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Conservative finite element methods for Kirchhoff-type equations

Dörich, Benjamin ORCID iD icon 1; Krumbiegel, Felix; Rogava, Jemal; Rupp, Andreas; Vashakidze, Zurab
1 Institut für Angewandte und Numerische Mathematik (IANM), Karlsruher Institut für Technologie (KIT)

Abstract:

We construct and analyse a fully discrete scheme for a Kirchhoff-type nonlinear integro-differential equation in two spatial dimensions with time-dependent coefficients. The scheme combines a symmetric three-layer time discretization of Crank–Nicolson type with a conforming finite element method of arbitrary polynomial degree $p$ and a Picard iteration for the nonlinearity. We prove that the Picard iteration is well defined and, that the iterates converge to the Ritz projection of the exact solution measured in fractional-power norms of energy argument in the unshifted norms, and under the same hypotheses, we then obtain the optimal order $\mathcal{O}(h^{p+1} + \tau^2)$ in $L^2$ and $\mathcal{O}(h^p+ \tau^2)$ in $H^1$ for the full error.
For the homogeneous problem with constant coefficients, the exact solution of the scheme moreover preserves a discrete energy identically. Numerical experiments with manufactured solutions reproduce the predicted second order in time and the full spatial order $h^{p+1}$ in the $L^2$-norm.


Volltext §
DOI: 10.5445/IR/1000198608
Veröffentlicht am 30.10.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Sonderforschungsbereich 1173 (SFB 1173)
Publikationstyp Forschungsbericht/Preprint
Publikationsmonat/-jahr 10.2026
Sprache Englisch
Identifikator ISSN: 2365-662X
KITopen-ID: 1000198608
Verlag Karlsruher Institut für Technologie (KIT)
Umfang 26 S.
Serie CRC 1173 Preprint ; 2026/59
Projektinformation SFB 1173, 258734477 (DFG, DFG KOORD, SFB 1173/3)
Externe Relationen Abstract/Volltext
Forschungsdaten/Software
Schlagwörter Kirchhoff-type equation, nonlinear wave equation, finite element method, three-layer scheme, Picard iteration, optimal-order error estimate
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