NewFrac FEniCSx Training¶
30th March 2020 at Sorbonnes Université¶
This repository contains material for a day-long course on using DOLFINx, the computational problem solving environment of the FEniCS Project. The focus will be on solving problems arising in solid mechanics.
This repository automatically generates a jupyter-book here: https://newfrac.gitlab.io/newfrac-fenicsx-training/
Running the notebooks (to be tested prior to course start)¶
Students should execute the notebooks using a Docker container running on their own computers.
Install Docker following the instructions at https://www.docker.com/products/docker-desktop.
Clone this repository using git:
git clone https://gitlab.com/newfrac/newfrac-fenicsx-training.git
Run
./launch_container.sh.You should be able to see the JupyterLab instance by navigating to https://localhost:8888 in your web browser.
The JupyterLab session will ask you for a token (password). This can be found in the output from the terminal and will look like e.g.
b64972b8b7df3717089c4899bd028f5e2df6a73a845cb250.
Although we recommend using Docker locally, you can also use the cloud-based binder service to execute the notebooks:
Prerequisite knowledge¶
The course will assume basic knowledge of the theory of finite elasticity and finite element methods. We will also assume that the students have taken the NEWFRAC Core School 2021 Basic computational methods for fracture mechanics. Basic knowledge of Python will be assumed, see https://github.com/jakevdp/WhirlwindTourOfPython to brush up if you feel unsure.
Course Schedule¶
0900-1030 Session 1 (1hr30m). Introduction to DOLFINX and linear elasticity.
1030-1045 Break (15m).
1045-1215 Session 2 (1hr30m). Finite elasticity
1215-1315 Lunch (1hr).
1315-1445 Session 3 (1hr30m). Solver for Variational Inequalities. Variational theory of fracture.
1445-1500 Break. (15m).
1500-1630 Session 4 (1hr30m). Variational theory of fracture or DOLFINX in parallel.
Instructors/Authors¶
Jack S. Hale, University of Luxembourg. Corrado Maurini, Sorbonnes Université.
Acknowledgements¶
The funding received from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No. 861061-NEWFRAC is gratefully acknowledged.