Swirl-stabilized Dump Combustor Research Articles

Control of Lean Blowout in a Swirl-Stabilized Dump Combustor at Different Levels of Premixing Based on Flame Colour

ABSTRACT Presently, the use of lean combustion has been growing in industrial furnaces, aero-engine, and rocket engine applications due to their low emission and minimum maintenance requirements. On the other hand, due to the excessively low combustion reaction rate, the operation at a low fuel–air ratio leads to the sudden shutdown of the engines, which is termed lean blowout (LBO). Therefore, to operate land-based and aircraft engines at an extremely lean fuel–air mixture, control of LBO has become indispensable. In the present work, we develop several feedback in-loop control strategies using a pixel-averaged intensity ratio between the red and blue components of the flame emission. During a lean operation, based on the quantification of the proximity of the combustion dynamics to the LBO limits using this color ratio, the control strategies make the solenoid valves active to inject a secondary pilot fuel and energize the flame base. We notice that a proper choice of the color ratio as a threshold enhances the stability of both premixed and partially premixed combustion using a low pilot fuel. Besides, we test emission for unpiloted and piloted operations and find that the emission is only marginally affected during a pilot injection.

Control of Lean Blowout in a Swirl-Stabilized Dump Combustor at Different Levels of Premixing Based on Flame Colour

Control of Lean Blowout in a Swirl-Stabilized Dump Combustor at Different Levels of Premixing Based on Flame Colour

Early Prediction of Lean Blowout from Chemiluminescence Time Series Data

ABSTRACT Lean combustion systems are usually employed in gas-turbine engines, particularly in land-based applications, to reduce NOx emission. These combustion systems are often susceptible to lean blowout (LBO), which can be detrimental for operation and productivity of gas-turbine engines. An abrupt decrease in the equivalence ratio during a throttling operation, which is often encountered in power plants due to sudden decrease in load demand and also in aircraft engines at the time of landing, may lead to an unexpected LBO. From this perspective, online data-driven algorithms are deemed necessary for early prediction of potential transitions to near-blowout conditions. This procedure would provide the human operator/active controller with an appropriate lead time to alter the operating conditions so that the system can be brought back to a desired stable condition. The paper emulates pertinent conditions of LBO on a laboratory-scale apparatus of swirl-stabilized dump combustor with transient time series of CH* chemiluminescence data, where the objective is early prediction of LBO. The underlying algorithms are constructed based on a well-known statistical learning tool, called Hidden Markov Modeling (HMM), which can be used in the setting of supervised learning to discern near-blowout time series data from stable data. Being solely data-driven, the proposed methodology is model-free; it has been shown to be numerically efficient as well as sensitive to regime changes when the combustion system moves toward or away from LBO.

Application of recurrence quantification analysis for early detection of lean blowout in a swirl-stabilized dump combustor.

Lean blowout (LBO) is a serious issue in modern gas turbine engines that operate in a lean (premixed) mode to follow the stringent emission norms. When an engine operates with a lean fuel-air mixture, the flame becomes unstable and is at times carried out of the combustion chamber by the unburnt flow. Thus, the sudden loss of the flame, known as lean blowout, leads to fatal accidents in aircrafts and loss of production in power plants. Therefore, an in-depth analysis of lean blowout is necessary as the phenomenon involves complex interactions between flow dynamics and chemical kinetics. For understanding the complex dynamics of this phenomenon, recurrence analysis can be a very useful method. In the current study, we observe a transition to LBO as the global fuel-air ratio is reduced from stoichiometric condition and perform recurrence quantification analysis (RQA) with the CH∗ chemiluminescence data obtained experimentally. The extent of fuel-air mixing is varied with an objective of developing some robust early predictors of LBO that would work over a wide range of premixing. We find some RQA measures, such as determinism, laminarity, and trapping time, which show distinctive signature toward LBO and thereby can be used as early predictors of LBO for both premixed and partially premixed flames. Our analysis shows that the computational time for laminarity and trapping time is relatively less. However, computational time for those measures depends upon the dynamics of the combustor, size of the data taken, and choice of recurrence threshold.

