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On the emergence of large clusters of acoustic power sources at the onset of thermoacoustic instability in a turbulent combustor

Published online by Cambridge University Press:  09 July 2019

Abin Krishnan Open the ORCID record for Abin Krishnan [Opens in a new window] ,
R. I. Sujith ,
Norbert Marwan  and
Jürgen Kurths
Abin Krishnan*
Affiliation:
Indian Institute of Technology Madras, Chennai 600036, India
R. I. Sujith
Affiliation:
Indian Institute of Technology Madras, Chennai 600036, India
Norbert Marwan
Affiliation:
Potsdam Institute for Climate Impact Research, 14412 Potsdam, Germany
Jürgen Kurths
Affiliation:
Potsdam Institute for Climate Impact Research, 14412 Potsdam, Germany Department of Physics, Humboldt University, 10115 Berlin, Germany
*
†Email address for correspondence: abin.roja@gmail.com
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Abstract

In turbulent combustors, the transition from stable combustion (i.e. combustion noise) to thermoacoustic instability occurs via intermittency. During stable combustion, the acoustic power production happens in a spatially incoherent manner. In contrast, during thermoacoustic instability, the acoustic power production happens in a spatially coherent manner. In the present study, we investigate the spatiotemporal dynamics of acoustic power sources during the intermittency route to thermoacoustic instability using complex network theory. To that end, we perform simultaneous acoustic pressure measurement, high-speed chemiluminescence imaging and particle image velocimetry in a backward-facing step combustor with a bluff body stabilized flame at different equivalence ratios. We examine the spatiotemporal dynamics of acoustic power sources by constructing time-varying spatial networks during the different dynamical states of combustor operation. We show that as the turbulent combustor transits from combustion noise to thermoacoustic instability via intermittency, small fragments of acoustic power sources, observed during combustion noise, nucleate, coalesce and grow in size to form large clusters at the onset of thermoacoustic instability. This nucleation, coalescence and growth of small clusters of acoustic power sources occurs during the growth of pressure oscillations during intermittency. In contrast, during the decay of pressure oscillations during intermittency, these large clusters of acoustic power sources disintegrate into small ones. We use network measures such as the link density, the number of components and the size of the largest component to quantify the spatiotemporal dynamics of acoustic power sources as the turbulent combustor transits from combustion noise to thermoacoustic instability via intermittency.

JFM classification

Reacting Flows: Turbulent reacting flows Vortex Flows: Vortex dynamics

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JFM Papers
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Journal of Fluid Mechanics , Volume 874 , 10 September 2019 , pp. 455 - 482
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© 2019 Cambridge University Press 

