parameter uncertainties in computational models from observation data (i.e. inverse analyses or data assimilation).
- Bayesian Inference
- Data assimilation
- Machine learning
- + 2
- Jupyter Notebook
- Python
- PureBasic
- + 1
3
68
openDARTS
Open Delft Advanced Research Terra Simulator is a simulation framework for forward and inverse modelling and uncertainty quantification of multi-physics (thermo-hydro-mechanical-chemical) processes in geo-engineering applications as geothermal, CO2 sequestration, water pumping, and hydrogen storage.
- energy transition
- environmental modelling
- geothermal
- + 3
- C++
- Python
- Cuda
- + 2
4
31