Numerical treatment of initial value problems, boundary value problems, and eigenvalue problems for ordinary and partial differential equations. Discretization by finite differences and finite elements. Convergence, stability and error estimation. Orientation about mathematical modeling. Application oriented computer labs and a project.
DN2221 Applied Numerical Methods, part 1 6.0 credits
This course has been discontinued.
Decision to discontinue this course:
No information inserted
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 DN2221 (Autumn 2009–)Headings with content from the Course syllabus DN2221 (Autumn 2009–) are denoted with an asterisk ( )
Content and learning outcomes
Course contents
Intended learning outcomes
An overlying goal with the course is to give the student knowledge about how to formulate, utilise, analyze and implement advanced computer oriented numerical methods for solving those differential equation problems that are of importance in scientific and engineering applications.
After completing this course the student should be able to
- for a given problem, identify problem type within the area of differential equations, ordinary and partial, and suggest an algorithm for the numerical solution
- utilise and analyze the most important algorithms for the kind of problems presented in this course
- utilise algorithms from other areas of numerical analysis which are necessary for solving differential equations, direct and iterative methods for large sparse systems of equations and Fourier analysis
- set up and explain some fundamental mathematical models in science which are based on differential equations
- implement the algorithms i a programming language suitable for numerical computation, e.g. Matlab
- utilise computer tools for simulation and visualization of differential equation models in science and engineering.
Literature and preparations
Specific prerequisites
Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.
Literature
Lennart Edsberg "Introduction to Computation and Modeling for Differential Equations", Wiley 2009.
Examination and completion
Grading scale
A, B, C, D, E, FX, F
Examination
- TEN1 - Examination, 3.0 credits, grading scale: A, B, C, D, E, FX, F
- LAB1 - Laboratory, 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.
If the course is discontinued, students may request to be examined during the following two academic years.
In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.
Other requirements for final grade
Examination (TEN1; 3 hp)
Computer assignments and project work (LAB1; 3 hp)
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
Education cycle
Second cycle
Supplementary information
The course replaces DN2225.
This course can be counted in the degree even if the student has taken 2D1255/DN2255.