Stochastic Finite Element Method in Vibroacoustic Analysis
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
MW2324 is a module over more years in German or English language at Master’s level which is offered every semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
|Total workload||Contact hours||Credits (ECTS)|
|150 h||45 h||5 CP|
Content, Learning Outcome and Preconditions
- Introduction to uncertainty quantification methods
- Introduction to random variables and probability theory
- Sampling and non-sampling based FEM
- Karhunen–Loève and polynomial chaos expansions
- Intrusive and non-intrusive vibroacoustics FEM
- Collocation-based vibroacoustics FEM
- Random parameter identification in vibroacoustics FEM
- define instrusive and non-intrusive FEM formulations
- identify and explain the developments of Karhunen-Loève and polynomial chaos
- understand methods to quantify the uncertainties and practice the sampling and non-sampling FEM methods
- to identify and apply analytical and numerical FE methods for the structural dynamic description of vibro-acoustic problems
- develop vibro-acoustic models and to evaluate them in terms of parameter uncertainties
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VO||2||Stochastic finite element method in vibroacoustic analysis||
Learning and Teaching Methods
Tutorials: Analytical and numerical examples, Matlab and ANSYS-based simulation examples
- "Advanced Computational Vibroacoustics: Reduced-Order Models and Uncertainty Quantification" by Roger Ohayon and Christian Soize, 2014.
Description of exams and course work
On the other hand a project work in the form of homework (programming exercice) are used to report the extent to which participants are able to develop vibro-acoustic models using ANSYS and Matlab and to apply stochastic FEM on their own. Besides the ability of modeling, the acquired knowledge of sFEM formulations will be asked in the homework. (50% )
There is a possibility to take the exam in the following semester.