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

Published online by Cambridge University Press:  13 April 2021

Abin Krishnan*
Affiliation:
Department of Aerospace Engineering, Indian Institute of Technology Madras, Chennai600 036, India
R.I. Sujith
Affiliation:
Department of Aerospace Engineering, Indian Institute of Technology Madras, Chennai600 036, India
Norbert Marwan
Affiliation:
Potsdam Institute for Climate Impact Research, Potsdam14412, Germany
Jürgen Kurths
Affiliation:
Potsdam Institute for Climate Impact Research, Potsdam14412, Germany Department of Physics, Humboldt University Berlin, Newtonstr. 15, 12489Berlin, Germany Institute for Complex Systems and Mathematical Biology, University of Aberdeen, AberdeenAB 24 UE, United Kingdom
*
Email address for correspondence: abin.roja@gmail.com

Abstract

In the present study, we quantify the vorticity interactions in a bluff body stabilized turbulent combustor during the transition from combustion noise to thermoacoustic instability via intermittency using complex networks. To that end, we perform simultaneous acoustic pressure, high-speed particle image velocimetry (PIV) and high-speed chemiluminescence measurements during the occurrence of combustion noise, intermittency and thermoacoustic instability. Based on the Biot–Savart law, we construct time-varying weighted spatial networks from the flow fields during these different regimes of combustor operation. We uncover that the turbulent networks display weighted scale-free behaviour intermittently during the different regimes of combustor operation, with the strong vortical structures acting as the hubs. Further, we discover two optimal locations for injecting steady air jets to successfully suppress the thermoacoustic oscillations. The amplitude of the acoustic pressure fluctuations of the suppressed state is comparable to that during the occurrence of combustion noise. However, the weighted scale-free network topology during the suppressed state is not as dominant as compared with the state of combustion noise.