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References

Albert, R. & Barabási, A. L. 2002 Statistical mechanics of complex networks. Rev. Mod. Phys. 74 (1), 47–97.Google Scholar
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), 221–248.Google Scholar
Barabasi, 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. 2011 The network takeover. Nat. Phys. 8 (1), 14–16.Google Scholar
Barabási, A. L. 2016 Network Science. Cambridge University Press.Google Scholar
Barabási, A. L. & Albert, R. 1999 Emergence of scaling in random networks. Science 286 (5439), 509–512.Google Scholar
Barthélemy, M. 2011 Spatial networks. Phys. Rep. 499 (1–3), 1–101.Google Scholar
Bar-Yam, Y. 1997 Dynamics of Complex Systems, vol. 213. Addison-Wesley.Google Scholar
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. & Hwang, D. U. 2006 Complex networks: structure and dynamics. Phys. Rep. 424 (4–5), 175–308.Google Scholar
Cabral, J., Kringelbach, M. L. & Deco, G. 2017 Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: models and mechanisms. NeuroImage 160, 84–96.Google Scholar
Candel, S. 2002 Combustion dynamics and control: progress and challenges. Proc. Combust. Inst. 29 (1), 1–28.Google 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), 61–84.Google Scholar
Coats, C. M. 1996 Coherent structures in combustion. Prog. Energy Combust. Sci. 22 (5), 427–509.Google Scholar
Deb, D., Vishveshwara, S. & Vishveshwara, S. 2009 Understanding protein structure from a percolation perspective. Biophys. J. 97 (6), 1787–1794.Google Scholar
Dimitriadis, S. I., Laskaris, N. A., Tsirka, V., Vourkas, M., Micheloyannis, S. & Fotopoulos, S. 2010 Tracking brain dynamics via time-dependent network analysis. J. Neurosci. Meth. 193 (1), 145–155.Google Scholar
Donges, J. F., Zou, Y., Marwan, N. & Kurths, J. 2009 Complex networks in climate dynamics. Eur. Phys. J. 174 (1), 157–179.Google Scholar
Doron, K. W., Bassett, D. S. & Gazzaniga, M. S. 2012 Dynamic network structure of interhemispheric coordination. Proc. Natl Acad. Sci. USA 109 (46), 18661–18668.Google Scholar
Emerson, B., O’Connor, J., Juniper, M. & Lieuwen, T. 2012 Density ratio effects on reacting bluff-body flow field characteristics. J. Fluid Mech. 706, 219–250.Google Scholar
Fornito, A., Zalesky, A. & Bullmore, E. 2016 Fundamentals of Brain Network Analysis. Academic Press.Google Scholar
Gallos, L., Sigman, M. & Makse, H. 2012 The conundrum of functional brain networks: small-world efficiency or fractal modularity. Front. Physiol. 3, 123.Google Scholar
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, 615–644.Google 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.Google Scholar
Gotoda, H., Amano, M., Miyano, T., Ikawa, T., Maki, K. & Tachibana, S. 2012 Characterization of complexities in combustion instability in a lean premixed gas-turbine model combustor. Chaos 22 (4), 043128.Google 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.Google Scholar
Gotoda, H., Nikimoto, H., Miyano, T. & Tachibana, S. 2011 Dynamic properties of combustion instability in a lean premixed gas-turbine combustor. Chaos 21 (1), 013124.Google 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.Google Scholar
Hagberg, A. A., Schult, D. A. & Swart, P. J. 2008 Exploring network structure, dynamics, and function using NetworkX. In Proceedings of the 7th Python in Science Conference (SciPy2008), Pasadena, CA, USA (ed. Varoquaux, G., Vaught, T. & Millman, J.), pp. 11–15.Google Scholar
Hegde, U. G., Reuter, D. & Zinn, B. T. 1988 Sound generation by ducted flames. AIAA J. 26 (5), 532–537.Google Scholar
Holme, P. & Saramäki, J. 2012 Temporal networks. Phys. Rep. 519 (3), 97–125.Google Scholar
Huang, Y. & Ratner, A. 2009 Experimental investigation of thermoacoustic coupling for low-swirl lean premixed flames. J. Propul. Power 25 (2), 365–373.Google Scholar
