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SF2528 Numerical Methods for Differential Equations II 7.5 credits

An advanced course on modern numerical methods for partial differential equations.

About course offering

For course offering

Spring 2025 Start 14 Jan 2025 programme students

Target group

Elective for all programmes as long as it can be included in your programme.

Part of programme

Master's Programme, Applied and Computational Mathematics, åk 1, COMA, Conditionally Elective

Periods

P3 (3.5 hp), P4 (4.0 hp)

Duration

14 Jan 2025
2 Jun 2025

Pace of study

25%

Form of study

Normal Daytime

Language of instruction

English

Course location

KTH Campus

Number of places

Places are not limited

Planned modular schedule

Application

For course offering

Spring 2025 Start 14 Jan 2025 programme students

Application code

61636

Contact

For course offering

Spring 2025 Start 14 Jan 2025 programme students

Examiner

No information inserted

Course coordinator

No information inserted

Teachers

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Headings with content from the Course syllabus SF2528 (Autumn 2024–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The course covers numerical treatment of inital value problems and boundary value problems for partial differential equations, including finite element methods and finite volume methods. The focus of the course is specifically on the theoretical and computational understanding of methods based on a weak formulation for linear elliptic, parabolic, and hyperbolic partial differential equations, as well as time discretizations. The course also addresses non-linear hyperbolic partial differential equations and stabilization. The emphasis on different aspects may vary from year to year. The course includes computerlabs and projects with various applications.

Intended learning outcomes

After completing the course, the student shall be able to:

- explain key concepts and fundamental ideas within numerical methods covered in the course, and be able to describe the advantages and limitations of the methods.

- apply and implement the numerical methods covered in the course to solve specific problems involving partial differential equations

- analyze the well-posedness of certain partial differential equations and estimate errors for the methods covered in the course

Literature and preparations

Specific prerequisites

English B / English 6

Completed basic course in numerical analysis (SF1550, SF1544, SF1545 or equivalent)

Completed basic course in differential equations (SF1692, SF1633, SF1683 or equivalent)

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • LABA - Laboratory assignments, 2.0 credits, grading scale: P, F
  • LABB - Laboratory assignments, 2.0 credits, grading scale: P, F
  • TEN1 - Written exam, 3.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

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Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Mathematics, Technology

Education cycle

Second cycle

Add-on studies

No information inserted