Type
JFM Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

REFERENCES

Ananthkrishnan, N., Deo, S. & Culick, F.E. 2005 Reduced-order modeling and dynamics of nonlinear acoustic waves in a combustion chamber. Combust. Sci. Technol. 177 (2), 221248.CrossRefGoogle Scholar
Barabási, A.L. 2003 Linked: how everything is connected to everything else and what it means for business, science, and everyday life. Basic books.Google Scholar
Barabási, A.L. 2012 The network takeover. Nat. Phys. 8 (1), 1416.CrossRefGoogle Scholar
Barabási, A.L. & Bonabeau, E. 2003 Scale-free networks. Sci. Am. 288 (5), 6069.CrossRefGoogle ScholarPubMed
Barrat, A., Barthélemy, M. & Vespignani, A. 2004 a Modeling the evolution of weighted networks. Phys. Rev. E 70 (6), 066149.CrossRefGoogle ScholarPubMed
Barrat, A., Barthélemy, M. & Vespignani, A. 2004 b Weighted evolving networks: coupling topology and weight dynamics. Phys. Rev. Lett. 92 (22), 228701.CrossRefGoogle ScholarPubMed
Barthélemy, M. 2011 Spatial networks. Phys. Rep. 499 (1–3), 1101.CrossRefGoogle Scholar
Barthélemy, M., Barrat, A., Pastor-Satorras, R. & Vespignani, A. 2005 Characterization and modeling of weighted networks. Physica A 346 (1–2), 3443.CrossRefGoogle Scholar
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. & Hwang, D.-U. 2006 Complex networks: structure and dynamics. Phys. Rep. 424 (4–5), 175308.CrossRefGoogle Scholar
Boers, N., Bookhagen, B., Barbosa, H.M, Marwan, N., Kurths, J. & Marengo, J.A. 2014 Prediction of extreme floods in the eastern Central Andes based on a complex networks approach. Nat. Commun. 5 (1), 17.CrossRefGoogle ScholarPubMed
Charakopoulos, A.K., Karakasidis, T.E., Papanicolaou, P.N. & Liakopoulos, A. 2014 The application of complex network time series analysis in turbulent heated jets. Chaos 24 (2), 024408.CrossRefGoogle Scholar
Clavin, P., Kim, J.S. & Williams, F.A. 1994 Turbulence-induced noise effects on high-frequency combustion instabilities. Combust. Sci. Technol. 96 (1–3), 6184.CrossRefGoogle Scholar
Coats, C.M. 1996 Coherent structures in combustion. Prog. Energy Combust. Sci. 22 (5), 427509.CrossRefGoogle Scholar
Donges, J.F., Zou, Y., Marwan, N. & Kurths, J. 2009 The backbone of the climate network. Europhys. Lett. 87 (4), 48007.CrossRefGoogle Scholar
Ebi, D., Denisov, A., Bonciolini, G., Boujo, E. & Noiray, N. 2018 Flame dynamics intermittency in the bistable region near a subcritical hopf bifurcation. Trans. ASME: J. Engng Gas Turbines Power 140 (6), 061504.Google Scholar
Gao, Z. & Jin, N. 2009 Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks. Phys. Rev. E 79 (6), 066303.CrossRefGoogle ScholarPubMed
George, N.B., Unni, V.R, Raghunathan, M. & Sujith, R.I. 2018 Pattern formation during transition from combustion noise to thermoacoustic instability via intermittency. J. Fluid Mech. 849, 615644.CrossRefGoogle Scholar
Godavarthi, V., Pawar, S.A., Unni, V.R., Sujith, R.I., Marwan, N. & Kurths, J. 2018 Coupled interaction between unsteady flame dynamics and acoustic field in a turbulent combustor. Chaos 28 (11), 113111.CrossRefGoogle Scholar
Godavarthi, V., Unni, V.R., Gopalakrishnan, E.A. & Sujith, R.I. 2017 Recurrence networks to study dynamical transitions in a turbulent combustor. Chaos 27 (6), 063113.CrossRefGoogle Scholar
Gotoda, H., Kinugawa, H., Tsujimoto, R., Domen, S. & Okuno, Y. 2017 Characterization of combustion dynamics, detection, and prevention of an unstable combustion state based on a complex-network theory. Phys. Rev. Appl. 7 (4), 044027.CrossRefGoogle Scholar
Gotoda, H., Shinoda, Y., Kobayashi, M., Okuno, Y. & Tachibana, S. 2014 Detection and control of combustion instability based on the concept of dynamical system theory. Phys. Rev. E 89 (2), 022910.CrossRefGoogle ScholarPubMed
Hardalupas, Y. & Orain, M. 2004 Local measurements of the time-dependent heat release rate and equivalence ratio using chemiluminescent emission from a flame. Combust. Flame 139 (3), 188207.CrossRefGoogle Scholar
Ho, C.-M. & Nosseir, N.S. 1981 Dynamics of an impinging jet. Part 1. The feedback phenomenon. J. Fluid Mech. 105, 119142.CrossRefGoogle Scholar
Huang, Y. & Yang, V. 2009 Dynamics and stability of lean-premixed swirl-stabilized combustion. Prog. Energy Combust. Sci. 35 (4), 293364.CrossRefGoogle Scholar
Iacobello, G., Ridolfi, L. & Scarsoglio, S. 2020 A review on turbulent and vortical flow analyses via complex networks. Physica A 563, 125476.CrossRefGoogle Scholar
Iacobello, G., Scarsoglio, S., Kuerten, J.G.M. & Ridolfi, L. 2019 Lagrangian network analysis of turbulent mixing. J. Fluid Mech. 865, 546562.CrossRefGoogle Scholar
