Investigating thermoacoustic instability mitigation dynamics with a Kuramoto model for flamelet oscillators

Dutta, Ankit Kumar; Ramachandran, Gopakumar; Chaudhuri, Swetaprovo

doi:10.1103/physreve.99.032215

Cited by 16 publications

(12 citation statements)

References 21 publications

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“…1a. The combustor was characterized in our previous work [22][23][24] in a vertical configuration and is used in the present experiments in a horizontal configuration to facilitate length variation and imaging. A lean mixture (equivalence ratio,φ = 0.68) consisting of 6.5 slpm of methane and 90 slpm of air (Reynolds number, Re = 5.9 × 10 3 ) flows through the bottom of the settling chamber using four equally spaced inlet ports.…”

Section: Experimental Setup and Measurementsmentioning

confidence: 99%

“…These two effects together make up the characteristic frequency of the swirler: Ωc = Ωs + Ωr. Thus, accounting for the competition in the acoustic ( Ω0) and swirler ( Ωc) time scales, the coupling strength can be expressed as [24]:…”

Section: Mean-field Model Of the Swirl Controlled Thermoacoustic Systemmentioning

confidence: 99%

“…They observed the suppression of thermoacoustic instability through an intermittency route, hinting towards the de-synchronization of pressure and heat release rate fluctuations in attaining the control. The underlying mechanism of control was then modeled through a phenomenological model by Dutta et al [24] based on synchronization of flamelet oscillators through the Kuramoto model, which was able to capture the heat release rate response observed in the experiments.…”

Section: Introductionmentioning

confidence: 99%

“…We first present the experimental data on the control of thermoacoustic instability by rotating the swirler in the turbulent combustor. We then extend the model introduced by Dutta et al [24] by explicitly accounting for the acoustic feedback. Specifically, we consider a mean-field phase oscillator model for the nonlinear flame response, coupled to the basis function expansion of the acoustic pressure governing equation.…”

Section: Introductionmentioning

confidence: 99%

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Mean-field synchronization model for open-loop, swirl controlled thermoacoustic system

Singh¹,

Dutta²,

Dhadphale³

et al. 2022

Preprint

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Open-loop control is known to be an effective strategy for controlling self-excited thermoacoustic oscillations in turbulent combustors. In this study, we investigate the suppression of thermoacoustic instability in a lean premixed, laboratory-scale combustor using experiments and analysis. Starting with a self-excited thermoacoustic instability in the combustor, we find that a progressive increase in the swirler rotation rate transitions the system from thermoacoustic instability to the suppressed state through a state of intermittency. To model such transition while also quantifying the underlying synchronization characteristics, we extend the model of Dutta et al. [Phys. Rev. E 99, 032215 (2019)] by introducing a feedback between the ensemble of mean-field phase oscillators and the basis expansion of the acoustic pressure governing equation. The assumption that coupling strength among the oscillators is a linear combination of acoustic and swirler rotation frequency is justified a posteriori. The link between the model and experimental results is quantitatively established by implementing an optimization algorithm for model parameter estimation. We show that the model replicates the bifurcation characteristics, time series, probability density function (PDF), and power spectral density (PSD) of the various dynamical states observed during the transition to the suppressed state, to excellent accuracy. Specifically, the model captures the change in the PDF of pressure and heat release rate fluctuations from a bimodal distribution during thermoacoustic instability to a unimodal distribution during suppression. Finally, we discuss the global and local flame dynamics and show that the model qualitatively captures various aspects of spatio-temporal synchronization that underlies the transition.

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Section: Experimental Setup and Measurementsmentioning

confidence: 99%

Section: Mean-field Model Of the Swirl Controlled Thermoacoustic Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mean-field synchronization model for open-loop, swirl controlled thermoacoustic system

Singh¹,

Dutta²,

Dhadphale³

et al. 2022

Preprint

Self Cite

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show abstract

“…To model the mutual interactions between the subsystems such as combustion, hydrodynamics, and acoustic field, synchronisation between coupled oscillators could be an appropriate approach. Using synchronisation properties, Dutta et al [149] modelled the dynamics in a swirl stabilised combustor using Kuramoto oscillators arranged circumferentially around the swirler. They obtained similar dynamics as observed in the experiments by increasing the coupling strength between the oscillators.…”

Section: Synchronisation-based Modelsmentioning

confidence: 99%

Critical transitions and their early warning signals in thermoacoustic systems

Pavithran

Unni

Sujith

2021

Eur. Phys. J. Spec. Top.

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Many complex systems undergo critical transitions. A thermoacoustic system is one such system which exhibits a catastrophic transition to a state of oscillatory instability known as thermoacoustic instability. So far, several early warning signals have been devised to detect the transition from stable operation to thermoacoustic instability in both laminar and turbulent systems. We focus on these early warning signals, and the challenges faced while detecting oscillatory instabilities in practical systems. In contrast to the transition from a fixed point to limit cycle oscillations in laminar systems, turbulent systems exhibit a transition from a chaotic state to limit cycle via a state of intermittency. In this review, we highlight the importance of the inherent fluctuations in the system in providing early warning signals for critical transitions.

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Detection and identification of nature of mutual synchronization for low- and high-frequency non-premixed syngas combustion dynamics

2022

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Investigating thermoacoustic instability mitigation dynamics with a Kuramoto model for flamelet oscillators

Cited by 16 publications

References 21 publications

Mean-field synchronization model for open-loop, swirl controlled thermoacoustic system

Mean-field synchronization model for open-loop, swirl controlled thermoacoustic system

Critical transitions and their early warning signals in thermoacoustic systems

Detection and identification of nature of mutual synchronization for low- and high-frequency non-premixed syngas combustion dynamics

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