|
Will be handed on hard copy.
Also see:
Assistant positions
BSc, MSc, ETc. thesis topics
Assignments are published on Mondays. You submit the solutions the following Monday before the Tutorials. Please us this link to submit solutions to coding problems.
Assignment | Extras | Sample solutions | Due date |
Problem Sheet 1 | MATLAB Templates | Reference solution 1 | Mon, 28.9. |
Problem Sheet 2 |
Templates 2 LehrFEM Tutorial |
Reference solution 2 Solutions to the Coding problem |
Mon, 5.10. |
Problem Sheet 3 |
Reference solution 3 Matlab Code |
Mon, 12.10 |
|
Problem Sheet 4 |
Solution 4 |
Thu, 22. 10. |
|
Problem Sheet 5 |
Templates 5 |
Solution 5 |
Thu 30.10. |
Problem Sheet 6 |
Templates 6 PSOR |
Solution 6 Codes |
Mon, 2. 11. |
Problem Sheet 7 |
Solution 7 |
Mon, 9.11. | |
Problem Sheet 8 |
Templates 8 |
Solution 8 |
Mon, 16.11. |
Problem Sheet 9 |
Templates 9 |
Solutions 9 Solutions to the coding problem |
Mon, 23.11 |
Problem Sheet 10 |
Templates and provided files 10 Mesh data 10 |
Solutions 10 |
Wed, 02.12. |
Problem Sheet 11 |
Solution 11 Krein Rutman and the principal Eigenvalue |
Mon, 14.12. |
|
Problem Sheet 12 |
To be published No post-discussion in tutorials. Questions are to be asked by e-mail. |
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Please find all necessary information here.
The course gives a comprehensive introduction into the numerical treatment of linear and non-linear elliptic boundary value problems and related eigenvalue problems and parabolic evolution problems. Emphasis is on theory and the foundations of numerical methods. Practical exercises involve Matlab implementation of finite element methods.
Participants of the course will become familiar with:
core:
optional:
recommended (but not mandatory):
more useful books:
yet more:
Note: "available online" applies to users in the ETH domain (student computers / ETH WiFi / VPN)
ETH students can download Matlab with a free network license from Stud-IDES
Matlab tutorials, etc.
Programming problems can be submitted either in Python 2.7 or in Matlab. Python is free (even if you are not a student) and easy to learn but more efficient and universal than Matlab.
Find here the Python tutorial for ETH students and here the official Python tutorial.
Relevant packages are NumPy, SciPy and MatPlotLib for plotting.
Find here a short comparison between Matlab and Python.
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