Module details

M1100-CMS62  Computational Engineering Advanced

Module Owner: N.N.
Displayed in timetable as: CMS-CE-EL2
Duration: 4
Number of electives: 0
Credits: 15,0
Start Semester: SuSe 2019
Lecturer Responsible Prof. Dr. Michael Beitelschmidt
michael.beitelschmidt@tu-dresden.de
Qualification Goals After completing the module, students will have in-depth skills in the application of computer-aided modelling and simulation in engineering sciences, extended to complex spatio-temporal systems. You have in-depth knowledge of the application domain and are able to study mixed models using self-implemented simulation methods, model complex systems independently and test and validate the models. Students are familiar with the application domain to the extent that they can hold solution-oriented project discussions with partners from the engineering sciences.
Content The contents of the module can be selected according to the focus of the students: in-depth aspects of mechanics, in-depth aspects of automation, in-depth aspects of computer science methods for graphical representation and control of simulations as well as flow simulation.
Forms of Teaching and Learning The module includes lectures, exercises, seminars, practical courses and project work in the scope of 12 SWS and self-study. The courses must be selected from the CMS-CE-EL2 catalogue to the specified extent; this will be announced at the beginning of the semester, as is customary at the Faculty of Computer Science, including the language of the course, the examination achievements required in each case and the weights of the grades.
Applicability The module is a compulsory module for students of the Computational Engineering track in the Master's Programme Computational Modelling and Simulation.
Prerequisites for the Assignment of Credit Points The credit points are awarded if the module examination is passed. The module examination consists of the examination services specified in the CMS-CE-EL2 catalogue.
Credit Points and Grades The module allows for the earning of 15 credit points. The module grade is calculated from the weighted average of the grades of the examination performances according to the CMS-CE-EL2 catalogue.
Frequency of Offer The module is offered each academic year, starting in the summer semester.
Workload The workload is a total of 450 hours.
Duration of Module The module takes two semesters to complete.
Module Number Module Handbook TU Dresden CMS-CE-EL2

Registration periods

Phase Block Register from | to End cancellation
Ohne Auswahlverfahren Vorlesungszeit 04.04.2019 00:00 | 20.01.2020 00:00 30.01.2020 00:00

Courses
Number Name Semester  
DK1100-MA001X Dummykurs CMS 1 SWS  
DK1100-MA002X Dummykurs CMS 2 SWS  
DK1100-MA002X Dummykurs CMS 2 SWS WiSe 2019/20
DK1100-MA003X Dummykurs CMS 3 SWS  
DK1100-MA004X Dummykurs CMS 4 SWS  
DK1100-MA004 Highly parallel programming of GPU WiSe 2019/20
DK1100-MA004 Dummykurs 4 SWS WiSe 2019/20
DK1100-MA004X Dummykurs CMS 4 SWS SuSe 2019
K1100-EX0630V Foundations for Machine Learning (V) 1  
K1104-MA0032V Scientific Visualization (V) 1  
K1104-MA0032V Scientific Visualization (L) SuSe 2020
K1104-MA0032Ü Scientific Visualization (Ü) 1  
K1104-MA0032Ü Scientific Visualization (E) SuSe 2020
K1107-MA0006V Particle Methods (V) 1  
K1107-MA0006V Particle Methods (L) SuSe 2019
K1107-MA0006V Particle Methods (L) SuSe 2020
K1107-MA0006Ü Particle Methods (Ü) 1  
K1107-MA0006Ü Particle Methods (E) SuSe 2019
K1107-MA0006Ü Particle Methods (E) SuSe 2020
K1107-MA0060V Machine Learning 1 (V) 1  
K1107-MA0060V Machine Learning 1 Compact event (L) WiSe 2019/20
K1107-MA0060Ü Machine Learning 1 (Ü) 1  
K1107-MA0060Ü Machine Learning 1 (E) WiSe 2019/20
K1202-1E0080V Numerische Verfahren der Theoretischen Elektrotechnik (V) 1  
K1202-1E0080V Numerical Methods for Electromagnetic Theory (L) SuSe 2019
K1202-1E0080Ü Numerische Verfahren der Theoretischen Elektrotechnik (Ü) 1  
K1202-1E0080Ü Numerical Methods for Electromagnetic Theory (E) SuSe 2019
K1202-1E0081P Wissenschaftliches Programmieren (P) 1  
K1202-1E0081P Scientific Programming (P) SuSe 2019
K1202-1E0081V Wissenschaftliches Programmieren (V) 1  
K1202-1E0081V Scientific Programming (L) SuSe 2019
K1208-500130Ü Characterization of micro- and nanoelectronic devices (E) 1  
K1208-500180V Modeling of Nanoelectronic Devices (L) 1  
K1301-1H0500V System Dynamics (L) 1  
K1301-1H0500V System Dynamics (L) SuSe 2019
K1301-1H0500Ü System Dynamics (E) 1  
K1301-1H0500Ü System Dynamics (E) SuSe 2019
K1302-1H0521P Turbulente Strömungen und deren Modellierung (P) 1  
K1302-1H0521V Turbulente Strömungen und deren Modellierung (V) 1  
K1302-1H0521Ü Turbulente Strömungen und deren Modellierung (Ü) 1  
K1302-1H1630P Numerische Modellierung von Mehrphasenströmungen (P) 1  
K1302-1H1630P Numerical modelling of multiphase flows (P) SuSe 2020
K1302-1H1630V Numerische Modellierung von Mehrphasenströmungen (V) 1  
K1302-1H1630V Numerical modelling of multiphase flows (L) SuSe 2020
K1302-1H1630Ü Numerische Modellierung von Mehrphasenströmungen (Ü) 1  
K1302-1H1630Ü Numerical modelling of multiphase flows (E) SuSe 2020
K1104-CMS03V Data Visualization (L) 2  
K1104-CMS03V Data Visualization (L) WiSe 2019/20
K1104-CMS03Ü Data Visualization (E) 2  
K1104-CMS03Ü Data Visualization (E) WiSe 2019/20
K1104-MA0024V User Interface Engineering (V) 2  
K1104-MA0024Ü User Interface Engineering (Ü) 2  
K1104-MA0025V Computer Graphics 1 (L) 2  
K1104-MA0025V Computer Graphics 1 (L) WiSe 2019/20
K1104-MA0025Ü Computer Graphics 1 (E) 2  
K1104-MA0025Ü Computer Graphics 1 (E) WiSe 2019/20
K1107-MA0009V Computer Vision 1 (V) 2  
K1107-MA0009Ü Computer Vision 1 (E) 2  
K1107-MA0062V Machine Learning 2 (V) 2  
K1107-MA0062Ü Machine Learning 2 (Ü) 2  
K1208-1M0320V Numerische Bauelementesimulation (V) 2  
K1208-1M0320Ü Numerische Bauelementesimulation (Ü) 2  
K1208-500170V Future Computing Strategies in Nano-Electronic Systems (L) 2  
K1208-500170V Theory of Nonlinear Networks (L) WiSe 2019/20
K1208-500170Ü Future Computing Strategies in Nano-Electronic Systems (E) 2  
K1208-500170Ü Theory of Nonlinear Networks (E) WiSe 2019/20
K1208-500170Ü Theory of Nonlinear Networks (E) WiSe 2020/21
K1210-500240V Introduction to Optical Non-classical Computing (V) 2  
K1210-500240V Introduction to Optical Non-classical Computing: Concepts and Devices (L) WiSe 2020/21
K1210-500240Ü Introduction to Optical Non-classical Computing (Ü) 2  
K1210-500240Ü Introduction to Optical Non-classical Computing: Concepts and Devices (E) WiSe 2020/21
K1212-500060V Electromechanical Networks (V) 2  
K1212-500060V Electromechanical Networks (L) WiSe 2019/20
K1212-500060V Electromechanical Networks (L) WiSe 2020/21
K1212-500060Ü Electromechanical Networks (Ü) 2  
K1212-500060Ü Electromechanical Networks (E) WiSe 2019/20
K1212-500060Ü Electromechanical Networks (E) WiSe 2020/21
K1301-EX0190V Gekoppelte Simulation/Echtzeitsimulation (V) 2  
K1301-EX0190V Coupled Simulation/Real Time Simulation (L) WiSe 2019/20

