Coupled interaction between unsteady flame dynamics and acoustic field in a turbulent combustor
TL;DR: A possible asymmetric bidirectional coupling between q ˙ ' and p ' is observed to exert a stronger influence on p ' than vice versa, and the directional property of the network measure, namely, cross transitivity is used to analyze the type of coupling existing between the acoustic field and the heat release rate fluctuations.
Abstract: 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.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 derive...
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TL;DR: In this article, the authors discuss various prognosis and mitigation strategies for thermo-acoustic instability based on complex system theory in turbulent combustors, where the authors view the thermoacoustic system in a turbulent combustor as a complex system and the dynamics exhibited by the system is perceived as emergent behaviors of this complex system.
Abstract: Thermoacoustic instability in turbulent combustors is a nonlinear phenomenon resulting from the interaction between acoustics, hydrodynamics, and the unsteady flame Over the years, there have been many attempts toward understanding, prognosis, and mitigation of thermoacoustic instabilities Traditionally, a linear framework has been used to study thermoacoustic instability In recent times, researchers have been focusing on the nonlinear dynamics related to the onset of thermoacoustic instability In this context, the thermoacoustic system in a turbulent combustor is viewed as a complex system, and the dynamics exhibited by the system is perceived as emergent behaviors of this complex system In this paper, we discuss these recent developments and their contributions toward the understanding of this complex phenomenon Furthermore, we discuss various prognosis and mitigation strategies for thermoacoustic instability based on complex system theory
88 citations
TL;DR: A feature space consisting of the principal component plane estimated from the probability distribution of the transition patterns, which is obtained by a support vector machine, allows the early detection of thermoacoustic combustion instability.
Abstract: Early detection of thermoacoustic instabilities is of interest to both applied physicists and engineers, to avoid resonance leading to self-destruction of gas-based engines and turbines. This study shows how a combination of complex-network physics and machine learning can be used to detect a precursor of thermoacoustic instabilities, which can help to prevent the onset of a potentially destructive combustion-driven instability.
66 citations
01 Jan 2021
TL;DR: In this article, a range of problems involving unsteady combustion such as thermoacoustic instability, flame blowout, fire propagation, reaction chemistry and flow flame interaction are discussed. But the focus is not on the effects of these processes on the actual combustion system.
Abstract: Reacting flow fields are often subject to unsteadiness due to flow, reaction, diffusion, and acoustics. Further, flames can also exhibit inherent unsteadiness caused by various intrinsic instabilities. Interaction between various unsteady processes across multiple scales often makes combustion dynamics complex. Characterizing such complex dynamics is essential to ensure the safe and reliable operation of high efficiency combustion systems. Tools from nonlinear dynamics and complex systems theory provide new perspectives to analyze and interpret the data from real systems. They could also provide new ways of monitoring and controlling combustion systems. We discuss recent advances in studying unsteady combustion dynamics using the tools from dynamical systems theory and complex systems theory. We cover a range of problems involving unsteady combustion such as thermoacoustic instability, flame blowout, fire propagation, reaction chemistry and flow flame interaction.
35 citations
TL;DR: The turbulence network, which consists of nodes and vertexes in weighted networks between vortices, can characterize the complex spatiotemporal structure of a flow field during thermoacoustic combustion instability.
Abstract: We numerically study the spatiotemporal dynamics and early detection of thermoacoustic combustion instability in a model rocket combustor using the theories of complex networks and synchronization. The turbulence network, which consists of nodes and vertexes in weighted networks between vortices, can characterize the complex spatiotemporal structure of a flow field during thermoacoustic combustion instability. The transfer entropy allows us to identify the driving region of thermoacoustic combustion instability. In addition to the order parameter, a phase parameter newly proposed in this study is useful for capturing the precursor of thermoacoustic combustion instability.
33 citations
TL;DR: This paper adopts 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.
Abstract: 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.
29 citations
References
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TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Abstract: Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
17,647 citations
TL;DR: In this article, a graphical tool for measuring the time constancy of dynamical systems is presented and illustrated with typical examples, and the tool can be used to measure the time complexity of a dynamical system.
Abstract: A new graphical tool for measuring the time constancy of dynamical systems is presented and illustrated with typical examples.
2,843 citations
TL;DR: A practical method to determine the minimum embedding dimension from a scalar time series that has the following advantages: does not contain any subjective parameters except for the time-delay for the embedding.
1,485 citations
TL;DR: This paper illustrates how recurrence plots can take single physiological measurements, project them into multidimensional space by embedding procedures, and identify time correlations (recurrences) that are not apparent in the one-dimensional time series.
Abstract: Physiological systems are best characterized as complex dynamical processes that are continuously subjected to and updated by nonlinear feedforward and feedback inputs. System outputs usually exhibit wide varieties of behaviors due to dynamical interactions between system components, external noise perturbations, and physiological state changes. Complicated interactions occur at a variety of hierarchial levels and involve a number of interacting variables, many of which are unavailable for experimental measurement. In this paper we illustrate how recurrence plots can take single physiological measurements, project them into multidimensional space by embedding procedures, and identify time correlations (recurrences) that are not apparent in the one-dimensional time series. We extend the original description of recurrence plots by computing an array of specific recurrence variables that quantify the deterministic structure and complexity of the plot. We then demonstrate how physiological states can be assessed by making repeated recurrence plot calculations within a window sliding down any physiological dynamic. Unlike other predominant time series techniques, recurrence plot analyses are not limited by data stationarity and size constraints. Pertinent physiological examples from respiratory and skeletal motor systems illustrate the utility of recurrence plots in the diagnosis of nonlinear systems. The methodology is fully applicable to any rhythmical system, whether it be mechanical, electrical, neural, hormonal, chemical, or even spacial.
1,327 citations
TL;DR: Applying measures of complexity based on vertical structures in recurrence plots and applying them to the logistic map as well as to heart-rate-variability data is able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event.
Abstract: The knowledge of transitions between regular, laminar or chaotic behaviors is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods that, however, require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart-rate-variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e., chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our measures to the heart-rate-variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.
890 citations