<tt>Gmunu</tt>: paralleled, grid-adaptive, general-relativistic magnetohydrodynamics in curvilinear geometries in dynamical space–times

A new general relativistic magnetohydrodynamics code for dynamical spacetimes

We present a new numerical code that solves the general relativistic magneto-hydrodynamical (GRMHD) equations coupled to the Einstein equations for the evolution of a dynamical spacetime within a conformally-flat approximation. This code has been developed with the main objective of studying astrophysical scenarios in which both, high magnetic fields and strong gravitational fields appear, such...

General-relativistic Mhd for the Numerical Construction of Dynamical Spacetimes

We assemble the equations of general relativistic magnetohydrodynamics (MHD) in 3+1 form. These consist of the complete coupled set of Maxwell equations for the electromagnetic field, Einstein’s equations for the gravitational field, and the equations of relativistic MHD for a perfectly conducting ideal gas. The adopted form of the equations is suitable for evolving numerically a relativistic M...

General relativistic hydrodynamics and magnetohydrodynamics: hyperbolic systems in relativistic astrophysics

A Numerical Method for General Relativistic Magnetohydrodynamics

This paper describes the development and testing of a general relativistic magnetohydrodynamic (GRMHD) code to study ideal MHD in the fixed background of a Kerr black hole. The code is a direct extension of the hydrodynamic code of Hawley, Smarr, and Wilson, and uses Evans and Hawley constrained transport (CT) to evolve the magnetic fields. Two categories of test cases were undertaken. A one di...

Curvilinear Grid Filtering by Adaptive Evaluation

Data from computational fluid dynamics (CFD) are frequently computed on curvilinear grids. In contrast to cartesian or uniform grids, the cell size in a curvilinear grid can vary significantly, which in turn complicates filter operations tremendously. Some of these filter operations may for example re-map the value range of the data values into another range. In this paper, we present adaptive ...