Thermoacoustic instability and lean blowout are the major challenges faced when a gas turbine combustor is operated under fuel lean conditions. The dynamics of thermoacoustic system is the result of complex nonlinear interactions between the subsystems-turbulent reactive flow and the acoustic field of the combustor. In order to study the transitions between the dynamical regimes in such a complex system, the time series corresponding to one of the dynamic variables is transformed to an ɛ-recurrence network. The topology of the recurrence network resembles the structure of the attractor representing the dynamics of the system. The transitions in the thermoacoustic system are then captured as the variation in the topological characteristics of the network. We show the presence of power law degree distribution in the recurrence networks constructed from time series acquired during the occurrence of combustion noise and during the low amplitude aperiodic oscillations prior to lean blowout. We also show the absence of power law degree distribution in the recurrence networks constructed from time series acquired during the occurrence of thermoacoustic instability and during the occurrence of intermittency. We demonstrate that the measures derived from recurrence network can be used as tools to capture the transitions in the turbulent combustor and also as early warning measures for predicting impending thermoacoustic instability and blowout. © 2017 Author(s).

R. I. Sujith

Department of Aerospace Engineering

Vedasri Godavarthi

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IIT Madras

Recurrence networks to study dynamical transitions in a turbulent combustor

Chaos

Liquid rockets are prone to large amplitude oscillations, commonly referred to as thermoacoustic instability. This phenomenon causes unavoidable developmental setbacks and poses a stern challenge to accomplish the mission objectives. Thermoacoustic instability arises due to the nonlinear interaction between the acoustic and the reactive flow subsystems in the combustion chamber. In this paper, we adopt tools from dynamical systems and complex systems theory to understand the dynamical transitions from a state of stable operation to thermoacoustic instability in a self-excited model multielement liquid rocket combustor based on an oxidizer rich staged combustion cycle. We observe that this transition to thermoacoustic instability occurs through a sequence of bursts of large amplitude periodic oscillations. Furthermore, we show that the acoustic pressure oscillations in the combustor pertain to different dynamical states. In contrast to a simple limit cycle oscillation, we show that the system dynamics switches between period-3 and period-4 oscillations during the state of thermoacoustic instability. We show several measures based on recurrence quantification analysis and multifractal theory, which can diagnose the dynamical transitions occurring in the system. We find that these measures are more robust than the existing measures in distinguishing the dynamical state of a rocket engine. Furthermore, these measures can be used to validate models and computational fluid dynamics simulations, aiming to characterize the performance and stability of rockets. © 2019 Author(s).

Dynamical systems approach to study thermoacoustic transitions in a liquid rocket combustor

In turbulent combustors, the transition from stable combustion (i.e. combustion noise) to thermoacoustic instability occurs via intermittency. During stable combustion, the acoustic power production happens in a spatially incoherent manner. In contrast, during thermoacoustic instability, the acoustic power production happens in a spatially coherent manner. In the present study, we investigate the spatiotemporal dynamics of acoustic power sources during the intermittency route to thermoacoustic instability using complex network theory. To that end, we perform simultaneous acoustic pressure measurement, high-speed chemiluminescence imaging and particle image velocimetry in a backward-facing step combustor with a bluff body stabilized flame at different equivalence ratios. We examine the spatiotemporal dynamics of acoustic power sources by constructing time-varying spatial networks during the different dynamical states of combustor operation. We show that as the turbulent combustor transits from combustion noise to thermoacoustic instability via intermittency, small fragments of acoustic power sources, observed during combustion noise, nucleate, coalesce and grow in size to form large clusters at the onset of thermoacoustic instability. This nucleation, coalescence and growth of small clusters of acoustic power sources occurs during the growth of pressure oscillations during intermittency. In contrast, during the decay of pressure oscillations during intermittency, these large clusters of acoustic power sources disintegrate into small ones. We use network measures such as the link density, the number of components and the size of the largest component to quantify the spatiotemporal dynamics of acoustic power sources as the turbulent combustor transits from combustion noise to thermoacoustic instability via intermittency. © 2019 Cambridge University Press.

Journal of Fluid Mechanics

On the emergence of large clusters of acoustic power sources at the onset of thermoacoustic instability in a turbulent combustor

Thermoacoustic instability is a result of the positive feedback between the acoustic pressure and the unsteady heat release rate fluctuations in a combustor. We apply the framework of the synchronization theory to study the coupled behavior of these oscillations during the transition to thermoacoustic instability in a turbulent bluff-body stabilized gas-fired combustor. Furthermore, we characterize this complex behavior using recurrence plots and recurrence networks. We mainly found that the correlation of probability of recurrence (C P R), the joint probability of recurrence (J P R), the determinism (D E T), and the recurrence rate (R R) of the joint recurrence matrix aid in detecting the synchronization transitions in this thermoacoustic system. We noticed that C P R and D E T can uncover the occurrence of phase synchronization state, whereas J P R and R R can be used as indices to identify the occurrence of generalized synchronization (GS) state in the system. We applied measures derived from joint and cross recurrence networks and observed that the joint recurrence network measures, transitivity ratio, and joint transitivity are useful to detect GS. Furthermore, we use the directional property of the network measure, namely, cross transitivity to analyze the type of coupling existing between the acoustic field (p ′) and the heat release rate (q ′) fluctuations. We discover a possible asymmetric bidirectional coupling between q ′ and p ′, wherein q ′ is observed to exert a stronger influence on p ′ than vice versa. © 2018 Author(s).

