Thermoacoustic Analysis and Experimental Validation of Statistically-Based Flame Transfer Function Extracted from Computational Fluid Dynamics

dc.contributor.authorSampathkumar, Shriharien
dc.contributor.committeechairMeadows, Josephen
dc.contributor.committeememberBurdisso, Ricardo A.en
dc.contributor.committeememberTafti, Danesh K.en
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2021-01-15T07:00:15Zen
dc.date.available2021-01-15T07:00:15Zen
dc.date.issued2019-07-24en
dc.description.abstractThermoacoustic instabilities arise and sustain due to the coupling of unsteady heat release from the flame and the acoustic field. One potential driving mechanism for these instabilities arise when velocity fluctuations (u') at the fuel injection location causes perturbations in the local equivalence ratio and is convected to the flame location generating an unsteady heat release (q') at a particular convection time delay, τ. Physically, τ is the time for the fuel to convect from injection to the flame. The n-τ Flame Transfer Function (FTF) is commonly used to model this relationship assuming an infinitesimally thin flame with a fixed τ. In practical systems, complex swirling flows, multiple fuel injections points, and recirculation zones create a distribution of τ, which can vary widely making a statistical description more representative. Furthermore, increased flame lengths and higher frequency instabilities with short acoustic wavelengths challenge the 'thin-flame' approximation. The present study outlines a methodology of using distributed convective fuel time delays and heat release rates in a one-dimensional (1-D) linear stability model based on the transfer matrix approach. CFD analyses, with the Flamelet Generated Manifold (FGM) combustion model are performed and probability density functions (PDFs) of the convective time delay and local heat release rates are extracted. These are then used as inputs to the 1-D Thermoacoustic model. Results are compared with the experimental results, and the proposed methodology improves the accuracy of stability predictions of 1-D Thermoacoustic modeling.en
dc.description.abstractgeneralGas turbines that operate with lean, premixed air-fuel mixtures are highly efficient and produce significantly lesser emission of pollutants. However, they are highly susceptible to self-induced thermoacoustic oscillations which can excite larger pressure fluctuation which can damage critical components or catastrophic engine failure. Such a combustion system is considered to be unstable since the oscillation amplitude increases with time. Understanding the non-linear feedback mechanisms driving the system unstable and their cause are naturally of high interest to the industry. Highly resolved, but computationally demanding simulations can predict the stability of the system accurately, but become bottlenecks delaying iterative design improvements. Low order numerical models counter this with quick solutions but use simplified representations of the flame and feedback mechanisms, resulting in unreliable stability predictions. The current study bridges the gap between these methods by modifying the numerical model, allowing it to incorporate a better representation of fluid flow fields and flame structures that are obtained through computationally cheaper simulations. Experiments are conducted to verify the predictions and a technique that can be used to identify regions of the flame that contribute to amplitude growth is introduced. The improved model shows notable improvement in its prediction capabilities compared to existing models.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:21913en
dc.identifier.urihttp://hdl.handle.net/10919/101897en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectthermoacousticsen
dc.subjectgas turbineen
dc.subjectcombustionen
dc.titleThermoacoustic Analysis and Experimental Validation of Statistically-Based Flame Transfer Function Extracted from Computational Fluid Dynamicsen
dc.typeThesisen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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