Suppression of thermoacoustic instability by targeting the hubs of the turbulent networks in a bluff body stabilized combustor

Krishnan, Abin; Sujith, R. I.; Marwan, Norbert; Kurths, Jürgen

doi:10.1017/jfm.2021.166

Cited by 25 publications

(16 citation statements)

References 72 publications

(142 reference statements)

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“…Murayama & Gotoda (2019) combined a phase synchronization parameter and the determinism (connection strength) of cross recurrence plots to build weighted networks, and then used them to explain how thermoacoustic oscillations can be weakened with secondary air injection. Recently, Krishnan et al (2021) constructed time-varying weighted spatial turbulent networks based on the Biot-Savart law, and showed that thermoacoustic instability can be suppressed by targeting the primary network hubs (i.e. the fluid elements with high vorticity) with steady air jets.…”

Section: Complex Network In Thermoacousticsmentioning

confidence: 99%

Synchronization and chimeras in a network of four ring-coupled thermoacoustic oscillators

et al. 2022

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We take a complex systems approach to investigating experimentally the collective dynamics of a network of four self-excited thermoacoustic oscillators coupled in a ring. Using synchronization metrics, we find a wide variety of emergent multi-scale behaviour, such as (i) a transition from intermittent frequency locking on a $\mathbb {T}^{3}$ quasiperiodic attractor to a breathing chimera, (ii) a two-cluster state of anti-phase synchronization on a periodic limit cycle, and (iii) a weak anti-phase chimera. We then compute the cross-transitivity from recurrence networks to identify the dominant direction of the coupling between the heat-release-rate ( $q^{\prime }_{\mathbb {X}}$ ) and pressure ( $p^{\prime }_{\mathbb {X}}$ ) fluctuations in each individual oscillator, as well as that between the pressure ( $p^{\prime }_{\mathbb {X}}$ and $p^{\prime }_{\mathbb {Y}}$ ) fluctuations in each pair of coupled oscillators. We find that networks of non-identical oscillators exhibit circumferentially biased $p^{\prime }_{\mathbb {X}}$ – $p^{\prime }_{\mathbb {Y}}$ coupling, leading to mode localization, whereas networks of identical oscillators exhibit globally symmetric $p^{\prime }_{\mathbb {X}}$ – $p^{\prime }_{\mathbb {Y}}$ coupling. In both types of networks, we find that the $p^{\prime }_{\mathbb {X}}$ – $q^{\prime }_{\mathbb {X}}$ coupling can be symmetric or asymmetric, but that the asymmetry is always such that $q^{\prime }_{\mathbb {X}}$ exerts a greater influence on $p^{\prime }_{\mathbb {X}}$ than vice versa. Finally, we show through a cluster analysis that the $p^{\prime }_{\mathbb {X}}$ – $p^{\prime }_{\mathbb {Y}}$ interactions play a more critical role than the $p^{\prime }_{\mathbb {X}}$ – $q^{\prime }_{\mathbb {X}}$ interactions in defining the collective dynamics of the system. As well as providing new insight into the interplay between the $p^\prime_{\mathbb{X}}\text{--}p^\prime_{\mathbb{Y}}$ and $p^\prime_{\mathbb{X}}\text{--}q^\prime_{\mathbb{X}}$ coupling, this study shows that even a small network of four ring-coupled thermoacoustic oscillators can exhibit a wide variety of collective dynamics. In particular, we present the first evidence of chimera states in a minimal network of coupled thermoacoustic oscillators, paving the way for the application of oscillation quenching strategies based on chimera control.

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Section: Complex Network In Thermoacousticsmentioning

confidence: 99%

Synchronization and chimeras in a network of four ring-coupled thermoacoustic oscillators

et al. 2022

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“…In this twodimensional system, flow elements at grid points (Fig. 2) are considered as nodes, and links between two nodes represent the interaction between these flow elements 45,61 . The magnitude of the velocity induced by the vorticity of a flow element at the i th grid point on another flow element at the j th grid point (V i→ j ) (Fig.…”

Section: B Construction Of Time-evolving Directed Networkmentioning

confidence: 99%

“…In recent decades, complex networks theory has emerged as one of the most powerful tools in understanding the interactions between the different units of a complex system across various disciplines [40][41][42][43][44][45] . Tsonis et al 46 first applied this theory to study climate, by considering the climate system to be represented by a grid of oscillators interacting with each other in a complex way, with each one representing climate variability of a particular location of the gridded spatiotemporal dataset.…”

Section: Introductionmentioning

confidence: 99%

Study of Interaction and Complete Merging of Binary Cyclones Using Complex Networks

De¹,

Gupta²,

Unni³

et al. 2022

Preprint

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Cyclones are amongst the most hazardous extreme weather events on Earth. When two co-rotating cyclones come in close proximity, a possibility of complete merger (CM) arises due to their interactions. However, identifying the transitions in the interaction of binary cyclones and predicting the merger is challenging for weather forecasters. In the present study, we suggest an innovative approach to understand the evolving vortical interactions between the cyclones during two such CM events using time-evolving induced velocity based unweighted directed networks. We find that network-based indicators, namely, in-degree and out-degree, can quantify the changes during the interaction between two cyclones and are better candidates than the traditionally used separation distance to classify the interaction stages before a CM. The network indicators also help to identify the dominating cyclone during the period of interaction and quantify the variation of the strength of the dominating and merged cyclones. Finally, we show that the network measures also provide an early indication of the CM event well before its occurrence.

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“…The complex-network approach (Newman 2010;Barabási 2016) inspired by discrete mathematics has recently enabled us to clarify the nonlinear dynamics of intermediate-frequency combustion instability in several turbulent combustors (Murugesan & Sujith 2015;Okuno, Small & Gotoda 2015;Godavarthi et al 2018;Murayama et al 2018;Guan et al 2019;Kobayashi et al 2019;Krishnan et al 2019bKrishnan et al , 2021. The importance of the complex-network approach in the fields of combustion engineering and fluid physics has been shown in some recent review articles (Juniper & Sujith 2018;Sujith & Unni 2020Iacobello, Ridolfi & Scarsoglio 2021) and a book (Sujith & Pawar 2021).…”

Section: Introductionmentioning

confidence: 99%

Complex-network analysis of high-frequency combustion instability in a model single-element rocket engine combustor

et al. 2023

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We study the spatio-temporal dynamics of high-frequency combustion instability in a model single-element rocket combustor using an acoustic energy flux-based spatial network. The acoustic energy source collapses by the formation of small communities with weak connection when the flame edge is attached to the injector rim. In contrast, large communities with strong connection are formed in the shear layer between the oxygen and hydrogen jets when the flame edge is detached from the injector rim, which has a significant impact on driving combustion instability. The switching between the attachment and detachment of the flame edge during combustion instability can be explained by the spectral-clustering-based transition network constructed from the pressure and flow velocity of the hydrogen jet at the injector exit, and the temperature near the injector rim.

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Suppression of thermoacoustic instability by targeting the hubs of the turbulent networks in a bluff body stabilized combustor

Abstract: Abstract

Cited by 25 publications

References 72 publications

Synchronization and chimeras in a network of four ring-coupled thermoacoustic oscillators

Synchronization and chimeras in a network of four ring-coupled thermoacoustic oscillators

Study of Interaction and Complete Merging of Binary Cyclones Using Complex Networks

Complex-network analysis of high-frequency combustion instability in a model single-element rocket engine combustor

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