Numerical treatment of initial value problems, boundary value problems and eigenvalue problems for ordinary and partial differential equations. The emphasis on different parts may vary from year to year. Relevant linear algebra, well-posedness, convergence, stability, error estimates, finite differences, finite elements, finite volumes, method of lines, modern iterative methods, problems with shocks. Computer labs and application oriented projects.
FSF3567 Numerical Solutions of Differential Equations 7.5 credits
Information per course offering
Information for Spring 2024 Start 16 Jan 2024 programme students
- Course location
KTH Campus
- Duration
- 16 Jan 2024 - 3 Jun 2024
- Periods
- P3 (3.7 hp), P4 (3.8 hp)
- Pace of study
25%
- Application code
60862
- Form of study
Normal Daytime
- Language of instruction
English
- Course memo
- Course memo is not published
- Number of places
Places are not limited
- Target group
PhD students only.
- Planned modular schedule
- [object Object]
- Schedule
- Schedule is not published
- Part of programme
- No information inserted
Contact
Anders Szepessy (szepessy@kth.se)
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus FSF3567 (Spring 2019–)Content and learning outcomes
Course contents
Intended learning outcomes
The course gives the students knowledge of problem classes, basic mathematical and numerical concepts and properties, modern numerical methods, and software for solution of engineering and scientific problems formulated as differential equations.
After successful completion of course requirements the students will be able to
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design, implement and use numerical methods for computer solution of scientific problems involving differential equations;
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follow specialized and application-oriented technical literature in the area;
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understand properties of different classes of differential equations and their impact on solutions and proper numerical methods;
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use commercial software with understanding of fundamental methods, properties, and limitations
Literature and preparations
Specific prerequisites
A Master degree including 45 university credits in Mathematics or Information Technology. English B, or equivalent.
Recommended prerequisites
Equivalent to SF2520/DN2221/DN2222 Applied Numerical Methods.
Equipment
Literature
To be announced at least 4 weeks before course start at course web page.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- LAB1 - Laboratory work, 3.5 credits, grading scale: P, F
- TEN1 - Written exam, 4.0 credits, grading scale: P, 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.
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Laboratory Task
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Examination
Other requirements for final grade
Examination
Computer assignments
Project
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
Examiner
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.