Juniper, M.P. & Sujith, R.I. 2018 Sensitivity and nonlinearity of thermoacoustic oscillations. Annu. Rev. Fluid Mech. 50, 661689.CrossRefGoogle Scholar
Kasthuri, P., Pavithran, I., Krishnan, A., Pawar, S.A., Sujith, R.I., Gejji, R., Anderson, W., Marwan, N. & Kurths, J. 2020 Recurrence analysis of slow–fast systems. Chaos 30 (6), 063152.CrossRefGoogle ScholarPubMed
Kheirkhah, S., Cirtwill, J.D.M., Saini, P., Venkatesan, K. & Steinberg, A.M. 2017 Dynamics and mechanisms of pressure, heat release rate, and fuel spray coupling during intermittent thermoacoustic oscillations in a model aeronautical combustor at elevated pressure. Combust. Flame 185, 319334.CrossRefGoogle Scholar
Kobayashi, T., Murayama, S., Hachijo, T. & Gotoda, H. 2019 Early detection of thermoacoustic combustion instability using a methodology combining complex networks and machine learning. Phys. Rev. Appl. 11 (6), 064034.CrossRefGoogle Scholar
Komarek, T. & Polifke, W. 2010 Impact of swirl fluctuations on the flame response of a perfectly premixed swirl burner. Trans. ASME: J. Engng Gas Turbines Power 132 (6), 061503.Google Scholar
Krishnan, A. 2019 Spatiotemporal analysis of a turbulent thermoacoustic system using complex networks. PhD thesis, Indian Institute of Technology Madras.Google Scholar
Krishnan, A., Manikandan, R., Midhun, P.R., Reeja, K.V., Unni, V.R., Sujith, R.I., Marwan, N. & Kurths, J. 2019 a Mitigation of oscillatory instability in turbulent reactive flows: a novel approach using complex networks. Europhys. Lett. 128 (1), 14003.CrossRefGoogle Scholar
Krishnan, A., Sujith, R.I., Marwan, N. & Kurths, J. 2019 b On the emergence of large clusters of acoustic power sources at the onset of thermoacoustic instability in a turbulent combustor. J. Fluid Mech. 874, 455482.CrossRefGoogle Scholar
Lacasa, L., Luque, B., Ballesteros, F., Luque, J. & Nuno, J.C. 2008 From time series to complex networks: the visibility graph. Proc. Natl Acad. Sci. USA 105 (13), 49724975.CrossRefGoogle ScholarPubMed
Lieuwen, T.C. 2002 Experimental investigation of limit-cycle oscillations in an unstable gas turbine combustor. J. Propul. Power 18 (1), 6167.CrossRefGoogle Scholar
Lieuwen, T.C. & Banaszuk, A. 2005 Background noise effects on combustor stability. J. Propul. Power 21 (1), 2531.CrossRefGoogle Scholar
Malik, N., Bookhagen, B., Marwan, N. & Kurths, J. 2012 Analysis of spatial and temporal extreme monsoonal rainfall over south asia using complex networks. Clim. Dyn. 39 (3–4), 971987.CrossRefGoogle Scholar
Manikandan, S. & Sujith, R.I. 2020 Rate dependent transition to thermoacoustic instability via intermittency in a turbulent afterburner. Exp. Therm. Fluid Sci. 114, 110046.CrossRefGoogle Scholar
McManus, K.R., Poinsot, T. & Candel, S.M. 1993 A review of active control of combustion instabilities. Prog. Energy Combust. Sci. 19 (1), 129.CrossRefGoogle Scholar
Molkenthin, N., Rehfeld, K., Marwan, N. & Kurths, J. 2014 Networks from flows-from dynamics to topology. Sci. Rep. 4, 4119.CrossRefGoogle Scholar
Mondal, S., Unni, V.R. & Sujith, R.I. 2017 Onset of thermoacoustic instability in turbulent combustors: an emergence of synchronized periodicity through formation of chimera-like states. J. Fluid Mech. 811, 659681.CrossRefGoogle Scholar
Murayama, S. & Gotoda, H. 2019 Attenuation behavior of thermoacoustic combustion instability analyzed by a complex-network-and synchronization-based approach. Phys. Rev. E 99 (5), 052222.CrossRefGoogle Scholar
Murayama, S., Kinugawa, H., Tokuda, I.T. & Gotoda, H. 2018 Characterization and detection of thermoacoustic combustion oscillations based on statistical complexity and complex-network theory. Phys. Rev. E 97 (2), 022223.CrossRefGoogle ScholarPubMed
Murugesan, M. & Sujith, R.I. 2015 Combustion noise is scale-free: transition from scale-free to order at the onset of thermoacoustic instability. J. Fluid Mech. 772, 225245.CrossRefGoogle Scholar
Murugesan, M. & Sujith, R.I. 2016 Detecting the onset of an impending thermoacoustic instability using complex networks. J. Propul. Power 32 (1), 707712.CrossRefGoogle Scholar
Nair, V., Thampi, G., Karuppusamy, S., Gopalan, S. & Sujith, R.I. 2013 Loss of chaos in combustion noise as a precursor of impending combustion instability. Intl J. Spray Combust. Dyn. 5 (4), 273290.CrossRefGoogle Scholar
Nair, V., Thampi, G. & Sujith, R.I. 2014 Intermittency route to thermoacoustic instability in turbulent combustors. J. Fluid Mech. 756, 470487.CrossRefGoogle Scholar
Newman, M. 2010 Networks. Oxford University Press.CrossRefGoogle Scholar
Noiray, N. & Schuermans, B. 2013 Deterministic quantities characterizing noise driven Hopf bifurcations in gas turbine combustors. Intl J. Non-Linear Mech. 50, 152163.CrossRefGoogle Scholar
