Simuleringsverktyg

Valid for: 2024/25

Faculty: Faculty of Engineering LTH

Decided by: PLED F/Pi

Date of Decision: 2024-04-15

Effective: 2024-05-08

Depth of study relative to the degree requirements: Second cycle, in-depth level of the course cannot be classified

Elective for: D4, F4, F4-bs, Pi4-bs, Pi4-pv

Language of instruction: The course will be given in English

Simulation techniques 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 a late stage of their university studies the possibility to work, in a small team, with industrially relevant computational problems in connection with the modelling of complex mechanical systems. The participants will experience how mathematical methods may be found on different levels in industrial simulation tools. In particular, the numerical treatment of ordinary differential equations, with discontinuities and/or without algebraic constraints, and numerical methods for large systems of nonlinear equations will form the backbone of the course.

Knowledge and understanding

For a passing grade the student must

- be able to describe which questions the software in the course may answer.
- be able to describe the numerical methods used in common commercial simulation tools.
- be able to evaluate simulation results for some simple problems.
- be able account for structural parallels between various engineering problems discussed during the course.

Competences and skills

For a passing grade the student must

- independently be able to apply and evaluate numerical methods within industrial software tools.
- 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 and of time dependent partial differential equations. Variants of different modelling techniques, variational integrators and other special numerical methods suitable for modelling. Introduction to a modelling language.

*Practical part:* Numerical experiments with computational tools within commercial and industrial software packages, e.g. DUNE. Similar experiments with selfproduced code in Python/SciPy.

Grading scale: UG - (U, G) - (Fail, Pass)

Assessment:

The examination consists of a written final report and an appurtenant oral presentation of the simulation projects at the end of the course.

Students who do not pass an assessment will be offered another opportunity for assessment soon thereafter.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Modules

Code: 0109. Name: Simulation Tools.

Credits: 7.5. Grading scale: UG - (U, G).

Assumed prior knowledge:
FMNN10 Numerical Methods for Differential Equations or similar course.

The number of participants is limited to: No

Kursen överlappar följande kurser:
FMN145
NUMN05
NUMN26

- Süli, Endre: An introduction to numerical analysis. Cambridge : Cambridge Univ. Press, 2003, ISBN: 0521810264. Also as Ebook via the Mathematics Library.
- Hairer, Ernst: Solving ordinary differential equations II - Stiff and Differential-Algebraic Problems. Berlin : Springer, 1996, ISBN: 3540604529. Available as Ebook via the Mathematics library.
- Führer, Claus, 1954-: Scientific computing with Python : high-performance scientific computing with NumPy, SciPy, and pandas. Birmingham : Packt Publishing, 2021, ISBN: 9781838822323. Available online via the Mathematics library.

Course coordinator: Robert Klöfkorn,
Robert.Klofkorn@math.lu.se

Teacher: Tony Stillfjord,
tony.stillfjord@math.lth.se

Director of studies: Anders Holst,
Studierektor@math.lth.se

Course administrator: Student Office,
expedition@math.lth.se

Course homepage: https://canvas.education.lu.se/courses/20396