Hostname: page-component-89b8bd64d-7zcd7 Total loading time: 0 Render date: 2026-05-07T19:37:36.343Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  09 March 2022

Yu Guan
Affiliation:
Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
Kihun Moon
Affiliation:
Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Kyu Tae Kim*
Affiliation:
Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Larry K.B. Li*
Affiliation:
Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong Guangdong–Hong Kong–Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
*
Email addresses for correspondence: kt_kim@kaist.ac.kr, larryli@ust.hk
Email addresses for correspondence: kt_kim@kaist.ac.kr, larryli@ust.hk

Abstract

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.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press.
Figure 0

Figure 1. Thermoacoustic system consisting of four turbulent lean-premixed combustors coupled in a ring configuration: (a) isometric view, (b) top cross-sectional view, and (c) end cross-sectional view of the annular cross-talk (XT) section. The dimensions shown are in millimetres. Further details can be found in Moon et al. (2020b, 2021). Panel (d) shows the network architecture, which contains two types of inter-combustor interactions: (i) direct coupling between any two adjacent oscillators, as represented by four pairwise links between $p^{\prime }_{\mathbb {X}}$ and $p^{\prime }_{\mathbb {Y}}$ (solid lines: C1–C2, C2–C3, C4–C3 and C4–C1); and (ii) indirect coupling between any two opposite oscillators, as represented by two pairwise links between $p^{\prime }_{\mathbb {X}}$ and $p^{\prime }_{\mathbb {Y}}$ (dash-dotted lines: C1–C3 and C4–C2). Intra-combustor interactions are captured by the coupling between $p^{\prime }_{\mathbb {X}}$ and $q^{\prime }_{\mathbb {X}}$ within each individual oscillator (C1, C2, C3 and C4).

Figure 1

Figure 2. Collective dynamics of network I, which exhibits a transition from intermittent frequency locking on a $\mathbb {T}^{3}$ quasiperiodic attractor to a breathing chimera. Shown at the top are time traces of (a1) $p^{\prime }$ and (a2) $p^{\prime }$ and $q^{\prime }$ for each of the four oscillators in the network (C1, C2, C3 and C4); both $p^{\prime }$ and $q^{\prime }$ have been normalized by their respective maximum values from the entire network. Also shown are the spectrograms and PSDs of (b1–4) $p^{\prime }$ and (c1–4) $q^{\prime }$, with the PSDs computed via the algorithm of Welch (1967). Panels (b1, c1), (b2, c2), (b3, c3) and (b4, c4) correspond to oscillators C1, C2, C3 and C4, respectively. The figure also shows (d1, e1) the temporal variation of $\Delta \psi _{p^{\prime }_{\mathbb {X}}p^{\prime }_{\mathbb {Y}}}$ and $\Delta \psi _{p^{\prime }_{\mathbb {X}}q^{\prime }_{\mathbb {X}}}$, alongside (d2, e2) their probability distributions, $\zeta _{p^{\prime }_{\mathbb {X}}p^{\prime }_{\mathbb {Y}}}$ and $\zeta _{p^{\prime }_{\mathbb {X}}q^{\prime }_{\mathbb {X}}}$, where the values of $\Delta \psi _{p^{\prime }_{\mathbb {X}}p^{\prime }_{\mathbb {Y}}}$ and $\Delta \psi _{p^{\prime }_{\mathbb {X}}q^{\prime }_{\mathbb {X}}}$ in (d2, e2) are wrapped around the interval $[-{\rm \pi}, {\rm \pi}]$. In the inset of (e1), each curve has been shifted by even integer multiples of ${\rm \pi}$ for clearer visualization. The ( f1) time trace, ( f2) spectrogram and PSD of the Kuramoto order parameter $R_K$ are shown in order to evaluate the phase coherence of the network. In (d1–2, e1–2), the dark- and light-grey regions denote in-phase and anti-phase dynamics, respectively. In (d1, f1–2), the yellow regions denote epochs of global in-phase synchronization.

Figure 2

Figure 3. The same as in figure 2 but for network II, which exhibits a two-cluster state of anti-phase synchronization on a periodic limit cycle.

Figure 3

Figure 4. The same as in figure 2 but for network III, which exhibits a weak anti-phase chimera.

Figure 4

Figure 5. Recurrence network analysis of the three networks in § 4.1: (a) cross-transitivity of $p^{\prime }_{\mathbb {X}}$ and $p^{\prime }_{\mathbb {Y}}$ for each pair of directly/indirectly coupled oscillators; (b) cross-transitivity of $p^{\prime }_{\mathbb {X}}$ and $q^{\prime }_{\mathbb {X}}$ for each individual oscillator. The vertical marker bars represent the standard deviation. Also shown are network diagrams illustrating the coupling architecture in (c) network I, (d) network II, and (e) network III.

Figure 5

Figure 6. GMM cluster analysis in a feature space defined by three global measures extracted from joint recurrence networks: the global clustering coefficient $\mathcal {C}_g$, the global edge density $\rho _g$, and the global average path length $\mathcal {L}_g$. Panel (a) shows $p^{\prime }_{\mathbb {X}}$$p^{\prime }_{\mathbb {Y}}$ objects, and (b) shows $p^{\prime }_{\mathbb {X}}$$q^{\prime }_{\mathbb {X}}$ objects. The bottom row shows a graphical representation of the cluster distribution for each of the three networks from § 4.1.

Figure 6

Figure 7. Cross-transitivity for the three networks in § 4.1 at three different sets of threshold values: (a,b) $RR_{\mathbb {X}\mathbb {Y}} = 0.04$, $RR_{\mathbb {X}} = RR_{\mathbb {Y}} = 0.05$; (c,d) $RR_{\mathbb {X}\mathbb {Y}} = 0.035$, $RR_{\mathbb {X}} = RR_{\mathbb {Y}} = 0.045$; and (e,f) $RR_{\mathbb {X}\mathbb {Y}} = 0.045$, $RR_{\mathbb {X}} = RR_{\mathbb {Y}} = 0.05$. The vertical marker bars represent the standard deviation.

Figure 7

Figure 8. Variation of (a) the silhouette score, (b) the Jensen–Shannon divergence, (c) the gradient of the Akaike information criterion, and (d) the gradient of the Bayesian information criterion, all as functions of the number of clusters. The optimal number of clusters suggested by each of the four indicators (ad) is highlighted with a red circular marker. Both the inter-combustor $p^{\prime }_{\mathbb {X}}$$p^{\prime }_{\mathbb {Y}}$ interactions and the intra-combustor $p^{\prime }_{\mathbb {X}}$$q^{\prime }_{\mathbb {X}}$ interactions are considered.