Investigation of flame behavior and dynamics prior to lean blowout in a combustor with varying mixedness of reactants for the early detection of lean blowout

Lean blowout is one of the major challenges faced when the gas turbine combustors are operated with lean fuel–air mixture to meet the emission norm. We experimentally study the flame behavior and the dynamics of heat release rate fluctuations during a transition to lean blowout. The study comprising flame visualization and estimating several measures to predict lean blowout for both premixed and partially premixed flames (using fuel ports F1 to F5) in a swirl stabilized dump combustor. To that end, we acquire unsteady heat release rate in terms of CH* chemiluminescence obtained through a photomultiplier tube with a narrow band-pass filter. For evaluating different statistical measures, we use National Instrument Labview software while acquiring the heat release rate oscillations. For premixed and partially premixed flames, such measures and the flame behavior show a different and, in some cases, even opposite trends as lean blowout is approached. However, in both premixed and partially premixed flames, the mean and root mean square values of the heat release rate fluctuation decrease as we decrease the equivalence ratio. Further, we show that the value of mean frequency calculated using Hilbert transform of the heat release rate fluctuations is a good indicator of lean blowout. Apart from the early prediction of lean blowout, different statistics of heat release rate oscillations, such as kurtosis and skewness, are shown to identify only the occurrence of lean blowout for premixed (F1 and F2) and flames with lower level of premixing (F3). They are not useful for the flames with high levels of unmixedness like F4 and F5. On the other side, probability density function is seen useful for both premixed and partially premixed flames. In short, we present the relative importance of different measures stated earlier for the identification and early prediction of lean blowout for both premixed and partially premixed flames.

Early Detection of Combustion Instability from Hi-speed Flame Images via Deep Learning and Symbolic Time Series Analysis


 
 
 Combustion instability, characterized by self-sustained, large-amplitude pressure oscillations and periodic shedding of coherent vortex structures at varied spatial scales, has many detrimental effects on flight-propulsion dynamics and structural integrity of gas turbine engines. Hence, its early detection is one of the important tasks in engine health monitoring and prognostics. This paper proposes a dynamic data-driven approach, where a large volume of sequential hi-speed (greyscale) images is used to analyze the temporal evolution of coherent structures in combustion chamber for early detection of combustion instability at various operating conditions. The proposed hierarchical approach involves extracting low-dimensional semantic features from images using Deep Neural Networks followed by capturing the temporal evolution of the extracted features using Symbolic Time Series Analysis (STSA). Extensive experimental data have been collected in a swirl-stabilized dump combustor at various operating conditions for validation of the proposed approach. Intermediate layer visualization of deep learning reveals that meaningful shape-features from the flame images are extracted, which enables the temporal modeling layer to enhance the class separability between stable and unstable regions. At the same time, the semantic nature of intermediate features enables expert-guided data exploration that can lead to better understanding of the underlying physics. To the best of the authors knowledge, this paper presents one of the early applications of the recently reported Deep Learning tools in the area of prognostics and health management (PHM).
 
 

