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perturbation to the gaseous field and that temperature may be accurately described by a single perturbed flamelet were no longer valid.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.

This work is devoted to generate knowledge and high quality experimental data of catalytic combustion at operational gas turbine conditions. The initial task of the thesis work was to design and construct a high pressure combustion test facility, where the catalytic combustion experiments can be performed at real gas turbine conditions. With this in mind, a highly advanced combustion test facility has been designed, constructed and tested. This test facility is capable of simulating combustion conditions relevant to a wide range of operating gas turbine conditions and different kinds of fuel gases. The shape of the combustor (test section) is similar to a “can” type gas turbine combustor, but with significant differences in its type of operation. The test combustor is expected to operate at near adiabatic combustion conditions and there will be no additions of cooling, dilution or secondary supply of air into the combustion process. The geometry of the combustor consists of three main zones such as air/fuel mixing zone, catalytic reaction zone and downstream gas phase reaction zone with no difference of the mass flow at inlet and exit. The maximum capacity of the test facility is 100 kW (fuel power) and the maximum air flow rate is 100g/s. The significant features of the test facility are counted as its operational pressure range (1 – 35 atm), air inlet temperatures (100 – 650 °C), fuel flexibility (LHV 4 - 40 MJ/m3) and air humidity (0 – 30% kg/kg of air). Given these features, combustion could be performed at any desired pressure up to 35 bars while controlling other parameters independently. Fuel flexibility of the applications was also taken into consideration in the design phase and proper measures have been taken in order to utilize two types of targeted fuels, methane and gasified biomass. Experimental results presented in this thesis are the operational performances of highly active precious metal catalysts (also called as ignition catalysts) and combinations of precious metal, perovskites and hexaaluminate catalysts (also called as fully catalytic configuration). Experiments were performed on different catalytic combustor configurations of various types of catalysts with methane and simulated gasified biomass over the full range of pressure. The types of catalysts considered on the combustor configurations are palladium on alumina (Pd/AL2O3), palladium lanthanum hexaaluminate (PdLaAl11O19), platinum on alumina (Pt/AL2O3),and palladium:platinum bi-metal on alumina (Pd:Pt/AL2O3). The influence of pressure, inlet temperature, flow velocity and air fuel ratio on the ignition, combustion stability and emission generation on the catalytic system were investigated and presented. Combustion catalysts were developed and provided mainly by the project partner, the Division of Chemical Technology, KTH. Division of Chemical Reaction Technology, KTH and Istituto di Ricerche sulla Combustione (CNR) Italy were also collaborated with some of the experimental investigations by providing specific types of catalysts developed by them for the specific conditions of gas turbine requirements. / <p>QC 20131125</p>

No description available.

Combustion instabilities (thermo-acoustic pressure oscillations) have been recognised for some time as a problem limiting the development of low emissions (e.g., lean burn) gas turbine combustion systems, particularly for aviation propulsion applications. Recently, significant research efforts have been focused on acoustic damping for suppression of combustion instability. Most of this work has either been experimental or based on linear acoustic theory. The last 3-5 years has seen application of density based CFD methods to this problem, but no attempts to use pressure-based CFD methods which are much more commonly used in combustion predictions. The goal of the present work is therefore to develop a pressure-based CFD algorithm in order to predict accurately acoustic propagation and acoustic damping processes, as relevant to gas turbine combustors. The developed computational algorithm described in this thesis is based on the classical pressure-correction approach, which was modified to allow fluid density variation as a function of pressure in order to simulate acoustic phenomena, which are fundamentally compressible in nature. The fact that the overall flow Mach number of relevance was likely to be low ( mildly compressible flow) also influenced the chosen methodology. For accurate capture of acoustic wave propagation at minimum grid resolution and avoiding excessive numerical smearing/dispersion, a fifth order accurate Weighted Essentially Non-Oscillatory scheme (WENO) was introduced. Characteristic-based boundary conditions were incorporated to enable accurate representation of acoustic excitation (e.g. via a loudspeaker or siren) as well as enable precise evaluation of acoustic reflection and transmission coefficients. The new methodology was first validated against simple (1D and 2D) but well proven test cases for wave propagation and demonstrated low numerical diffusion/dispersion. The proper incorporation of Characteristic-based boundary conditions was validated by comparison against classical linear acoustic analysis of acoustic and entropy waves in quasi-1D variable area duct flows. The developed method was then applied to the prediction of experimental measurements of the acoustic absorption coefficient for a single round orifice flow. Excellent agreement with experimental data was obtained in both linear and non-linear regimes. Analysis of predicted flow fields both with and without bias flow showed that non-linear acoustic behavior occurred when flow reversal begins inside the orifice. Finally, the method was applied to study acoustic excitation of combustor external aerodynamics using a pre-diffuser/dump diffuser geometry previously studied experimentally at Loughborough University and showed the significance of boundary conditions and shear layer instability to produce a sustained pressure fluctuation in the external aerodynamics.

No description available.

No description available.

This diploma thesis deals about the combustion turbine, design, processing and utilization. This work can be divided into three parts. The first part focuses on the theoretical knowledge gained in the field of gas turbines and their applications. The second part addresses the design of combustion turbine and its integral part. The third section describes the expected characteristics of combustion turbines. The work also includes the annex, which includes the technical documentation.

