From Isolated Numerical Approaches to an Integrative Systems Science
What is SimTech?
In the 21st century's society, simulation technology has become completely indispensable, it dominates all areas of life. The cluster Simulation Technology, approved with the certificate “excellent” by the experts of the German Research Foundation (DFG), is embedded in the Stuttgart Research Centre for Simulation Technology. Together, it represents a massive platform for further developing scientific methods and techniques in all branches of modelling and simulation techniques.
SimTech Visions
- The transfer of an empirically dominated material description towards a simulation-based design of new materials with tailored high-end properties
- A completely virtualised development of prototypes and factories
- The use of complex and integrative methods in environmental engineering, e. g., with respect to the handling of greenhouse gases or the global climate change
- The transfer from the classical descriptive biology towards a systems-biologically dominated view on technical and natural systems
- The summing-up of isolated solutions in the field of biomechanics to an integrative description of the human body, e. g., with respect to medical technology and crash tests
More about the visions
Movie about the visions
Vision-based demonstrators
Projects in the focus
With the SimTech projects we want to investigate exciting, recent and scientifically relevant phenomena. Therefore, we are, inter alia, concentrating on the following problems:
How may multi-scale simulations be visualised interactively?
From Simulation Models with Uncertainties to Safety Verifications - is this possible?
How can we design novel materials with customised properties?
Publications from SimTech
Segmentation of skeletal muscle fibres for applications in computational skeletal muscle mechanics
O. Röhrle, H. Köstler, M. Loch
Explicit One-Step Time Discretizations for Discontinuous Galerkin and Finite Volume Schemes Based on Local Predictors
G. Gassner, M. Dumbser, F. Hindenlang, C.-D. Munz
Identification of models of heterogeneous cell populations from population snapshot data
J. Hasenauer, S. Waldherr, M. Doszczak, N. Radde, P. Scheurich, F. Allgöwer

