Syllabus academic year 2009/2010
(Created 2009-08-11.)

Higher education credits: 7,5. Grading scale: UG. Level: A (Second level). Language of instruction: The course will be given in English on demand. FMNN05 overlap following cours/es: FMN145 och FMN145. Optional for: D4, E4, F4, F4tvb, Pi4, Pi4bs. Course coordinator: Claus Führer, Numerisk analys. Recommended prerequisits: FMN130 Numerical Methods for Differential Equations. The course might be cancelled if the numer of applicants is less than 10. Assessment: A report in several parts. Further information: The course is given every second year. Home page:

Simulation technique is a field which merges experience in modelling with knowledge in Scientific Computing and programming skills. The aim of the course is to give students in the last stage of their university studies the possibility to experience in a working team industrial relevant computational problems in connection with modelling of complex mechanical systems. The participants meet numerical methods on different levels in industrial simulation tools. In particular ordinary differential equations with and without algebraic constraints and methods for large systems of nonlinear equations will form the numerical backbone of the course.

Knowledge and understanding
For a passing grade the student must

- be familiar with the software’s purpose.

- be able to evaluate simulation results.

Skills and abilities
For a passing grade the student must

independently be able to apply and evaluate numerical methods within industrial software tools.

Judgement and approach
For a passing grade the student must

- be able to see structural parallels in varying engineering problems.

-write an algorithmically well structured report in suitable terminology on the mathematical methods applied in industrial simulation tools.

Theoretical part: numerical treatment of ordinary differential equations with discontinuities and/or algebraic constraints, variants of different modelling techniques, variational integrators and other modeling related methods. Introduction to a modelling language.

Practical part: numerical experiments with computational tools within commercial and industrial software packages, e.g. MSC ADAMS and ABACUS. Experiments with selfproduced code in MATLAB or Python/SciPy.

Relevant material (from scientific journals and webbased user manuals) will be distributed at the beginning of the course.