Geometry of the Computational Singular Perturbation Method
Mathematical modelling of natural phenomena, Tome 10 (2015) no. 3, pp. 16-30.

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The Computational Singular Perturbation (CSP) method, developed by Lam and Goussis [Twenty-Second Symposium (International) on Combustion, The Combustion Institute, Pittsburgh, 1988, pp. 931–941], is a commonly-used method for finding approximations of slow manifolds in systems of ordinary differential equations (ODEs) with multiple time scales. The validity of the CSP method was established for fast–slow systems with a small parameter ε by the authors in [Journal of Nonlinear Science, 14 (2004), 59–91]. In this article, we consider a more general class of ODEs which lack an explicit small parameter ε, but where fast and slow variables are nevertheless separated by a spectral gap. First, we show that certain key quantities used in the CSP method are tensorial and thus invariant under coordinate changes in the state space. Second, we characterize the slow manifold in terms of these key quantities and explain how these characterizations are related to the invariance equation. The implementation of the CSP method can be either as a one-step or as a two-step procedure. The one-step CSP method aims to approximate the slow manifold; the two-step CSP method goes one step further and aims to decouple the fast and slow variables at each point in the state space. We show that, in either case, the operations of changing coordinates and performing one iteration of the CSP method commute. We use the commutativity property to give a new, concise proof of the validity of the CSP method for fast–slow systems and illustrate with an example due to Davis and Skodje. Dedicated to Professor Alexander Gorban on the occasion of his sixtieth birthday
DOI : 10.1051/mmnp/201510303

Hans G. Kaper 1 ; Tasso J. Kaper 2 ; Antonios Zagaris 3

1 Department of Mathematics and Statistics, Georgetown University Washington, D.C. 20057, USA
2 Department of Mathematics and Statistics, Boston University Boston, MA 02215, USA
3 Applied Analysis and Mathematical Physics University of Twente, 7522NB Enschede, the Netherlands
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Hans G. Kaper; Tasso J. Kaper; Antonios Zagaris. Geometry of the Computational Singular Perturbation Method. Mathematical modelling of natural phenomena, Tome 10 (2015) no. 3, pp. 16-30. doi : 10.1051/mmnp/201510303. http://geodesic.mathdoc.fr/articles/10.1051/mmnp/201510303/

[1] T.M.K. Coles, H.N Najm, Y.M. Marzouk. CSP simplification of chemical kinetic systems under uncertainty. In: Proc. Third IWMRRF. Corfu, Greece, April 27-29, 2011, 331–334.

[2] B.J. Debusschere, Y.M. Marzouk, H.N. Najm, B. Rhoads, D.A. Goussis, M. Valorani Combust. Theor. Model. 2012 173 198

[3] M.J. Davis, R.T. Skodje J. Chem. Phys. 1999 859 874

[4] B.A. Dubrovin, A.T. Fomenko, S.P. Novikov. Modern Geometry – Methods and Applications, vol. 2. Graduate Texts in Mathematics, 104. Springer-Verlag, New York, 1985.

[5] N. Fenichel 1979 53 98

[6] A.N. Gorban, I.V. Karlin Chem. Eng. Sci. 2003 4751 4768

[7] A.N. Gorban, I.V. Karlin. Invariant Manifolds for Physical and Chemical Kinetics. Springer, Berlin, 2004.

[8] A.N. Gorban, I.V. Karlin Bulletin Amer. Math. Soc. 2014 187 246

[9] A.N. Gorban, I.V. Karlin, A.Yu. Zinovyev Phys. Reports 2004 197 403

[10] A.N. Gorban, N. Kazantzis, Y.G. Kevrekidis, H.C. Ottinger, and C. Theodoropoulos (eds.). Model Reduction and Coarse-Graining Approaches for Multiscale Phenomena. Springer, Berlin, 2006.

[11] D.A. Goussis, S.H. Lam. A study of homogeneous methanol oxidation kinetics using CSP. In: Proceedings of the Twenty-Fourth Symposium (International) on Combustion, The University of Sydney, Sydney, Australia, July 5–10, 1992. The Combustion Institute, Pittsburgh, 1992, 113–120.