Syngas consisting mainly of a mixture of carbon monoxide, hydrogen and other diluents, is an important fuel for power generation applications since it can be obtained from both biomass and coal gasification. Clean coal technologies require stable and efficient operation of syngas-fired gas turbines. The trapped vortex combustor (TVC) is a relatively new gas turbine combustor concept which shows tremendous potential in achieving stable combustion under wide operating conditions with low emissions. In the present work, combustion of low calorific value syngas in a TVC has been studied using in-situ laser diagnostic techniques and numerical modeling. Specifically, this work reports in-situ measurements of mixture fraction, OH radical concentration and velocity in a single cavity TVC, using state-of-the art laser diagnostic techniques such as Planar Laser-induced Fluorescence (PLIF) and Particle Image Velocimetry (PIV). Numerical simulations using the unsteady Reynolds-averaged Navier-Stokes (URANS) and Large Eddy Simulation (LES) approaches have also been carried out to complement the experimental measurements. The fuel-air momentum flux ratio (MFR), where the air momentum corresponds to that entering the cavity through a specially-incorporated flow guide vane, is used to characterize the mixing. Acetone PLIF experiments show that at high MFRs, the fuel-air mixing in the cavity is very minimal and is enhanced as the MFR reduces, due to a favourable vortex formation in the cavity, which is corroborated by PIV measurements. Reacting flow PIV measurements which differ substantially from the non-reacting cases primarily because of the gas expansion due to heat release show that the vortex is displaced from the centre of the cavity towards the guide vane. The MFR was hence identified as the controlling parameter for mixing in the cavity. Quantitative OH concentration contours showed that at higher MFRs 4.5, the fuel jet and the air jet stream are separated and a flame front is formed at the interface. As the MFR is lowered to 0.3, the fuel air mixing increases and a flame front is formed at the bottom and downstream edge of the cavity where a stratified charge is present. A flame stabilization mechanism has been proposed which accounts for the wide MFRs and premixing in the mainstream as well. LES simulations using a flamelet-based combustion model were conducted to predict mean OH radical concentration and velocity along with URANS simulations using a modified Eddy dissipation concept model. The LES predictions were observed to agree closely with experimental data, and were clearly superior to the URANS predictions as expected. Performance characteristics in the form of exhaust temperature pattern factor and pollutant emissions were also measured. The NOx emissions were found to be less than 2 ppm, CO emissions below 0.2% and HC emissions below 700 ppm across various conditions. Overall, the in-situ experimental data coupled with insight from simulations and the exhaust measurements have confirmed the advantages of using the TVC as a gas turbine combustor and provided guidelines for stable and efficient operation of the combustor with syngas fuel.

<p>The main accomplishments of this research are </p> <p>(1) developed a high fidelity computational methodology based on large eddy simulation to capture lean blowout (LBO) behaviors of different fuels; </p> <p>(2) developed fundamental insights into the combustion processes leading to the flame blowout and fuel composition effects on the lean blowout limits; </p> <p>(3) developed artificial intelligence-based models for early detection of the onset of the lean blowout in a realistic complex combustor. </p> <p>The methodologies are demonstrated by performing the lean blowout (LBO) calculations and statistical analysis for a conventional (A-2) and an alternative bio-jet fuel (C-1).</p> <p>High-performance computing methodology is developed based on the large eddy simulation (LES) turbulence models, detailed chemistry and flamelet based combustion models. This methodology is employed for predicting the combustion characteristics of the conventional fuels and bio-derived alternative jet fuels in a realistic gas turbine engine. The uniqueness of this methodology is the inclusion of as-it-is combustor hardware details such as complex hybrid-airblast fuel injector, thousands of tiny effusion holes, primary and secondary dilution holes on the liners, and the use of highly automated on the fly meshing with adaptive mesh refinement. The flow split and mesh sensitivity study are performed under non-reacting conditions. The reacting LES simulations are performed with two combustion models (finite rate chemistry and flamelet generated manifold models) and four different chemical kinetic mechanisms. The reacting spray characteristics and flame shape are compared with the experiment at the near lean blowout stable condition for both the combustion models. The LES simulations are performed by a gradual reduction in the fuel flow rate in a stepwise manner until a lean blowout is reached. The computational methodology has predicted the fuel sensitivity to lean blowout accurately with correct trends between the conventional and alternative bio-jet fuels. The flamelet generated manifold (FGM) model showed 60% reduction in the computational time compared to the finite rate chemistry model. </p> <p>The statistical analyses of the results from the high fidelity LES simulations are performed to gain fundamental insights into the LBO process and identify the key markers to predict the incipient LBO condition in swirl-stabilized spray combustion. The bio-jet fuel (C-1) exhibits significantly larger CH₂O concentrations in the fuel-rich regions compared to the conventional petroleum fuel (A-2) at the same equivalence ratio. It is observed from the analysis that the concentration of formaldehyde increases significantly in the primary zone indicating partial oxidation as we approach the LBO limit. The analysis also showed that the temperature of the recirculating hot gases is also an important parameter for maintaining a stable flame. If this temperature falls below a certain threshold value for a given fuel, the evaporation rates and heat release rated decreases significantly and consequently leading to the global extinction phenomena called lean blowout. The present study established the minimum recirculating gas temperature needed to maintain a stable flame for the A-2 and C-1 fuels. </p> The artificial intelligence (AI) models are developed based on high fidelity LES data for early identification of the incipient LBO condition in a realistic gas turbine combustor under engine relevant conditions. The first approach is based on the sensor-based monitoring at the optimal probe locations within a realistic gas turbine engine combustor for quantities of interest using the Support Vector Machine (SVM). Optimal sensor locations are found to be in the flame root region and were effective in detecting the onset of LBO ~20ms ahead of the event. The second approach is based on the spatiotemporal features in the primary zone of the combustor. A convolutional autoencoder is trained for feature extraction from the mass fraction of the OH ( data for all time-steps resulting in significant dimensionality reduction. The extracted features along with the ground truth labels are used to train the support vector machine (SVM) model for binary classification. The LBO indicator is defined as the output of the SVM model, 1 for unstable and 0 for stable. The LBO indicator stabilized to the value of 1 approximately 30 ms before complete blowout.