Course syllabus for Partial differential equations, project course

The course has been discontinued
The course syllabus contains changes
See changes

Course syllabus adopted 2019-02-22 by Head of Programme (or corresponding).

Overview

  • Swedish namePartiella differentialekvationer, projektkurs
  • CodeTMA632
  • Credits7.5 Credits
  • OwnerMPENM
  • Education cycleSecond-cycle
  • Main field of studyMathematics
  • DepartmentMATHEMATICAL SCIENCES
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language English
  • Application code 20113
  • Open for exchange studentsYes

Credit distribution

0101 Examination 7.5 c
Grading: TH		 7.5 c

In programmes

Examiner

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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.

The course syllabus contains changes

  • Changes to course:
    • 2020-03-12: Discontinued Changed to discontinued by UOL
      The course is discontinued