Passing rules
Context Name Description
Global * For information on the module examination please see module description
Global * For information on the module examination please see module description

Requirements
Course / Final module requirements Requirements Compulsory pass Weighting
DK1100-MA001X Dummykurs CMS 1 SWS Assessment No 1
DK1100-MA002X Dummykurs CMS 2 SWS Assessment No 2
DK1100-MA003X Dummykurs CMS 3 SWS Assessment No 3
DK1100-MA004X Dummykurs CMS 4 SWS Assessment No 4
K1100-EX0630V Foundations for Machine Learning (L) Written Examination Foundations of Machine Learning No 2
K1104-CMS03V Data Visualization (L) Written Examination/Oral Assessment Data Visualization No 4
K1104-MA0024V User Interface Engineering (L) Written Examination/Oral Assessment User Interface Engineering No 4
K1104-MA0025V Computer Graphics 1 (L) Written Examination/Oral Assessment Computer Graphics 1 No 4
K1104-MA0032V Scientific Visualization (L) Written Examination/Oral Assessment Scientific Visualization No 4
K1107-MA0006V Particle Methods (L) Written Examination/Oral Assessment Particle Methods No 4
K1107-MA0009V Computer Vision 1 (L) Oral Assessment Computer Vision 1 No 4
K1107-MA0060V Machine Learning 1 (L) Written Examination/Oral Assessment Machine Learning 1 No 4
K1107-MA0062V Machine Learning 2 (L) Written Examination/Oral Assessment Machine Learning 2 No 4
K1202-1E0080V Numerical Methods for Electromagnetic Theory (L) Written Examination/Oral Assessment Numerical Methods for Electromagnetic Theory No 3
K1202-1E0081V Scientific Programming (L) Laboratory Course Scientific Programming No 3
K1208-1M0320V Numerical Device Simulation (L) Written Examination Physics of Selected Components No 3
K1208-500170V Future Computing Strategies in Nano-Electronic Systems (L) Written Examination/Oral Assessment Theory of Nonlinear Networks No 3
K1208-500180V Modeling of Nanoelectronic Devices (V) Written Examination Modeling and Characterization of Nanoelectronic Devices No 3
K1210-500240V Introduction to Optical Non-classical Computing (L) Oral Assessment Introduction to Optical Non-classical Computing: Concepts and Devices No 3
Presentation Introduction to Optical Non-classical Computing: Concepts and Devices No 3
K1212-500060V Electromechanical Networks (L) Written Examination Electromechanical Networks No 3
K1301-1H0500V System Dynamics (L) Written Examination System Dynamics No 4
K1301-EX0190V Coupled Simulation/Real Time Simulation (L) Written Examination Coupled Simulation/Real Time Simulation No 2
K1302-1H0521V Turbulent flows and their modelling (L) Written Examination Turbulent flows and their modelling No 4
K1302-1H1630V Numerical modelling of multiphase flows (L) Written Examination/Oral Assessment Numerical modelling of multiphase flows No 4

Caption
**

For this final module requirement, several combinations of requirements do exist. The passing rules (see above) specify, whether you have to complete one or several requirement combinations.