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Docker image combining Underworld2 & Badlands
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Underworld 2

Underworld 2 is a python-friendly version of the Underworld code which provides a programmable and flexible front end to all the functionality of the code running in a parallel HPC environment. This gives signficant advantages to the user, with access to the power of python libraries for setup of complex problems, analysis at runtime, problem steering, and multi physics coupling. While Underworld2 embraces Jupyter Notebooks as the preferred modelling environment, only standard python is required.

The Underworld2 development team is based in Melbourne, Australia at the University of Melbourne and at Monash University led by Louis Moresi. We would like to acknowledge AuScope Simulation, Analysis and Modelling for providing long term funding which has made the project possible. Additional funding for specific improvements and additional functionality has come from the Australian Research Council ( The python toolkit was funded by the NeCTAR eresearch_tools program. Underworld was originally developed in collaboration with the Victorian Partnership for Advanced Computing.

Lastest stable release (master branch)

Development branch - compile | unit tests |

Getting Underworld2

The Underworld2 docker container is the recommended method of installation for Windows, Mac OSX and Linux. It is available through the docker hub:

Please check our blog page for a writeup on using dockers:

If you need to compile Underworld2 (in particular for HPC usage), please refer to

Underworld Docker Usage

To access Underworld2 examples, run the following command,

   docker run -p 8888:8888 underworldcode/underworld2

and then (Linux users) browse to http://localhost:8888. For Windows/Mac, your docker containers will be run within a VM. To determine the address of this VM, check the output of:

   docker-machine ip default 

So, for example, you may need to browse to


Note that basic usage metrics are dispatched when you use Underworld. To opt out, set the UW_NO_USAGE_METRICS environment variable. See for full details.

Bedtime reading

Moresi, L., Dufour, F., and Muhlhaus, H.B., 2002, Mantle convection modeling with viscoelastic/brittle lithosphere: Numerical methodology and plate tectonic modeling: Pure And Applied Geophysics, v. 159, no. 10, p. 2335–2356, doi: 10.1007/s00024-002-8738-3.

Moresi, L., Dufour, F., and Muhlhaus, H.B., 2003, A Lagrangian integration point finite element method for large deformation modeling of viscoelastic geomaterials: Journal of Computational Physics, v. 184, no. 2, p. 476–497.

Moresi, L., Quenette, S., Lemiale, V., Mériaux, C., Appelbe, W., Mühlhaus, 2007, Computational approaches to studying non-linear dynamics of the crust and mantle: Phys. Earth Planet. Inter, v. 163, p. 69–82, doi: 10.1016/j.pepi.2007.06.009.

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