- 1:
Master ACM. - 2:
Curriculum & duration.- .2.1:
Mathematics - 2.2:
Numerical Methods. - 2.3:
Solid Mechanics/Heat Transfer. - 2.4:
Fatigue and Fracture. - 2.5:
Computational Dynamics. - 2.6:
Nonlinear Computational .... - 2.7:
Basics in Multiphysics. - 2.8:
Advanced Simulation .... - 2.9:
Managment Skills. - 2.10:
Product Development .... - 2.11:
Master Thesis. - 2.12:
Colloquium.
- .2.1:
- 3:
List of references. - 4:
Lecturers. - 5:
Application. - 6:
Campus & housing.
e-learning (intern)
Brochures
eBook
Links
Contact
Marktplatz 2
85576 Grafing near Munich
Dipl.-Ing. Anja Vogel
Fax
Mathematics
Teaching aims
The participants have advanced knowledge and a thorough understanding of the mathematical concepts and background needed in the other modules of the master program. They command the primary methods of advanced engineering mathematics needed in the field of computational mechanics.
They are able to apply mathematical methods and descriptions like tensor and vector calculus to engineering problems. They have acquired the ability to formulate and manipulate with this calculus corresponding equations and master the analysis of phenomena within the field of computational mechanics. The students are familiar with mathematical concepts like Fourier analysis and partial differential equations and have applied the acquired knowledge in practical exercises.
The students have acquired a thorough comprehension of optimization concepts. They are able to select and apply adequate optimization methods to solve problems like design optimization. They can estimate the potential and limits of optimization processes.
The students have the ability to apply theoretical concepts in practical usage. They are able to formulate and solve engineering problems in a conceptual and methodical way with the help of mathematical methods. They are able to discuss and investigate complex and interdisciplinary problems using mathematical terminology.
Content
- Tensor analysis
- Partial differential equations
- Fourier analysis
- Stochastics and statistics (probability analysis)
- Mathematical optimization
- Design sensitivity and optimization
- Numerical stability and convergence
- Solving systems of equations
Lecturers
- Prof. von Koch, Ingolstadt University of Applied Sciences
- Prof. Schittkowski, University of Bayreuth
ECTS
4 credits
Taught as
Class, practical exercise, lab exercise
Contact hours
40 hours
Examination
Written exam




