Articles with "bdf methods" as a keyword



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Linearly implicit BDF methods for nonlinear parabolic interface problems

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Published in 2017 at "BIT Numerical Mathematics"

DOI: 10.1007/s10543-016-0641-x

Abstract: We analyze linearly implicit BDF methods for the time discretization of a nonlinear parabolic interface problem, where the computational domain is divided into two subdomains by an interface, and the nonlinear diffusion coefficient is discontinuous… read more here.

Keywords: implicit bdf; nonlinear parabolic; bdf methods; linearly implicit ... See more keywords
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New class of hybrid BDF methods for the computation of numerical solutions of IVPs

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Published in 2017 at "Numerical Algorithms"

DOI: 10.1007/s11075-017-0433-7

Abstract: A new class of hybrid BDF-like methods is presented for solving systems of ordinary differential equations (ODEs) by using the second derivative of the solution in the stage equation of class 2 + 1hybrid BDF-like… read more here.

Keywords: new class; class; bdf methods; hybrid bdf ... See more keywords
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Construction of Implicit–Explicit Second-Derivative BDF Methods

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Published in 2018 at "Bulletin of the Iranian Mathematical Society"

DOI: 10.1007/s41980-018-0065-2

Abstract: In many applications, large systems of ordinary differential equations with both stiff and nonstiff parts have to be solved numerically. Implicit–explicit (IMEX) methods are useful for efficiently solving these problems. In this paper, we construct… read more here.

Keywords: construction implicit; implicit explicit; derivative bdf; bdf methods ... See more keywords
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Gradient stability of high-order BDF methods and some applications

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Published in 2020 at "Journal of Difference Equations and Applications"

DOI: 10.1080/10236198.2019.1709062

Abstract: It is well-known that the backward differentiation formulae (BDF) of order 1, 2 and 3 are gradient stable. This means that when such a method is used for the time discretization of a gradient flow,… read more here.

Keywords: order; gradient stable; bdf methods; applications gradient ... See more keywords