2007
DOI: 10.1002/pamm.200700767
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Patch dynamics: macroscopic simulation of multiscale systems

Abstract: We describe a numerical algorithm to perform time integration of a partial differential equation (PDE) which is not available in closed from; instead we are given a more microscopic description of the system behaviour. The proposed methods mimic a macroscopic finite difference (FD) or finite volume (FV) scheme for the unavailable PDE; they extract a macroscopic time derivative (for FD schemes) or flux (for FV schemes) from appropriately initialized, but otherwise unconstrained simulations with the given micros… Show more

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Cited by 4 publications
(4 citation statements)
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“…The HMM method we suggest here is described in three separate steps. We follow the same strategy as in [1] for parabolic equations and in [14] for the onedimensional advection equation. See [8], [9] and [2] for additional details and proofs.…”
Section: Description Of the Methodsmentioning
confidence: 99%
“…The HMM method we suggest here is described in three separate steps. We follow the same strategy as in [1] for parabolic equations and in [14] for the onedimensional advection equation. See [8], [9] and [2] for additional details and proofs.…”
Section: Description Of the Methodsmentioning
confidence: 99%
“…The HMM algorithm we use here is based on a central finite difference scheme fitted in the framework described in [1]. It is similar to the schemes in [3], for parabolic equations, and in [5] for the one dimensional advection equation. A more detailed description of the HMM algorithm follows:…”
Section: Heterogeneous Multiscale Methodsmentioning
confidence: 99%
“…We follow the same strategy as in [1] for parabolic equations and in [19] for the one-dimensional advection equation. See also [8].…”
Section: Hmm For the Wave Equationmentioning
confidence: 99%
“…c.f. discussion about micro solver boundary conditions in [19]. In this way we do not need to worry about the effects of boundary conditions.…”
Section: Hmm For the Wave Equationmentioning
confidence: 99%