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SLOW-BURNING INSTABILITIES OF DUFORT–FRANKEL FINITE DIFFERENCING

Published online by Cambridge University Press:  30 April 2021

DAVID GALLOWAY
Affiliation:
School of Mathematics and Statistics, University of Sydney, Sydney, NSW2006, Australia; david.ivers@sydney.edu.au.
DAVID IVERS*
Affiliation:
School of Mathematics and Statistics, University of Sydney, Sydney, NSW2006, Australia; david.ivers@sydney.edu.au.

Abstract

DuFort–Frankel averaging is a tactic to stabilize Richardson’s unstable three-level leapfrog timestepping scheme. By including the next time level in the right-hand-side evaluation, it is implicit, but it can be rearranged to give an explicit updating formula, thus apparently giving the best of both worlds. Textbooks prove unconditional stability for the heat equation, and extensive use on a variety of advection–diffusion equations has produced many useful results. Nonetheless, for some problems the scheme can fail in an interesting and surprising way, leading to instability at very long times. An analysis for a simple problem involving a pair of evolution equations that describe the spread of a rabies epidemic gives insight into how this occurs. An even simpler modified diffusion equation suffers from the same instability. Finally, the rabies problem is revisited and a stable method is found for a restricted range of parameter values, although no prescriptive recipe is known which selects this particular choice.

Type
Research Article
Copyright
© Australian Mathematical Society 2021

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References

Ames, W. F., “Numerical methods for partial differential equations”, Computer science and scientific computing, 3rd edn (Academic Press, Boston, MA, 1992); ISBN: 0-12-056761-X.Google Scholar
Du Fort, E. C. and Frankel, S. P., “Stability conditions in the numerical treatment of parabolic differential equations”, Math. Tables Other Aids Comput. 7 (1953) 135152; doi:10.2307/2002754.CrossRefGoogle Scholar
Fornberg, B., “On the instability of leap-frog and Crank–Nicolson approximations of a nonlinear partial differential equation”, Math. Comp. 27 (1973) 4557; doi:10.2307/2005246.CrossRefGoogle Scholar
Galloway, D. J. and Moore, D. R., “Axisymmetric convection in the presence of a magnetic field”, Geophys. Astrophys. Fluid Dyn. 12 (1979) 73106; doi:10.1080/03091927908242678.CrossRefGoogle Scholar
Galloway, D. J. and Weiss, N. O., “Convection and magnetic fields in stars”, Astrophys. J. 243 (1981) 945953; doi:10.1086/158659.CrossRefGoogle Scholar
Henery, R., Farnell, L., Gibson, W. G. and Bennett, M. R., “Potential fields in vascular smooth muscle generated by transmitter release from sympathetic varicosities”, J. Theoret. Biol. 218 (2002) 531548; doi:10.1016/S0022-5193(02)93098-5.CrossRefGoogle ScholarPubMed
Jones, C. A. and Galloway, D. J., “Axisymmetric magnetoconvection in a twisted field”, J. Fluid Mech. 253 (1993) 297326; doi:10.1017/S0022112093001806.CrossRefGoogle Scholar
Jury, E. I. and Bharucha, B. H., “Notes on the stability criterion for linear discrete systems”, IRE Trans. Automat. Control 6 (1961) 8890; doi:10.1109/TAC.1961.6429319.CrossRefGoogle Scholar
Kato, T., Perturbation theory for linear operators, 2nd edn (Springer-Verlag, Berlin, 1976); doi:10.1007/978-3-642-66282-9.Google Scholar
Kirk, J. G. and Galloway, D. J., “The evolution of a test particle distribution in a strongly magnetised plasma”, Plasma Phys. 24 (1982) 339359; doi:10.1088/0032-1028/24/8/512.CrossRefGoogle Scholar
Kramer, S., “There was a little girl: its first printings–its authorship–its variants”, Pap. Bibliogr. Soc. Am. 40 (1946) 287310; http://www.jstor.org/stable/24298820.Google Scholar
Lambert, J. D., Numerical methods for ordinary differential systems: The initial value problem (John Wiley & Sons, Chichester, 1991); ISBN: 978-0-471-92990-1.Google Scholar
Moore, D. R. and Weiss, N. O., “2-dimensional Rayleigh–Benard convection”, J. Fluid Mech. 58 (1973) 289312; doi:10.1017/S0022112073002600.CrossRefGoogle Scholar
Morton, K. W. and Mayer, D. F., Numerical solution of partial differential equations (Cambridge University Press, Cambridge, 2005); ISBN: 9780521607933.CrossRefGoogle Scholar
Murray, J. D., Mathematical biology. II: Spatial models and biomedical applications, 3rd edn, Volume 18 of Interdiscip. Appl. Math. Ser. (Springer-Verlag, New York, 2003); ISBN: 978-0-387-95228-4.CrossRefGoogle Scholar
Noye, J., “Finite difference techniques for partial differential equations”, in: Computational techniques for differential equations, Volume 83 of North-Holland Math. Stud. (Elsevier, North-Holland, Amsterdam, 1984) 95354; doi:10.1016/S0304-0208(08)71201-5.CrossRefGoogle Scholar
Roache, P. J., Computational fluid dynamics (Hermosa Publishers, Albuquerque, NM, 1976), with an appendix (“On artificial viscosity”) reprinted from J. Comput. Phys. 10 (1972) 169184, Revised printing.Google Scholar
Roberts, K. V. and Weiss, N. O., “Convective difference schemes”, Math. Comp. 20 (1966) 272299; doi:10.2307/2003507.CrossRefGoogle Scholar
Taylor, P. J., “The stability of the Du Fort–Frankel method for the diffusion equation with boundary conditions involving space derivatives”, Comput. J. 13 (1970) 9297; doi:10.1093/comjnl/13.1.92.CrossRefGoogle Scholar
Weiss, N. O., “The expulsion of magnetic flux by eddies”, Proc. R. Soc. Lond. Ser. A 293 (1966) 310328; http://adsabs.harvard.edu/abs/1966RSPSA.293.310W.Google Scholar
Zheligovsky, V. A. and Galloway, D. J., “Dynamo action in Christopherson hexagonal flow”, Geophys. Astrophys. Fluid Dyn. 88 (1998) 277293; doi:10.1080/03091929808245477.CrossRefGoogle Scholar