Dynamic Data-Driven Prediction of Lean Blowout in a Swirl-Stabilized Combustor

This paper addresses dynamic data-driven prediction of lean blowout (LBO) phenomena in confined combustion processes, which are prevalent in many physical applications (e.g., land-based and aircraft gas-turbine engines). The underlying concept is built upon pattern classification and is validated for LBO prediction with time series of chemiluminescence sensor data from a laboratory-scale swirl-stabilized dump combustor. The proposed method of LBO prediction makes use of the theory of symbolic dynamics, where (finite-length) time series data are partitioned to produce symbol strings that, in turn, generate a special class of probabilistic finite state automata (PFSA). These PFSA, called D-Markov machines, have a deterministic algebraic structure and their states are represented by symbol blocks of length D or less, where D is a positive integer. The D-Markov machines are constructed in two steps: (i) state splitting, i.e., the states are split based on their information contents, and (ii) state merging, i.e., two or more states (of possibly different lengths) are merged together to form a new state without any significant loss of the embedded information. The modeling complexity (e.g., number of states) of a D-Markov machine model is observed to be drastically reduced as the combustor approaches LBO. An anomaly measure, based on Kullback-Leibler divergence, is constructed to predict the proximity of LBO. The problem of LBO prediction is posed in a pattern classification setting and the underlying algorithms have been tested on experimental data at different extents of fuel-air premixing and fuel/air ratio. It is shown that, over a wide range of fuel-air premixing, D-Markov machines with D > 1 perform better as predictors of LBO than those with D = 1.

Correspondence Between “Stable” Flame Macrostructure and Thermo-acoustic Instability in Premixed Swirl-Stabilized Turbulent Combustion

In this paper, we conduct an experimental investigation to study the link between the flame macroscale structure—or flame brush spatial distribution—and thermo-acoustic instabilities, in a premixed swirl-stabilized dump combustor. We operate the combustor with premixed methane–air in the range of equivalence ratio (φ) from the lean blowout limit to φ=0.75. First, we observe the different dynamic modes in this lean range as φ is raised. We also document the effect of φ on the flame macrostructure. Next, we examine the correspondence between dynamic mode transitions and changes in flame macrostructure. To do so, we modify the combustor length—by downstream truncation—without changing the underlying flow upstream. Thus, the resonant frequencies of the geometry are altered allowing for decoupling the heat release rate fluctuations and the acoustic feedback. Mean flame configurations in the modified combustor and for the same range of equivalence ratio are examined, following the same experimental protocol. It is found that not only the same sequence of flame macrostructures is observed in both combustors but also that the transitions occur at a similar set of equivalence ratio. In particular, the appearance of the flame in the outside recirculation zone (ORZ) in the long combustor—which occurs simultaneously with the onset of instability at the fundamental frequency—happens at similar φ when compared to the short combustor, but without being in latter case accompanied by a transition to thermo-acoustic instability. Then, we interrogate the flow field by analyzing the streamlines, mean, and rms velocities for the nonreacting flow and the different flame types. Finally, we focus on the transition of the flame to the ORZ in the acoustically decoupled case. Our analysis of this transition shows that it occurs gradually with an intermittent appearance of a flame in the ORZ and an increasing probability with φ. The spectral analysis of this phenomenon—we refer to as “ORZ flame flickering”—shows the presence of unsteady events occurring at two distinct low frequency ranges. A broad band at very low frequency in the range ∼(1 Hz–10 Hz) associated with the expansion and contraction of the inner recirculation zone (IRZ) and a narrow band centered around 28 Hz which is the frequency of rotation of the flame as it is advected by the ORZ flow.

A Cross-Wavelet Transform Aided Rule Based Approach for Early Prediction of Lean Blow-out in Swirl-Stabilized Dump Combustor

Lean or ultralean combustion is one of the popular strategies to achieve very low emission levels. However, it is extremely susceptible to lean blow-out (LBO). The present work explores a Cross-wavelet transform (XWT) aided rule based scheme for early prediction of lean blowout. XWT can be considered as an advancement of wavelet analysis which gives correlation between two waveforms in time-frequency space. In the present scheme a swirl-stabilized dump combustor is used as a laboratory-scale model of a generic gas turbine combustor with LPG as fuel. Various time series data of CH chemiluminescence signal are recorded for different flame conditions by varying equivalence ratio, flow rate and level of air-fuel premixing. Some features are extracted from the cross-wavelet spectrum of the recorded waveforms and a reference wave. The extracted features are observed to classify the flame condition into three major classes: near LBO, moderate and healthy. Moreover, a Rough Set based technique is also applied on the extracted features to generate a rule base so that it can be fed to a real time controller or expert system to take necessary control action to prevent LBO. Results show that the proposed methodology performs with an acceptable degree of accuracy.