[12] D. Goussis, U. Maas. Model reduction for combustion chemistry. In: Turbulent Combustion Modeling, Fluid Mechanics and Its Applications, vol. 95. Springer, (2011), 193–220.

[13] D. Goussis, H.N. Najm Multiscale Model. Sim. 2006 1297 1332

[14] D. Goussis, M. Valorani J. Comp. Phys. 2006 316 346

[15] S. Gupta. High-Fidelity Simulation and Analysis of Ignition Regimes and Mixing Characteristics for Low Temperature Combustion Engine Applications. Ph.D. Thesis, U. Michigan, 2012.

[16] M. Hadjinicolaou, D.A. Goussis SIAM J. Sci. Comput. 1999 781 810

[17] H. Hardin, A. Zagaris, K. Krab, H.W. Westerhoff Fed. Eur. Biochem. Soc. J. 2009 5491 5506

[18] C.K.R.T. Jones. Geometric singular perturbation theory. In: Dynamical Systems, Montecatini Terme, L. Arnold, Lecture Notes in Mathematics, 1609. Springer-Verlag, Berlin, 1994, 44–118.

[19] H.G. Kaper, T.J. Kaper Physica D 2002 66 93

[20] P.D. Kourdis, A.G. Palasantza, D.A. Goussis Comp. Math. Appl. 2013 1516 1534

[21] P.D. Kourdis, R. Steuer, D.A. Goussis Physica D 2010 1798 1817

[22] S.H. Lam Combust. Sci. Tech. 1993 375 404

[23] S.H. Lam Combust. Sci. Tech. 2007 767 786

[24] S.H. Lam, D.A. Goussis. Understanding complex chemical kinetics with computational singular perturbation. In: Proceedings of the Twenty-Second Symposium (International) on Combustion, The University of Washington, Seattle, Washington, August 14–19, 1988. The Combustion Institute, Pittsburgh, 1988, 931–941.

[25] S.H. Lam, D.A. Goussis. Conventional asymptotics and computational singular perturbation theory for simplified kinetics modeling. In: Reduced Kinetic Mechanisms and Asymptotic Approximations for Methane-Air Flames, M. Smooke (ed.). Lecture Notes in Physics, 384. Springer-Verlag, New York, 1991, Chapter 10.

[26] S.H. Lam, D.A. Goussis Internat. J. Chem. Kin. 1994 461 486

[27] T. Lovas, E. Mastorakos, D.A. Goussis Reduction of the RACM scheme using CSP in atmospheric chemistry modeling. J Geophys. Res. - Atmos. 2006 1 16

[28] T.F. Lu, Y.G. Ju, C.K. Law Combust. Flame 2001 1445 1455

[29] A. Massias, D. Diamantis, E. Mastorakos, D. Goussis Combust. Theor. Model. 1999 233 257

[30] M.K. Neophytou, D.A. Goussis, M. Van Loon, E. Mastorakos Atmos. Environ. 2004 3661 3673

[31] P.J. Olver. Applications of Lie Groups to Differential Equations, Graduate Texts in Mathematics, vol. 107. Springer-Verlag, New York, 1986.

[32] M. Valorani, F. Creta, D.A. Goussis, H.N. Najm, J.C. Lee Combust. Flame 2006 29 51

[33] M. Valorani, D.A. Goussis, F. Creta, H.N. Najm J. Comp. Phys. 2005 754 786

[34] M. Valorani, D.A. Goussis J. Comput. Phys. 2001 44 79

[35] M. Valorani, H.M. Najm, D.A. Goussis Combust. Flame 2003 35 53

[36] A. Zagaris, H.G. Kaper, T.J. Kaper J. Nonlin. Sci. 2004 59 91

[37] A. Zagaris, H.G. Kaper, T.J. Kaper Multiscale Model. Sim. 2004 613 638

[38] A. Zagaris, H.G. Kaper, T.J. Kaper 2005 1629 1642

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