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Simulation II

Module name (EN):
Name of module in study programme. It should be precise and clear.
Simulation II
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Industrial Engineering, Bachelor, ASPO 01.10.2013
Module code: WIBASc-525-625-FÜ19
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P420-0411
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
1V+1U (2 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
3
Semester: 5
Mandatory course: no
Language of instruction:
German
Assessment:
Written exam

[updated 13.09.2018]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

WIBASc-525-625-FÜ19 (P420-0411) Industrial Engineering, Bachelor, ASPO 01.10.2013 , semester 5, optional course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
30 class hours (= 22.5 clock hours) over a 15-week period.
The total student study time is 90 hours (equivalent to 3 ECTS credits).
There are therefore 67.5 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
WIBASc145 Physics
WIBASc165 Mathematics I
WIBASc255 Statistics
WIBASc265 Mathematics II
WIBASc355 Computer Science / Programming


[updated 06.01.2020]
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Frank Kneip
Lecturer:
Prof. Dr. Frank Kneip


[updated 06.01.2020]
Learning outcomes:
After successfully completing this module students will:
_        have received insight into integration methods for solving common differential equations.
_        know options regarding the solution methods in Simulink.
_        have the ability to implement time-discrete systems in Simulink taking sampling times into account.
_        be able to model and implement suitable systems using non-linear, discontinuous and/or user-defined sub-elements.
_        have the ability to interpret simulation results.


[updated 13.09.2018]
Module content:
1.        Integration methods in Simulink
2.        Importance of selected options from the solution methods
3.        Sampling times and time-discrete systems
4.        Non-linear and discontinuous elements
5.        User-defined functions in Simulink
6.        Implementation and simulation of example models


[updated 13.09.2018]
Teaching methods/Media:
Lecture with integrated exercises,
presentation with projector, lecture notes, blackboard, PC, Matlab/Simulink


[updated 13.09.2018]
Recommended or required reading:
_        Pietruszka, W. D.: Matlab und Simulink in der Ingenieurpraxis _ Modellbildung, Berechnung und Simulation; 3. Auflage, Vieweg+Teubner Verlag, 2012
_        RRZN Handbuch: Matlab/Simulink; 4. Auflage, 2012
_        Nollau, R.: Modellierung und Simulation technischer Systeme; Springer Verlag, 2009
_        Hauߟer, F., Luchko, Y.: Mathematische Modellierung mit Matlab; Spektrum Akademischer Verlag, 2011
_        Scherf, H.: Modellbildung und Simulation dynamischer Systeme - Eine Sammlung von Simulink-Beispielen;
_        4. Auflage, Oldenbourg Verlag, 2010


[updated 13.09.2018]
 
[Wed May 15 08:20:23 CEST 2024, CKEY=wsi, BKEY=wi2, CID=WIBASc-525-625-FÜ19, LANGUAGE=en, DATE=15.05.2024]