Syllabus academic year 2011/2012
(Created 2011-09-01.)
Credits: 7,5. Grading scale: UG. Cycle: A (Second Cycle). Main field: Technology. Language of instruction: The course will be given in English on demand. FMNN05 overlaps following cours/es: FMN145. Optional for: D4, F4, F4bs, Pi4, Pi4bs, Pi4pv. Course coordinator: Claus Führer, and Anders Holst,, Numerical Analysis. Recommended prerequisits: FMNN10 Numerical Methods for Differential Equations. The course might be cancelled if the number of applicants is less than 10. The number of participants is limited to 15 Assessment: A report in several parts. 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, industrially 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 between various 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 modelling 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. Similar 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.