Abstract
When Co-simulation is applied to coupled differential algebraic equations, convergence can only be guaranteed if certain properties are fulfilled. However, introducing uncertainties in this mode may have great impact on these contraction properties and may destroy convergence. Hence one is interested to analyze the stochastic behavior of those properties. Within this paper we compare the Kernel Density Estimation technique and the spectral approach based on polynomial chaos expansion to measure the density of the contraction factor which may occur for coupled systems. Using the new R-splitting approach in a field/circuit coupled problem as benchmark, we clarify the benefits of both schemes.
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Acknowledgements
This work is supported by the German Federal Ministry of Education and Research (BMBF) in the research projects SIMUROM (05M13PXB) and KoSMos (05M13PXA).
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Gausling, K., Bartel, A. (2018). Density Estimation Techniques in Cosimulation Using Spectral- and Kernel Methods. In: Langer, U., Amrhein, W., Zulehner, W. (eds) Scientific Computing in Electrical Engineering. Mathematics in Industry(), vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-75538-0_8
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DOI: https://doi.org/10.1007/978-3-319-75538-0_8
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