Institute of Physics & ForWind
Prof. Dr. Joachim Peinke
Room, W33 3-302
Extracting dynamical cluster features of complex systems
In a recently published article Philip Rinn, Yuriy Stepanov, Joachim Peinke, Thomas Guhr and Rudi Schäfer propose to combine cluster analysis and stochastic process analysis to characterize high-dimensional complex dynamical systems by few dominating variables. They analyze stock market data for which the dynamical stability as well as transitions between different stable states are found. The method allows to set up new criteria for identifying spurious clusters and to uncover dynamically distinct states.
Dynamics of quasi-stationary systems: Finance as an example
P. Rinn, Y. Stepanov, J. Peinke, T. Guhr, und R. Schäfer
EPL (Europhysics Letters), vol. 110, iss. 6, p. 68003, 2015.
Philip Rinn, Hendrik Heißelmann, Matthias Wächer and Joachim Peinke present in an article (description in pro-Physik and highlights in Europhysics News) a new method for diagnosing even the smallest changes in mechanical properties. Especially for reliable continuous operation of wind turbines, timely detection of mechanical damage is crucial. Here, the new method should enable better damage diagnosis of wind turbines.
Patrick Milan, Matthias Wächer and Joachim Peinke describe in an article in the journal Physical Review Letters (description in Phys-org) that the energy conversion process on small time scales in the range of seconds follows complex patterns with multi-fractal scale laws, which correspond to the theory on turbulence of A. N. Kolmogorov from 1962.
Illustration of the second dynamics of the power output of a modern wind turbine. In the background the deterministic drift field of a reconstructed Langevin equation for the dynamics of the power conversion.