Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-28T21:49:08.471Z Has data issue: false hasContentIssue false

Asymptotic and numerical study of Brusselator chaos

Published online by Cambridge University Press:  16 July 2009

Klaus Deller
Affiliation:
Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208, USA
Thomas Erneux
Affiliation:
Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208, USA
Alvin Bayliss
Affiliation:
Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208, USA

Abstract

We investigate the Brusselator reaction–diffusion equations with periodic boundary conditions. We consider the range of values of the parameters used by Kuramoto in his study of chaotic concentration waves. We determine numerically the bifurcation diagram of the long-time travelling and standing wave solutions using a highly accurate Fourier pseudo-spectral method. For moderate values of the bifurcation parameter, we have found a sequence of instabilities leading either to periodic and quasiperiodic standing waves, or to chaotic regimes. However, for large values of the control parameter, we have found only uniform time-periodic solutions or time-periodic travelling wave solutions. Our numerical study motivates a new asymptotic analysis of the Brusselator equations for large values of the control parameter and small diffusion coefficients. This analysis explains the numerical predictions. The chaotic regime is limited to moderate values of the control parameter and periodic solutions are the only solutions for large values of the control parameter. We identify the stabilizing mechanism as the relaxation oscillations which appear when the control parameter is large. Our asymptotic result on the stability of periodic solutions is then generalized to a class of two-variable reaction-diffusion equations.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1991

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arneodo, A. & Elezgaray, J. 1990 Spatiotemporal patterns and diffusion-induced chaos in a chemical system with equal diffusion coefficients. Phys. Lett. A143, 2533.CrossRefGoogle Scholar
Bayliss, A. & Matkowsky, B. J. 1990 Two routes to chaos in condensed phase combustion. To appear in SIAM J. Appl. Math. 50, 437459.Google Scholar
Bayliss, A., Gottlieb, D., Matkowsky, B. J. & Minkoff, M. 1989 An adaptive pseudo-spectral method for reaction–diffusion problems. J. Comput. Phys. 81, 421443.CrossRefGoogle Scholar
Bergé, P., Pomeau, Y. & Vidal, C. 1984 Order within Chaos. John Wiley.Google Scholar
Boa, J. A. 1976 Asymptotic calculation of a limit cycle. J. Math. Anal. and Appl. 54, 115137.CrossRefGoogle Scholar
Canuto, C., Hussaini, M. Y., Quarteroni, A. & Zang, T. A. 1988 Spectral Methods in Fluid Dynamics. Springer-Verlag.CrossRefGoogle Scholar
De Kepper, P., Boissonade, J. & Epstein, I. R. 1990 Chlorite–iodide reaction: a versatile system for the study of nonlinear dynamical behavior. J. Phys. Chem. 94, 65256536.CrossRefGoogle Scholar
Doelman, A. 1990 Finite dimensional models of the Ginzburg–Landau equation. Nonlinearity 4, 231250.CrossRefGoogle Scholar
Field, R. J. & Burger, M., eds. 1985 Oscillating and Travelling Waves in Chemical Systems. Wiley.Google Scholar
Gottlieb, D. & Orszag, S. A. 1977 Numerical analysis of spectral methods: theory and applications. C.B.M.S–N.S.F. Conference Series in Applied Mathematics,SIAM,PA, USA.CrossRefGoogle Scholar
Grasman, J. 1987 Asymptotic methods for relaxation oscillations and applications. Appl. Math. Sci. 63, Springer-Verlag.Google Scholar
Kervokian, J. & Cole, J. D. 1981 Perturbation methods in applied mathematics. Appl. Math. Sc. 34, Springer-Verlag.Google Scholar
Kuramoto, Y. 1978 Diffusion-induced chaos in reaction systems. Suppl. Prog. Theor. Phys. 64, 346367.CrossRefGoogle Scholar
Kuramoto, Y. 1984 Chemical Oscillations, Waves, and Turbulence. Springer Series in Synergetics.CrossRefGoogle Scholar
Lefever, R., Lugiato, L. A., Kaige, W., Abraham, N. B. & Mandel, P. 1990 Phase dynamics of transverse diffraction patterns in the laser. Phys. Lett. A 135, 254257.Google Scholar
Michelson, D. M. & Sivashinsky, G. I. 1977 Nonlinear analysis of hydrodynamic instability in laminar flames – II. Numerical experiments. Acta Astronautica 4, 1207.CrossRefGoogle Scholar
Newton, P. K. & Sirovich, L. 1986 Instabilities of the Ginzburg–Landau equation: part II, secondary bifurcation. Quart. Appl. Math. 44, 367374.CrossRefGoogle Scholar
Nicolis, G. & Prigogine, I. 1977 Self-Organization in Nonequilibrium Systems. Wiley-Interscience.Google Scholar
Nicolis, G., Erneux, T. & Herschkowitz-Kaufman, M. 1978 Pattern formation in reacting and diffusing systems. Adv. Chem. Phys. 38, 263315.Google Scholar
Sivashinsky, G. I. 1980 On flame propagation under conditions of stoichiometry. SIAM J. App. Math. 39, 6782.CrossRefGoogle Scholar
Turner, J. W. 1974 Asymptotic behavior of nonlinear oscillations in a chemical system. Trans. New York Acad. Sciences 36, 800806.CrossRefGoogle Scholar
Tyson, J. J. 1977 Analytic representation of oscillations, excitability and traveling waves in a realistic model of the Belousov–Zhabotinskii reaction. J. Chem. Phys. 66, 905915.CrossRefGoogle Scholar
Tyson, J. J. 1984 Relaxation oscillations in the revised Oregonator. J. Chem. Phys. 80, 60796082.CrossRefGoogle Scholar