- Maxwell's equations and basic concepts in electromagnetics.
- Numerical methods based on discretisation with finite differences and finite elements as well as the method of moments.
- Theory of convergence, stability and error analysis.
- Development of software for electromagnetic problems.
- Commercial software for electromagnetic problems.
FDD3270 Computational Methods for Electromagnetics 7.5 credits
The aim of the course is to give the students knowledge of numerical approaches to solve electromagnetics problems, relevant mathematical theory, and some insight into industrial application domains, as well as pros and cons of different formulations and commercial software approaches.
Information per course offering
Course offerings are missing for current or upcoming semesters.
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus FDD3270 (Autumn 2021–)Headings with content from the Course syllabus FDD3270 (Autumn 2021–) are denoted with an asterisk ( )
Content and learning outcomes
Course disposition
Course contents
- Maxwell's equations and basic concepts in electromagnetics.
- Numerical methods based on discretisation with finite differences and finite elements as well as the method of moments.
- Theory of convergence, stability and error analysis.
- Development of software for electromagnetic problems.
- Commercial software for electromagnetic problems.
Intended learning outcomes
After successful completion of course requirements, the students will be able to
- solve numerically electromagnetics problems to study wave propagation, transmission lines and antennas
- develop and implement numerical methods and software for finite difference and finite element differential equation models as well as integral equation models
- describe and list the advantages and limitations of different numerical techniques
- use commercial software to identify its limitations.
Literature and preparations
Specific prerequisites
No information inserted
Recommended prerequisites
Basic knowledge of Matlab and Python programming
Literature
You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
P, F
Examination
- EXA1 - Written examination, 7.5 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.
In order to pass the course, the student must pass three assignments, one final course adavanced project (report and presentation) and the presentation of an article on the field.
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.
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
This course does not belong to any Main field of study.
Education cycle
Third cycle