Armac: Functional Variant Modeling for Adaptable Functional Networks

The application of functional networks in the automotive industry is still very slowly adopted into their development processes. Reasons for this are manifold. A functional network gets very quickly complex, even for small subsystems. Furthermore, concepts for variability handling are not sufficient for future standards such as AUTOSAR. In this paper we will provide an approach to reduce the size of functional networks by applying abstraction and partitioning. The achieved improvements will be described. In addition we will provide an alternative concept to handle variants in functional networks. The approach is based on extracting variation points from the functional network and modeling them separately. Open problems and future work are discussed at the end.

Refactoring of Automotive Models to Handle the Variant Problem

Models and model-based languages are more and more used in the automotive domain [1] to define artifacts for software (requirements, software and hardware architectures, code structure and behavior) to run in

RESPONSE OF STRUCTURES TO VARIOUS SEISMIC ENVIRONMENTS AND SUPPORTING MEDIA

In this parametric study, the effects of soil-structure interaction on the earthquake response of structures is demonstrated by including various types of supporting media and seismic environments in the analysis of a very simple structure representing residential building. The effect of the type of control point selected is also addressed. The analyses are performed in frequency space by employing the substructure method and non-dimensional variables. The transformation from the frequency to time space is performed by FFT algorithm. The results are presented in the form of plots of maximum lateral (or torsional) acceleration against a reference period for various parameters appearing in the analyses