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We present the implementation of a three-dimensional, second order accurate Godunov-type algorithm for magneto-hydrodynamic (MHD), in the adaptive-mesh-refinement (AMR) cosmological code {\tt CHARM}. The algorithm is based on the full…

天体物理仪器与方法 · 物理学 2015-05-27 Francesco Miniati , Daniel F. Martin

We present a new implementation of radiation hydrodynamics (RHD) in the adaptive mesh refinement (AMR) code RAMSES. The multi-group radiative transfer (RT) is performed on the AMR grid with a first-order Godunov method using the M1 closure…

宇宙学与河外天体物理 · 物理学 2015-06-15 Joakim Rosdahl , Jeremy Blaizot , Dominique Aubert , Timothy Stranex , Romain Teyssier

In this work, we introduce the novel application of the adaptive mesh refinement (AMR) technique in the global stability analysis of incompressible flows. The design of an accurate mesh for transitional flows is crucial. Indeed, an…

数值分析 · 数学 2026-02-17 Daniele Massaro , Valerio Lupi , Adam Peplinski , Philipp Schlatter

The advent of robust, reliable and accurate higher order Godunov schemes for many of the systems of equations of interest in computational astrophysics has made it important to understand how to solve them in multi-scale fashion. This is so…

天体物理学 · 物理学 2015-06-24 Dinshaw Balsara

There is great interest in numerical relativity simulations involving matter due to the likelihood that binary compact objects involving neutron stars will be detected by gravitational wave observatories in the coming years, as well as to…

广义相对论与量子宇宙学 · 物理学 2012-06-06 William E. East , Frans Pretorius , Branson C. Stephens

We have developed a new three-dimensional general relativistic magnetohydrodynamic (GRMHD) code, RAISHIN, using a conservative, high resolution shock-capturing scheme. The numerical fluxes are calculated using the Harten, Lax, & van Leer…

天体物理学 · 物理学 2007-05-23 Yosuke Mizuno , Ken-Ichi Nishikawa , Shinji Koide , Philip Hardee , Gerald J. Fishman

A new N-body and hydrodynamical code, called RAMSES, is presented. It has been designed to study structure formation in the universe with high spatial resolution. The code is based on Adaptive Mesh Refinement (AMR) technique, with a tree…

天体物理学 · 物理学 2014-10-13 Romain Teyssier

Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR…

计算物理 · 物理学 2022-03-02 Brandon Gusto , Tomasz Plewa

We compare two different codes for simulations of cosmological structure formation to investigate the sensitivity of hydrodynamical instabilities to numerics, in particular, the hydro solver and the application of adaptive mesh refinement…

宇宙学与河外天体物理 · 物理学 2014-11-27 W. Schmidt , J. Schulz , L. Iapichino , F. Vazza , A. S. Almgren

We describe a grid-based numerical method for 3D hydrodynamic cosmological simulations which is adaptive in space and time and combines the best features of higher order--accurate Godunov schemes for Eulerian hydrodynamics with adaptive…

天体物理学 · 物理学 2016-01-27 Michael L. Norman , Greg L. Bryan

A numerical method based on smoothed particle hydrodynamics with adaptive spatial resolution (SPH-ASR) was developed for simulating free surface flows. This method can reduce the computational demands while maintaining the numerical…

计算物理 · 物理学 2021-07-28 Xiufeng Yang , Song-Charng Kong , Moubin Liu , Qingquan Liu

In this paper we study the problem of divergence-free numerical MHD and show that the work done so far still has four key unresolved issues. We resolve those issues in this paper. The problem of reconstructing MHD flow variables with…

天体物理学 · 物理学 2009-11-10 Dinshaw Balsara

We present \texttt{SACRA-2D}, a new MPI and OpenMP parallelized, fully relativistic hydrodynamics (GRHD) code in dynamical spacetime under axial symmetry with the cartoon method using the finite-volume shock-capturing schemes for…

高能天体物理现象 · 物理学 2025-02-06 Alan Tsz-Lok Lam , Masaru Shibata

We construct a relativistic resistive magneto-hydrodynamic (RRMHD) numerical simulation code for high-energy heavy-ion collisions. We split the system of differential equations into two parts, a non-stiff and a stiff part. For the non-stiff…

核理论 · 物理学 2023-04-05 Kouki Nakamura , Takahiro Miyoshi , Chiho Nonaka , Hiroyuki R. Takahashi

I provide a pedagogic review of adaptive mesh refinement (AMR) radiation hydrodynamics (RHD) methods and codes used in simulations of star formation, at a level suitable for researchers who are not computational experts. I begin with a…

天体物理仪器与方法 · 物理学 2015-05-19 Mark R. Krumholz

The relativistic magnetohydrodynamics (RMHD) set of equations has recently seen increased use in astrophysical computations. Even so, RMHD codes remain fragile. The reconstruction can sometimes yield superluminal velocities in certain parts…

高能天体物理现象 · 物理学 2016-03-23 Dinshaw S. Balsara , Jinho Kim

We describe a powerful methodology for numerical solution of 3-D self-gravitational hydrodynamics problems with extremely high resolution. Our method utilizes the technique of local adaptive mesh refinement (AMR), employing multiple grids…

天体物理学 · 物理学 2016-01-27 Richard I. Klein , Robert T. Fisher , Christopher F. McKee , J. Kelly Truelove

We study the Richtmyer--Meshkov (RM) instability of a relativistic perfect fluid by means of high order numerical simulations with adaptive mesh refinement (AMR). The numerical scheme adopts a finite volume Weighted Essentially…

流体动力学 · 物理学 2014-11-04 Olindo Zanotti , Michael Dumbser

We have developed a simulation code with the techniques which enhance both spatial and time resolution of the PM method for which the spatial resolution is restricted by the spacing of structured mesh. The adaptive mesh refinement (AMR)…

天体物理学 · 物理学 2009-11-06 Hideki Yahagi , Yuzuru Yoshii

The design and implementation of a new framework for adaptive mesh refinement (AMR) calculations is described. It is intended primarily for applications in astrophysical fluid dynamics, but its flexible and modular design enables its use…

天体物理仪器与方法 · 物理学 2020-07-08 James M. Stone , Kengo Tomida , Christopher J. White , Kyle G. Felker