Simulation Tools
Simuleringsverktyg

FMNN05F, 7.5 credits

Valid from: Autumn 2013
Decided by: FN1/Anders Gustafsson
Date of establishment: 2014-09-15

General Information

Division: Numerical Analysis
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course codes: FMNN05, NUMN05
Teaching language: English

Aim

Simulation techniques is a field which demands experience in modelling, knowledge in Scientific Computing and programming skills. The aim of the course is to give the postgraduate student a chance to solve, 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, methods for large systems of nonlinear equations and computations of eigenvalues.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

• understand how the mathematical modelling of mechanical systems may yield differential equations with discontinuous coefficients or algebraic constraints.
• understand how such systems are handled by modern software packages, e.g., ASSIMULO.
• be able to describe structural parallels between different engineering problems that are discussed during the course.

Competences and Skills

For a passing grade the doctoral student must

• independently be able to apply and critically evaluate numerical methods which are common in industrial software packages.
• write an algorithmically well structured report in suitable terminology on mathematical methods applied in industrial simulation tools.

Course Contents

Theoretical part: Numerical treatment of ordinary differential equations with discontinuities and/or algebraic constraints. Variants of different modelling techniques, variational integrators and other methods suitable for modelling. Introduction to a modelling language. Practical part: numerical experiments with computational tools within commercial and industrial software packages, e.g. Dymola. Similar experiments with selfproduced code in Python/SciPy.

Course Literature

Relevant material (journal articles and extracts from web based handbooks) will be provided at the start of the course.

Instruction Details

Types of instruction: Lectures, exercises, project

Examination Details

Examination format: Written report
Grading scale: Failed, pass
Examiner:

Admission Details

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page: http://ctr.maths.lu.se/na/courses/FMNN05/