Okuno, Y., Small, M. & Gotoda, H. 2015 Dynamics of self-excited thermoacoustic instability in a combustion system: pseudo-periodic and high-dimensional nature. Chaos 25 (4), 043107.CrossRefGoogle Scholar
Pawar, S.A., Vishnu, R., Vadivukkarasan, M., Panchagnula, M.V. & Sujith, R.I. 2016 Intermittency route to combustion instability in a laboratory spray combustor. Trans. ASME: J. Engng Gas Turbines Power 138 (4), 041505.Google Scholar
Poinsot, T.J., Trouve, A.C., Veynante, D.P, Candel, S.M. & Esposito, E.J. 1987 Vortex-driven acoustically coupled combustion instabilities. J. Fluid Mech. 177, 265292.CrossRefGoogle Scholar
Putnam, A.A. 1971 Combustion-Driven Oscillations in Industry. Elsevier Publishing Company.Google Scholar
Raffel, M., Willert, C.E., Scarano, F., Kähler, C.J., Wereley, S.T. & Kompenhans, J. 2007 Particle Image Velocimetry: A Practical Guide. Springer.CrossRefGoogle Scholar
Raghunathan, M., George, N.B., Unni, V.R., Midhun, P.R., Reeja, K.V. & Sujith, R.I. 2020 Multifractal analysis of flame dynamics during transition to thermoacoustic instability in a turbulent combustor. J. Fluid Mech. 888, A14.CrossRefGoogle Scholar
Rayleigh, J.W.S. 1878 The explanation of certain acoustical phenomena. Nature 18, 319321.CrossRefGoogle Scholar
Renard, P.-H., Thevenin, D., Rolon, J.-C. & Candel, S. 2000 Dynamics of flame/vortex interactions. Prog. Energy Combust. Sci. 26 (3), 225282.CrossRefGoogle Scholar
Rogers, D.E. & Marble, F.E. 1956 A mechanism for high-frequency oscillation in ramjet combustors and afterburners. J. Jet Propul. 26 (6), 456462.CrossRefGoogle Scholar
Sampath, R. & Chakravarthy, S.R. 2016 Investigation of intermittent oscillations in a premixed dump combustor using time-resolved particle image velocimetry. Combust. Flame 172, 309325.CrossRefGoogle Scholar
Sampath, R., Mathur, M. & Chakravarthy, S.R. 2016 Lagrangian coherent structures during combustion instability in a premixed-flame backward-step combustor. Phys. Rev. E 94 (6), 062209.CrossRefGoogle Scholar
Scarsoglio, S., Iacobello, G. & Ridolfi, L. 2016 Complex networks unveiling spatial patterns in turbulence. Intl J. Bifurcation Chaos 26 (13), 1650223.CrossRefGoogle Scholar
Schadow, K.C. & Gutmark, E. 1992 Combustion instability related to vortex shedding in dump combustors and their passive control. Prog. Energy Combust. Sci. 18 (2), 117132.CrossRefGoogle Scholar
Shanbhogue, S.J. 2008 Dynamics of perturbed exothermic bluff-body flow-fields. PhD thesis, Georgia Institute of Technology.Google Scholar
Singh, J., Belur Vishwanath, R., Swetaprovo, C. & Sujith, R.I. 2017 Network structure of turbulent premixed flames. Chaos 27 (4), 043107.CrossRefGoogle ScholarPubMed
Smith, D.A. & Zukoski, E.E. 1985 Combustion instability sustained by unsteady vortex combustion. In 21st Joint Propulsion Conference, p. 1248. AlAA/SAE/ASME/ASEE.Google Scholar
Strogatz, S.H 2001 Exploring complex networks. Nature 410 (6825), 268.CrossRefGoogle ScholarPubMed
Taira, K., Nair, A. & Brunton, S. 2016 Network structure of two-dimensional decaying isotropic turbulence. J. Fluid Mech. 795, R2.CrossRefGoogle Scholar
Tietjens, O.K.G. & Prandtl, L. 1957 Applied Hydro-and Aeromechanics: Based on Lectures of L. Prandtl, vol. 2. Courier Corporation.Google Scholar
Tony, J., Gopalakrishnan, E.A., Sreelekha, E & Sujith, R.I. 2015 Detecting deterministic nature of pressure measurements from a turbulent combustor. Phys. Rev. E 92 (6), 062902.CrossRefGoogle ScholarPubMed
Tsonis, A.A. & Roebber, P.J. 2004 The architecture of the climate network. Physica A 333, 497504.CrossRefGoogle Scholar
Tupikina, L., Rehfeld, K., Molkenthin, N., Stolbova, V., Marwan, N. & Kurths, J. 2014 Characterizing the evolution of climate networks. Nonlinear Process. Geophys. 21 (3), 705711.CrossRefGoogle Scholar
Unni, V.R., Krishnan, A., Manikandan, R., George, N.B., Sujith, R.I., Marwan, N. & Kurths, J. 2018 On the emergence of critical regions at the onset of thermoacoustic instability in a turbulent combustor. Chaos 28 (6), 063125.CrossRefGoogle Scholar
Unni, V.R., Nair, S.R.I., Krishnan, A., Marwan, N. & Kurths, J. 2021 System and method for optimizing passive control of oscillatory instabilities in turbulent flows. Indian Institute of Technology Madras.Google Scholar
Unni, V.R. & Sujith, R.I. 2017 Flame dynamics during intermittency in a turbulent combustor. Proc. Combust. Inst. 36 (3), 37913798.CrossRefGoogle Scholar
Varun, A.V., Balasubramanian, K. & Sujith, R.I. 2008 An automated vortex detection scheme using the wavelet transform of the $d_2$ field. Exp. Fluids 45 (5), 857868.CrossRefGoogle Scholar
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