Flame and Flow Topologies in an Annular Swirling Flow

This article describes an investigation of flame shapes and flow configurations in a premixed, swirl-stabilized dump combustor. High swirl, annular nozzle flows of this nature enable a variety of different flame configurations and heat release distributions with their associated flow fields. These differences are significant, since each of these configurations, in turn, has different thermoacoustic sensitivities and influences on combustor emissions, nozzle lifetime, and liner heating. These different configurations arise because multiple flame stabilization locations are present, associated with the inner and outer shear layers of the annulus, and the stagnation point of the vortex breakdown region. We present results from high-speed luminosity imaging, particle image velocimetry (PIV), and OH-planar laser induced fluorescence (PLIF) to illustrate time-averaged and instantaneous flame shapes and flow fields associated with the different configuration “families.” Selected cases are compared with large eddy simulations (LES). Particular emphasis is given to the distinctly different flame and flow topologies that exist in these flows, and their sensitivity to geometric (such as centerbody size and shape, combustor diameter, exhaust contraction) and operational (e.g., bulkhead temperature, preheat temperature, fuel/air ratio) parameters. We particularly emphasize the importance of the centerbody shape, and its associated impact on the structure of the central recirculating flow, as differentiating between two different families of flame shapes.

A GAS TURBINE COMBUSTOR FOR INSTABILITY RESEARCH AND LES VALIDATION: METHODS AND MEAN RESULTS

A novel atmospheric swirl stabilized dump combustor to facilitate instability investigations and the acquisition of validation and boundary condition data for large eddy simulation has been investigated when artificially perturbed. Combustor features include the capabilities of imposing pressure perturbations upon the premixed flow, preheating the reactant mixture up to 400°C, and introducing dilution air into the chamber. The combustor design is presented in detail. A fully premixed methane/air mixture of equivalence ratio 0.8 and mass flow of 20 mgs−1 perturbed at 100 Hz, 200 Hz, and 400 Hz was investigated in significant detail and the analysis completed. A full description of the high speed phase locked CH chemiluminescence and stereo particle imaging velocimetry used to characterize the unsteady reacting fields, flow fields, and vortex breakdown is given. The ensemble average results presented reveal changes in flame structure with frequency. These were attributed to the upstream movement of the toroidal vortex ring within the internal recirculation zone.

Design and preliminary results of an atmospheric-pressure model gas turbine combustor utilizing varying CO2 doping concentration in CH4 to emulate biogas combustion

Utilization of biogas can provide a source of renewable energy in both heat and power generation. Combustion of biogas in land-based gas turbines for power generation is a promising approach to reducing greenhouse gases and US dependence on foreign–source fossil fuels. Biogas is a byproduct from the decomposition of organic matter and consists primarily of CH4 and large amounts of CO2. The focus of this research was to design a combustion device and investigate the effects of increasing levels of CO2 addition to the combustion of pure CH4 with air. Using an atmospheric-pressure, swirl-stabilized dump combustor, emissions data and flame stability limitations were measured and analyzed. In particular, CO2, CO, and NOx emissions were the main focus of the combustion products. Additionally, the occurrence of lean blowout and combustion pressure oscillations, which impose significant limitations in operation ranges for actual gas turbines, was observed. Preliminary kinetic and equilibrium modeling was performed using Cantera and CEA for the CH4/CO2/Air combustion systems to analyze the effect of CO2 upon adiabatic flame temperature and emission levels. The numerical and experimental results show similar dependence of emissions on equivalence ratio, CO2 addition, inlet air temperature, and combustor residence time.