Hult, J., Meier, U., Meier, W., Harvey, A. & Kaminski, C. F. 2005 Experimental analysis of local flame extinction in a turbulent jet diffusion flame by high repetition 2-D laser techniques and multi-scalar measurements. Proc. Combust. Inst. 30 (1), 701–709.Google Scholar
Hurle, I. R., Price, R. B., Sugden, T. M. & Thomas, A. 1968 Sound emission from open turbulent premixed flames. Proc. R. Soc. Lond. A 303 (1475), 409–427.Google Scholar
Juniper, M. P. & Sujith, R. I. 2018 Sensitivity and nonlinearity of thermoacoustic oscillations. Annu. Rev. Fluid Mech. 50, 661–689.Google Scholar
Kheirkhah, S., Cirtwill, J. 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, 319–334.Google Scholar
Kheirkhah, S., Geraedts, B. D., Saini, P., Venkatesan, K. & Steinberg, A. M. 2016 Non-stationary local thermoacoustic phase relationships in a gas turbine combustor. Proc. Combust. Inst. 36 (3), 3873–3880.Google 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
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), 4972–4975.Google Scholar
Lee, J. G. & Santavicca, D. A. 2003 Experimental diagnostics for the study of combustion instabilities in lean premixed combustors. J. Propul. Power 19 (5), 735–750.Google Scholar
Lieuwen, T. C. 2002 Experimental investigation of limit-cycle oscillations in an unstable gas turbine combustor. J. Propul. Power 18 (1), 61–67.Google Scholar
Lieuwen, T. C. & Banaszuk, A. 2005 Background noise effects on combustor stability. J. Propul. Power 21 (1), 25–31.Google Scholar
Lu, Z., Yuan, N. & Fu, Z. 2016 Percolation phase transition of surface air temperature networks under attacks of El Niño/La Niña. Sci. Rep. 6, 26779.Google Scholar
Malik, N., Bookhagen, B., Marwan, N. & Kurths, J. 2012 Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks. Climate Dyn. 39 (3–4), 971–987.Google Scholar
McManus, K. R., Poinsot, T. & Candel, S. M. 1993 A review of active control of combustion instabilities. Prog. Energy Combust. Sci. 19 (1), 1–29.Google Scholar
Molkenthin, N., Rehfeld, K., Marwan, N. & Kurths, J. 2014 Networks from flows – from dynamics to topology. Sci. Rep. 4, 4119.Google 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, 659–681.Google Scholar
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, 225–245.Google 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), 273–290.Google Scholar
Nair, V., Thampi, G. & Sujith, R. I. 2014 Intermittency route to thermoacoustic instability in turbulent combustors. J. Fluid Mech. 756, 470–487.Google Scholar
Newman, M. 2010 Networks. Oxford University Press.Google Scholar
Nicosia, V., Tang, J., Musolesi, M., Russo, G., Mascolo, C. & Latora, V. 2012 Components in time-varying graphs. Chaos 22 (2), 023101.Google Scholar
Noiray, N. & Schuermans, B. 2013a Deterministic quantities characterizing noise driven Hopf bifurcations in gas turbine combustors. Intl J. Non-Linear Mech. 50, 152–163.Google Scholar
Noiray, N. & Schuermans, B. 2013b On the dynamic nature of azimuthal thermoacoustic modes in annular gas turbine combustion chambers. Proc. R. Soc. Lond. A 469 (2151), 20120535.Google Scholar
Nori, V. & Seitzman, J. 2008 Evaluation of chemiluminescence as a combustion diagnostic under varying operating conditions. In 46th AIAA Aerospace Sciences Meeting and Exhibit, p. 953.Google 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.Google Scholar
Paschereit, C. O., Gutmark, E. & Weisenstein, W. 1999 Coherent structures in swirling flows and their role in acoustic combustion control. Phys. Fluids 11 (9), 2667–2678.Google Scholar
Pawar, S. A., Mondal, S., George, N. B. & Sujith, R. I. 2018 Synchronization behaviour during the dynamical transition in swirl-stabilized combustor: temporal and spatiotemporal analysis. In 2018 AIAA Aerospace Sciences Meeting, p. 0394.Google Scholar
Pawar, S. A., Seshadri, A., Unni, V. R. & Sujith, R. I. 2017 Thermoacoustic instability as mutual synchronization between the acoustic field of the confinement and turbulent reactive flow. J. Fluid Mech. 827, 664–693.Google Scholar
