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TU Berlin

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Following the cyberattack on the TU Berlin at the end of April 2021, this website can no longer be updated as usual. Please be aware that some information may be outdated.

Data Analysis and Modeling of Turbulent Flows


We focus on the dynamics of non-reacting and reacting flows on both fundamental and applied configurations. Our aim is to understand the physics of unstable fluid dynamical problems, which represent a bottleneck in modern energy generating systems such as gas turbines, wind turbines or rocket engines. Our research is based on high-fidelity numerical simulations and well-equipped experiments. Based on the acquired data set, we derive models that break down the essential physics by theoretical and/or purely data-driven approaches.

News of the group

  • 26.04.2021:
    Our latest paper with the title "An exceptional point switches stability of a thermoacoustic experiment" is accepted for publication in the Journal of Fluid Mechanics.

  • 09.04.2021:
    Our project is accepted for the first X-Student Research Group organized by the Berlin Univerity Alliance. Students interested in research are welcome to participate at the first online meeting on Thursday, 15.04.21 at 9h. Please send us an email for registration. More infos here !

  • 31.03.2021:
    Our colloquium on "Data-Driven Methods in Engineering Science" started for this semester. Please check the course webpage for more dates.

  • 22.01.2021:
    We offer a new MINTgrün course and a colloquium on "Data-Driven Methods in Engineering Science" for SoSe 2021. Please go to the teaching section for more information.

  • 20.01.2021:
    Notification on courses  for WiSe 20/21 online now ! Please check out the teaching section.

  • 11.01.2021:
    Welcome to MSc. Mario Casel and MSc. Vikas Yadav to the DMF group.

  • 20.21.2020:
    The paper "Data-Driven Identification of Nonlinear Flame Models" is available online now.

  • 20.08.2020:
    We have several exciting Master thesis topics available on numerical simulations, theoretical and/or data-driven approaches using machine learning. Contact us if you are interested !

  • 14.06.2020:
    Our paper "Control of intrinsic thermoacoustic instabilities using hydrogen fuel" is accepted for the upcoming Combustion Symposium.

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