(*) Unfortunately this information is not available in english.
Workload
Education level
Study areas
Responsible person
Hours per week
Coordinating university
6 ECTS
M1 - Master's programme 1. year
Mathematics
Herbert Egger
4 hpw
Johannes Kepler University Linz
Detailed information
Original study plan
Master's programme Mechatronics 2025W
Learning Outcomes
Competences
The students are able to solve initial and boundary value problems for differential equations and optimization problems using suitable approximation methods.
Skills
Knowledge
Investigate existence and uniqueness of solutions to differential equations (k4);
Select (k2) and investigate (k4) suitable discretisation methods in space and time;
Select (k2) and investigate (k4) suitable methods for free and constrained optimization problems;
Implement the selected solution methods on the computer (k3);
Verify the accuracy and plausibility of the numerical solution (k4).
Analysis and numerical methods for ordinary and partial differential equations; single-step methods; finite element methods; numerical methods for parabolic and hyperbolic differential equations; necessary and sufficient optimality conditions; decent methods (steepest decent, Newton method).
Criteria for evaluation
Oral examination and homework assignments (each 50% of the grade).
The course is passed when both parts are graded with at least the mark “4”.
Language
German
Study material
W. Dahmen und A. Reusken: Numerik für Ingenieure und Naturwissenschaftler. Springer, 2006.
U. Langer und M. Jung: Methode der Finiten Elemente für Ingenieure. Teubner, 2013.
O. Stein: Grundzüge der Nichtlinearen Optimierung. Springer, 2021.
Changing subject?
No
Further information
none
Corresponding lecture
(*)MEMPAKVNUOP: KV Numerik und Optimierung (5,75 ECTS)