Pawar, S. A. & Sujith, R. I. 2018 Transition to thermoacoustic instability in a turbulent combustor. J. Combust. Soc. Japan 60 (192), 99–111.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, 265–292.Google Scholar
Poinsot, T. & Veynante, D. 2005 Theoretical and Numerical Combustion. RT Edwards, Inc.Google Scholar
Putnam, A. A. 1971 Combustion Driven Oscillations in Industry. Elsevier.Google Scholar
Raffel, M., Willert, C.E. & Kompenhans, J. 2007 Particle Image Velocimetry: A Practical Guide. Springer.Google Scholar
Rayleigh, J. W. S. 1878 The explanation of certain acoustical phenomena. Nature 18 (455), 319–321.Google Scholar
Rogers, D. E. & Marble, F. E. 1956 A mechanism for high-frequency oscillation in ramjet combustors and afterburners. J. Jet Propul. 26 (6), 456–462.Google Scholar
Scarsoglio, S., Iacobello, G. & Ridolfi, L. 2016 Complex networks unveiling spatial patterns in turbulence. Intl J. Bifurcation Chaos 26 (13), 1650223.Google 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), 117–132.Google Scholar
Schwing, J., Sattelmayer, T. & Noiray, N. 2011 Interaction of vortex shedding and transverse high-frequency pressure oscillations in a tubular combustion chamber. In ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition, pp. 259–268. American Society of Mechanical Engineers.Google Scholar
Seshadri, A., Nair, V. & Sujith, R. I. 2016 A reduced-order deterministic model describing an intermittency route to combustion instability. Combust. Theor. Model. 20 (3), 441–456.Google Scholar
Shanbhogue, S. J.2008. Dynamics of perturbed exothermic bluff-body flow-fields. Doctoral dissertation, Georgia Institute of Technology.Google Scholar
Singh, J., Belur Vishwanath, R., Chaudhuri, S. & Sujith, R. I. 2017 Network structure of turbulent premixed flames. Chaos 27 (4), 043107.Google Scholar
Smith, D. A. & Zukoski, E. 1985 Combustion instability sustained by unsteady vortex combustion. In 21st Joint Propulsion Conference, p. 1248.Google Scholar
Strahle, W. C. 1971 On combustion generated noise. J. Fluid Mech. 49 (2), 399–414.Google Scholar
Strogatz, S. H. 2001 Exploring complex networks. Nature 410 (6825), 268–276.Google Scholar
Tachibana, S., Kanai, K., Yoshida, S., Suzuki, K. & Sato, T. 2015 Combined effect of spatial and temporal variations of equivalence ratio on combustion instability in a low-swirl combustor. Proc. Combust. Inst. 35 (3), 3299–3308.Google Scholar
Taira, K., Nair, A. G. & Brunton, S. L. 2016 Network structure of two-dimensional decaying isotropic turbulence. J. Fluid Mech. 795, R2.Google Scholar
Tang, J., Scellato, S., Musolesi, M., Mascolo, C. & Latora, V. 2010 Small-world behavior in time-varying graphs. Phys. Rev. E 81 (5), 055101.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.Google Scholar
Tsonis, A. A. & Roebber, P. J. 2004 The architecture of the climate network. Physica 333, 497–504.Google 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.Google Scholar
Unni, V. R. & Sujith, R. I. 2015 Multifractal characteristics of combustor dynamics close to lean blowout. J. Fluid Mech. 784, 30–50.Google Scholar
Unni, V. R. & Sujith, R. I. 2017 Flame dynamics during intermittency in a turbulent combustor. Proc. Combust. Inst. 36 (3), 3791–3798.Google Scholar
Valencia, M., Martinerie, J., Dupont, S. & Chavez, M. 2008 Dynamic small-world behavior in functional brain networks unveiled by an event-related networks approach. Phys. Rev. E 77 (5), 050905.Google Scholar
Watts, D. J. & Strogatz, S. H. 1998 Collective dynamics of ‘small-world’ networks. Nature 393 (6684), 440–442.Google Scholar
Weber, J. K. & Pande, V. S. 2015 Percolation-like phase transitions in network models of protein dynamics. J. Chem. Phys. 142 (21), 215105.Google Scholar
Zhang, Y., Zhao, D., Zhang, J., Xiong, R. & Gao, W. 2011 Interpolation-dependent image downsampling. IEEE Trans. Image Process. 20 (11), 3291–3296.Google Scholar