The objective of this thesis is to develop and validate a model of soot formation which is capable of being applied to a computational fluid dynamic (CFD) simulation of gas turbine combustion. The work follows previous research by Moss and Co-workers (Moss et al.1987, Syed 1990, Stewart et al.1991) The concept of the study is to generate a detailed set of experimental data in turbulent flames of kerosine in which the complicating factors of gas turbine combustion - that is 3D geometry and droplet combustion - are removed. This allows more confidence in the computational simulation of the flames and therefore more insight into the soot formation process. There are two components to the work: the experimental and theoretical studies. The first involves the compilation of an experimental dataset of key variables in ethylene and vaporised kerosine jet flames at elevated pressure, the second with the simulation of two of the experimentally studied flames using CFD methods. The main achievement of the study is the generation of a formidable and detailed experimental database for flames at a variety of pressures and conditions. The unexpected finding is the extremely large conversion of carbon to soot found in the flames even at low pressure. This results in high radiant heat losses and measurement difficulties. From the data, it is possible to assess the pressure dependence of soot growth in kerosine flames. Although, at the higher pressures, high soot levels created uncertainties in the measurements, in absolute terms growth rate is shown to be independent of pressure up to 6atm pressure. Above this it increases significantly. The soot model of Moss et al.1988 - originally developed in laminar e~hylene flames - was shown to give excellent agreement in turbulent situations. However, owing to the large radiant heat loss and soot levels, its application to the kerosine flames was more problematic since the assumptions that soot is a perturbation to the gaseous field and that temperature may be accurately described by a single perturbed flamelet were no longer valid. Further models to deal with such situations are proposed and tested. Aside from the obvious relevance of this study to the field of gas turbine combustion, the large radiant heat loss and high soot levels observed in the flames studied here imply a further significance for the study of fire hazards. That a laboratory scale flame maybe made to behave in a similar manner to a much larger pool fire flame is a very useful finding.

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Thermoacoustic 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. / Master of Science / Gas 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.

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