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Syllabus for

Academic year
The course has been discontinued 
TMA632 - Partial differential equations, project course  
Partiella differentialekvationer, projektkurs
 
Syllabus adopted 2019-02-22 by Head of Programme (or corresponding)
Owner: MPENM
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: English
Application code: 20113
Open for exchange students: Yes

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0101 Examination 7,5 c Grading: TH   7,5 c    

In programs

MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 2 (elective)

Examiner:

Anders Logg

  Go to Course Homepage


Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

Partial differential equations - first course or equivalent knowledge.

Aim

The course aims at giving a solid introduction to modern theoretical and computational methods for ordinary differential equations (ODE) and partial differential equations (PDE) with training both in theoretical modeling and computational simulations.

Learning outcomes (after completion of the course the student should be able to)

- use and (to some extent) develop software for solving numerically a choice of ODE and PDE.
- in a written report document the model description, the mathematical theory, the numerical models/algorithms, error analysis and numerical examples.
- make an oral presentation of a theoretical and computational investigation.

Content

Duality and adjoint operators. Stability and duality based a posteriori error analysis for ODE. Stability and duality based a posteriori error analysis for PDE. Adaptivity. Computational methods for various types of PDE such as diffusion, convection-diffusion, reaction-diffusion, wave propagation, fluid flow, electromagnetics, and fluid-structure interaction.

Organisation

Some introductory lectures and supervision of projects.

Literature

Computational Differential Equations, K. Eriksson, D. Estep, P. Hansbo and C. Johnson, Studentlitteratur/Cambridge University Press, 1996.
MATLAB, Octave, Puffin/Dolfin (www.bodysoulmath.org), COMSOL MultiPhysics.

Examination including compulsory elements

Two compulsory projects. Oral and written presentations of the projects.


Page manager Published: Mon 28 Nov 2016.