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SF2527 Numerical Methods for Differential Equations I 7.5 credits

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Application

For course offering

Autumn 2024 Start 26 Aug 2024 programme students

Application code

52116

Headings with content from the Course syllabus SF2527 (Autumn 2024–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The course will give you knowledge about advanced numerical methods for solving differential equations in engineering and natural science applications. The course explores how these methods are formulated and implemented on a computer, as well as the theory regarding the accuracy, stability, and computational cost of these methods. The course covers numerical methods for ordinary differential equations, finite difference methods for linear partial differential equations, and an introduction to mathematical modeling with differential equations. It includes computer labs and projects with various applications.

Intended learning outcomes

For the differential equations in the course contents, the student shall after completion of course be able to:

- classify and characterize the differential equation, as well as choose an appropriate numerical method to solve it

- analyze numerical methods with respect to computational cost, accuracy and stability

- apply and implement numerical algorithms in a suitable programming langugae, as well as assess the accuracy of numerical results

- explain key concepts and fundamental ideas within numerical methods covered in the course, and be able to apply them to argue for advantages and descibe limitations of the methods

Upon approved completion of the course, the student shall also have the skills to work in a group to solve a numerical problem and to present, discuss, and summarice the problem, solution method, and results clearly.

Literature and preparations

Specific prerequisites

English B / English 6

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

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

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

No information inserted

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 - Laboration, 3.5 credits, grading scale: A, B, C, D, E, FX, F
  • LABB - Laboration, 1.0 credits, grading scale: P, F
  • TEN1 - Written exam, 3.0 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

No information inserted

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