2010
DOI: 10.1051/m2an/2010057
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Optimized Schwarz coupling of Bidomain and Monodomain models in electrocardiology

Abstract: Abstract. The Bidomain model is nowadays one of the most accurate mathematical descriptions of the action potential propagation in the heart. However, its numerical approximation is in general fairly expensive as a consequence of the mathematical features of this system. For this reason, a simplification of this model, called Monodomain problem is quite often adopted in order to reduce computational costs. Reliability of this model is however questionable, in particular in the presence of applied currents and … Show more

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Cited by 25 publications
(17 citation statements)
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“…Due to a dimensional mismatch between the two models, two interface conditions are needed on the Bidomain side of the interface, and one on the Monodomain side [6]. Possible coupling conditions are …”
Section: Coupling Conditions and Optimized Schwarz Methodsmentioning
confidence: 99%
See 3 more Smart Citations
“…Due to a dimensional mismatch between the two models, two interface conditions are needed on the Bidomain side of the interface, and one on the Monodomain side [6]. Possible coupling conditions are …”
Section: Coupling Conditions and Optimized Schwarz Methodsmentioning
confidence: 99%
“…To cope with the mismatch, the second condition in (8) is a transparent boundary condition, designed to avoid spurious reflexions off the interface for the extracellular potential wave. The convergence of the Optimized Schwarz Algorithm based on the interface conditions (8)- (9) was analyzed in [6], where also optimal parameters has been identified by means of Fourier analysis.…”
Section: Coupling Conditions and Optimized Schwarz Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…The advantage of IMEX and operator splitting schemes is that they only require the solution of linear systems at each time step. Many different preconditioners have been proposed in order to devise efficient iterative solvers for such linear systems: SSOR [16], block diagonal or triangular [17,18,19,20,21,22,23], optimized Schwarz [24,25], geometric multigrid [26,27], algebraic multigrid [28,17,29,18,19], multilevel Schwarz [30,31,32], Neumann-Neumann and BDDC [33,34] preconditioners.…”
Section: Introductionmentioning
confidence: 99%