Journal of Computational Physics
MPDATA: a finite-difference solver for geophysical flows
Journal of Computational Physics
MPDATA: An edge-based unstructured-grid formulation
Journal of Computational Physics
Building resolving large-eddy simulations and comparison with wind tunnel experiments
Journal of Computational Physics
Iterated upwind schemes for gas dynamics
Journal of Computational Physics
On numerical realizability of thermal convection
Journal of Computational Physics
Pores resolving simulation of Darcy flows
Journal of Computational Physics
An edge-based unstructured mesh discretisation in geospherical framework
Journal of Computational Physics
Modelling atmospheric flows with adaptive moving meshes
Journal of Computational Physics
Journal of Computational Physics
Hi-index | 31.45 |
EULAG is an established high-performance computational model for simulating fluid flows across a wide range of scales and physical scenarios [Prusa et al., Comput. Fluids 37 (2008) 1193]. Historically driven by interests in simulating weather and climate processes, the numerics of EULAG are unique, owing to a synergistic blend of non-oscillatory forward-in-time MPDATA methods, robust elliptic solver, and generalized coordinate formulation enabling grid adaptivity. In this paper the numerical apparatus of an ideal magnetohydrodynamic (MHD) extension of the EULAG model is discussed, the robust workings of which have been recently revealed in global large-eddy simulations of solar magneto-convection producing solar-like magnetic cycles and dynamo action [Ghizaru et al., ApJL 715 (2010) L133; Racine et al., ApJ 735 (2011) 46]. Here, a specialized nonoscillatory forward-in-time scheme for integrating ideal anelastic MHD equations is presented in detail, and illustrated with an abstract example of magnetized three-dimensional flow in time-dependent geometry for a weak, moderate and strong magnetic field. An analysis of the model performance reveals that multiple solutions of elliptic problems do not have to imply proportionally larger computational expense.