The focus of our scientific work is the data-driven and analytical modeling of coherent structures in complex turbulent flows. Their great importance in the dynamics of turbulent flows was demonstrated by their discovery in the 1970s in various simplified flow forms. However, it is only in recent years that the influence of coherent structures on engineered flows has become understood in detail and can be modeled. A milestone of this development is the linear stability analysis of turbulent flows in interaction with data-driven model reduction methods. These two methods are core to the current scientific work of this field.

Current research projects aim at the analysis and control of turbulent flows in the field of aerodynamics and aeroacoustics, compressible strongly unsteady flows, reacting flows and two-phase vortex flows. In this context, new models based on the linear stability theory are developed on the basis of fundamental investigations and applied to complex technical flows.  To support the models, new data-driven modal decomposition methods are developed based on high-resolution experimental and numerical data (keyword: Big Data Science, Machine Learning).

For this purpose, numerical methods such as RANS, LES and DNS and experimental measurements are used. Furthermore, we are developing new stability solver for global stability and resolvent analysis, for complex geometries, including turbulence models, chemical reaction models and consideration of compressible and two-phase flows.  This solver is already being used extensively in basic research projects as well as in industry-related studies.