Effects of unstable flame structure and recirculation zones in a swirl-stabilized dump combustor

There has been increased demand in recent years for low NOx gas turbines to meet stringent emission goals by operating in a lean, premixed combustion mode. Unfortunately, detrimental combustion instabilities are often excited within the combustor when it operates under lean conditions, degrading performance and reducing combustor life. To eliminate the onset of these instabilities and develop effective approaches for their control, the mechanisms responsible for their occurrence must be understood. This study addresses structural characteristics of natural gas flames in a lean premixed swirl-stabilized combustor with attention focused on the effect of the formation of recirculation zones and vortex interaction on the combustion instability. To improve our understanding of the role of the recirculation zone and vortex combustion instability, the flame structure was investigated for various mixture velocities, equivalence ratios and swirl numbers. The optically accessible combustor allowed for the laser diagnostics of particle image velocimetry (PIV) measurement, while OH chemiluminescence was used to characterize the flow structure under both cold flow conditions and hot flow combustion conditions. Dynamic pressures were also measured at the same time to investigate characteristics of the combustion phenomenon. We also observed fundamental longitudinal type of combustion instability characteristics related to the instability of thermo-acoustics. The result suggests that the formation of the recirculation zone is strongly related to the occurrence of combustion instabilities.

모형 덤프 연소기에서 혼합기 유입구 길이 변화에 따른 연소불안정 특성에 대한 실험적 연구

The main objective of this study was investigation of natural gas flames in a lean premixed swirl-stabilized dump combustor with an attention focused on the effect of the various fuel-air mixing section geometry on the combustion instability characteristics. The combustor and mixing section length was varied in order to have different acoustic resonance characteristics from 800 to 1800 mm in combustor and 470, 550, 870 mm in mixing section. We observed two dominant instability frequencies in this study. Lower frequencies were associated with a fundamental longitudinal mode of combustor length. Higher frequencies were related to secondary longitudinal mode of coupled with the combustor and mixing section. As a result, combustion instability was strongly affected by acoustic characteristics of combustor and mixing section geometry.

Emission Measurements and CH* Chemiluminescence of a Staged Combustion Rig for Stationary Gas Turbine Applications

An optically accessible combustion rig was constructed to study the combustion characteristics of a reactive jet in a vitiated crossflow. The rig features two staged combustion zones. The main combustion zone is a swirl stabilized dump combustor. The second combustion zone, which is axially downstream from the main combustion zone, is formed by a transverse jet injecting either fuel or a premixed fuel/air mixture into the vitiated stream. The rig was designed to investigate the transverse jet conditions, equivalence ratio, and momentum ratios that produce low NOx and give an adequate temperature rise before the simulated high pressure turbine. A water-cooled sampling probe extracts exhaust gas downstream for emission measurements. As a baseline, the main combustion zone was fired without the transverse jet and the results compare closely to the work of previous researchers. The emission survey with the transverse jet found several conditions that show a benefit of staging compared to the baseline of firing only the main combustion zone. The flame structure from the transverse jet was captured using high speed CH* chemiluminescence, which shows the extent of the flame front and its penetration depth into the vitiated stream. The chemiluminescence images were averaged and compared to the Holdeman correlation, which showed good agreement for injection with fuel only but poorer agreement when premixed.

Experimental and Numerical Investigation of a Swirl Stabilized Premixed Combustor Under Cold-Flow Conditions

Planar velocity measurements under cold-flow conditions in a swirl-stabilized dump combustor typical of land-based gas turbine combustors were carried out using two-dimensional particle image velocimetry (PIV). Axial, radial, and tangential velocity components were measured sequentially using two experimental configurations. Mean and root-mean-squared velocity components are presented along with instantaneous realizations of the flowfield. A numerical study of the flowfield using large-eddy simulation (LES) and Reynolds-averaged Navier-Stokes (RANS) techniques was conducted in an effort to help understand the complex hydrodynamics observed in the experiments. The agreement between the experimental data and LES simulation was good with both showing evidence of a precessing vortex core. The results of the RANS simulation were not as encouraging. The results provide a fundamental understanding of the complex flowfield associated with the relatively simple geometry and also serve as a baseline validation dataset for further numerical simulations of the current geometry. Validation of LES models in a highly swirled, nonreacting flowfield such as the work presented here is an essential step towards more accurate prediction in a reacting environment.