Coupled interaction between unsteady flame dynamics and acoustic field in a turbulent combustor

We use complex network theory to investigate the dynamical transition from stable operation to thermoacoustic instability via intermittency in a turbulent combustor with a bluff body stabilized flame. A spatial network is constructed, representing each of these three dynamical regimes of combustor operation, based on the correlation between time series of local velocity obtained from particle image velocimetry. Network centrality measures enable us to identify critical regions of the flow field during combustion noise, intermittency, and thermoacoustic instability. We find that during combustion noise, the bluff body wake turns out to be the critical region that determines the dynamics of the combustor. As the turbulent combustor transitions to thermoacoustic instability, during intermittency, the wake of the bluff body loses its significance in determining the flow dynamics and the region on top of the bluff body emerges as the most critical region in determining the flow dynamics during thermoacoustic instability. The knowledge about this critical region of the reactive flow field can help us devise optimal control strategies to evade thermoacoustic instability. © 2018 Author(s).

On the emergence of critical regions at the onset of thermoacoustic instability in a turbulent combustor

Recently, M. Murugesan and R. I. Sujith ("Combustion Noise is Scale-Free: Transition from Scale-Free to Order at the Onset of Thermoacoustic Instability," Journal of Fluid Mechanics, Vol. 32, June 2015, pp. 225-245) showed that the transition from combustion noise to thermoacoustic instability can be represented as a change from a scale-free to a regular structure in the topology of complex networks. These topological changes of the complex networks during this transition can be quantified by calculating the network properties. In this paper, the variation of network properties, namely, clustering coefficient, characteristic path length, network diameter, and global efficiency is presented as the system dynamics undergoes transition from combustion noise to thermoacoustic instability. These network properties capture the change in system dynamics well before the rise in pressure amplitude levels in the combustors. These network properties can be used as early warning signals to detect the onset of impending thermoacoustic instabilities. ©2015 by Meenatchidevi Murugesan and R. I. Sujith. Published by the American Institute of Aeronautics and Astronautics, Inc.

Journal of Propulsion and Power

Detecting the Onset of an Impending Thermoacoustic Instability Using Complex Networks

Analysis of thermoacoustic instabilities were dominated by modal (eigenvalue) analysis for many decades. Recent progress in nonmodal stability analysis allows us to study the problem from a different perspective, by quantitatively describing the short-term behavior of disturbances. The short-term evolution has a bearing on subcritical transition to instability, known popularly as triggering instability in thermoacoustic parlance. We provide a review of the recent developments in the context of triggering instability. A tutorial for nonmodal stability analysis is provided. The applicability of the tools from nonmodal stability analysis are demonstrated with the help of a simple model of a Rjike tube. The article closes with a brief description of how to characterize bifurcations in thermoacoustic systems. © The Author(s) 2016.

International Journal of Spray and Combustion Dynamics

Non-normality and nonlinearity in thermoacoustic instabilities

Identifying nonlinear structures in a time series, acquired from real-world systems, is essential to characterize the dynamics of the system under study. A single time series alone might be available in most experimental situations. In addition to this, conventional techniques such as power spectral analysis might not be sufficient to characterize a time series if it is acquired from a complex system such as a thermoacoustic system. In this study, we analyze the unsteady pressure signal acquired from a turbulent combustor with bluff-body and swirler as flame holding devices. The fractal features in the unsteady pressure signal are identified using the singularity spectrum. Further, we employ surrogate methods, with translational error and permutation entropy as discriminating statistics, to test for determinism visible in the observed time series. In addition to this, permutation spectrum test could prove to be a robust technique to characterize the dynamical nature of the pressure time series acquired from experiments. Further, measures such as correlation dimension and correlation entropy are adopted to qualitatively detect noise contamination in the pressure measurements acquired during the state of combustion noise. These ensemble of measures is necessary to identify the features of a time series acquired from a system as complex as a turbulent combustor. Using these measures, we show that the pressure fluctuations during combustion noise has the features of a high-dimensional chaotic data contaminated with white and colored noise. © 2015 American Physical Society.

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics

Detecting deterministic nature of pressure measurements from a turbulent combustor

In classical literature, blowout is described as loss of static stability of the combustion system whereas thermoacoustic instability is seen as loss of dynamic stability of the system. At blowout, the system transitions from a stable reacting state to a non-reacting state, indicating loss of static stability of the reaction. However, this simple description of stability margin is inadequate since recent studies have shown that combustors exhibit complex nonlinear behaviour prior to blowout. Recently, it was shown that combustion noise that characterizes the regime of stable operation is itself dynamically complex and exhibits multifractal characteristics. Researchers have already described the transition from combustion noise to combustion instability as a loss of multifractality. In this work, we provide a multifractal description for lean blowout in combustors with turbulent flow and thus introduce a unified framework within which both thermoacoustic instability and blowout can be described. Further, we introduce a method for predicting blowout based on the multifractal description of blowout. © © 2015 Cambridge University PressA.

Multifractal characteristics of combustor dynamics close to lean blowout

We investigate the scale invariance of combustion noise generated from turbulent reacting flows in a confined environment using complex networks. The time series data of unsteady pressure, which is the indicative of spatiotemporal changes happening in the combustor, is converted into complex networks using the visibility algorithm. We show that the complex networks obtained from the low-amplitude, aperiodic pressure fluctuations during combustion noise have scale-free structure. The power-law distributions of connections in the scale-free network are related to the scale invariance of combustion noise. We also show that the scale-free feature of combustion noise disappears and order emerges in the complex network topology during the transition from combustion noise to combustion instability. The use of complex networks enables us to formalize the identification of the pattern (i.e. scale-free to order) during the transition from combustion noise to thermoacoustic instability as a structural change in topology of the network. © 2015 Cambridge University Press.

Journal	Data powered by TypesetChaos
Publisher	Data powered by TypesetAmerican Institute of Physics Inc.
ISSN	10541500
Open Access	No