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Flame front (red) oscillating under the action of equivalence ratio (φ) and flow fluctuations.

Thermoacoustic instabilities arise due to the constructive feedback between unsteady heat release fluctuations and combustor acoustics. They are strongly undesirable, as they lead to unwanted structural vibrations limiting the operating range of gas turbines and aeroengines. The flame response, known as the Flame Transfer Function (FTF) and driven by the coupling with acoustic, hydrodynamic and equivalence ratio fluctuations, plays a key role in driving these instabilities.

Thesis description

With this work we will numerically study the response of a laminar bluff-body stabilized flame and use machine learning methods to control the flame response.  The goal is that of optimize the  geometrical and hydrodynamic parameters that drive the FTF and suppress thermoacoustic oscillations. The stability of a closed-loop thermoacoustic system will be investigated using the Nyquist method. The code for simulating the flame dynamics already exists, and needs to be interfaced with state-of-the-art machine learning optimization methods.

This work will be conducted together with Prof. Kilian Oberleithner, head of the Laboratory for Flow Instabilities and Dynamics, Dr. Alessandro Orchini and Jakob von Saldern.


Your profile

You are a motivated and creative student, happy to work in a team and with good communication skills. Applicants for this position are expected to have a background in Mechanical Engineering or Physics, and about to finish their Master's studies. Ideally, you have experience in one or more of the following:  acoustics, coding (MATLAB, C and/or Python), control-theory.




Dr. Alessandro Orchini


Jakob von Saldern


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