2001
DOI: 10.1051/0004-6361:20010157
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A 3D MHD model of astrophysical flows: Algorithms, tests and parallelisation

Abstract: Abstract. In this paper we describe a numerical method designed for modelling different kinds of astrophysical flows in three dimensions. Our method is a standard explicit finite difference method employing the local shearingbox technique. To model the features of astrophysical systems, which are usually compressible, magnetised and turbulent, it is desirable to have high spatial resolution and large domain size to model as many features as possible, on various scales, within a particular system. In addition, … Show more

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Cited by 54 publications
(60 citation statements)
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References 42 publications
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“…SAC is the reconfigurable multi-dimensional ideal MHD solver which is designed to simulate the nonlinear interaction of an arbitrary perturbation with a gravitationally stratified background model, i.e., a model of the solar atmosphere, in magnetohydrostatic equilibrium. The code uses variable separation and hyperdiffusive and hyper-resistive terms (Stein & Nordlund 1998;Caunt & Korpi 2001;Vögler et al 2005;Shelyag et al 2008) to stabilize the solution against numerical instabilities and imperfections in the background model, caused by truncation errors. The main advantage of the implemented numerical technique is that it allows us to robustly simulate the macroscopic processes in a gravitationally stratified, magnetized plasma.…”
Section: Numerical Methods and Modelmentioning
confidence: 99%
“…SAC is the reconfigurable multi-dimensional ideal MHD solver which is designed to simulate the nonlinear interaction of an arbitrary perturbation with a gravitationally stratified background model, i.e., a model of the solar atmosphere, in magnetohydrostatic equilibrium. The code uses variable separation and hyperdiffusive and hyper-resistive terms (Stein & Nordlund 1998;Caunt & Korpi 2001;Vögler et al 2005;Shelyag et al 2008) to stabilize the solution against numerical instabilities and imperfections in the background model, caused by truncation errors. The main advantage of the implemented numerical technique is that it allows us to robustly simulate the macroscopic processes in a gravitationally stratified, magnetized plasma.…”
Section: Numerical Methods and Modelmentioning
confidence: 99%
“…In a similar manner to Stein and Nordlund (1998) and Caunt and Korpi (2001), in order to damp high-frequency numerical noise on subgrid scales, the physical diffusive terms in the equations of momentum and energy are replaced by artificial equivalents. In the induction equation, the magnetic-diffusion term is retained, with η being replaced by an artificial value.…”
Section: The Iac Mhd Codementioning
confidence: 99%
“…In particular, the method has been used to study the absorption of p-mode power by active regions (Braun, Duvall, and Labonte, 1988;Bogdan et al, 1993;Chen, Chou, and TON Team, 1996). In this procedure, the wave signal of the p modes is decomposed into inward-and outward-propagating modes in an annular region surrounding a sunspot.…”
Section: Moat Flow: Hankel Analysismentioning
confidence: 99%
“…These terms are implemented to stabilise the solution against numerical instabilities, and they are extensively described in e.g., Caunt & Korpi (2001), Vögler et al (2005), Shelyag et al (2008), and references therein. Equations (2)-(11) are solved using a fourth-order central difference scheme for the spatial derivatives and are advanced in time by implementing a fourth order Runge-Kutta numerical method.…”
Section: Simulation Modelmentioning
confidence: 99%
“…The 2D box is 180 Mm wide and 50 Mm deep, and has a resolution of 960 × 1000 grid points; the upper boundary of the domain is at the solar surface R = R . We employ the simplest type of "open" boundary conditions, assuming that all of the spatial derivatives of the variables, which are advanced in time, are set to be zero across the boundaries of the domain (Caunt & Korpi 2001;Shelyag et al 2008). The perturbation source is located in the upper-middle (500 km below the upper boundary) of the simulation box.…”
Section: Simulation Modelmentioning
confidence: 99%