Combustion dynamics of turbulent premixed combustors at elevated pressure

Gas turbines are integral to power generation and aviation, valued for their ability to deliver high efficiency and flexibility. To meet stringent environmental regulations, these systems increasingly employ lean premix combustion techniques to minimize nitrogen oxide (NOx) emissions. However, while effective in reducing emissions, lean premix combustion introduces a increased risk of thermoacoustic instabilities. These instabilities arise from complex interactions between heat release and acoustic waves within the combustion chamber, posing significant challenges to stability and performance.

In addition to environmental concerns, gas turbines are critical for balancing power grids dominated by variable renewable energy sources such as solar and wind. Their ability to rapidly adjust output necessitates robust designs capable of managing thermoacoustic instabilities. Advancements in this field are crucial for developing gas turbines that are both ecologically sustainable and operationally reliable.

This dissertation addresses the modeling, analysis, and mitigation of thermoacoustic instabilities in gas turbines. A one-dimensional acoustic network model is developed to evaluate system sensitivity to instabilities. This model incorporates key factors, including turbulence-induced damping, acoustic reflections, flow effects, and temperature gradients, enabling versatile analysis across diverse configurations. Coupled with experimentally derived flame transfer functions (FTFs), the model predicts instabilities with high accuracy.

Nonlinear flame dynamics are investigated using numerical simulations validated against experiments. A novel method for deriving FTFs from computational fluid dynamics (CFD) simulations is introduced, leveraging discrete multi-frequency excitation techniques. These methods are applied to analyze and optimize a laboratory-scale pressurized combustor, focusing on the effects of combustor length and exit impedance. Experimental validation confirms the model's effectiveness in detecting and mitigating instabilities.

The findings contribute to the development of efficient, stable, and flexible gas turbines, addressing modern energy challenges while ensuring compliance with environmental regulations.