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Title: Relativistic Flows Using Spatial And Temporal Adaptive Structured Mesh Refinement. I. Hydrodynamics

Abstract

Astrophysical relativistic flow problems require high resolution three-dimensional numerical simulations. In this paper, we describe a new parallel three-dimensional code for simulations of special relativistic hydrodynamics (SRHD) using both spatially and temporally structured adaptive mesh refinement (AMR). We used method of lines to discrete SRHD equations spatially and used a total variation diminishing (TVD) Runge-Kutta scheme for time integration. For spatial reconstruction, we have implemented piecewise linear method (PLM), piecewise parabolic method (PPM), third order convex essentially non-oscillatory (CENO) and third and fifth order weighted essentially non-oscillatory (WENO) schemes. Flux is computed using either direct flux reconstruction or approximate Riemann solvers including HLL, modified Marquina flux, local Lax-Friedrichs flux formulas and HLLC. The AMR part of the code is built on top of the cosmological Eulerian AMR code enzo, which uses the Berger-Colella AMR algorithm and is parallel with dynamical load balancing using the widely available Message Passing Interface library. We discuss the coupling of the AMR framework with the relativistic solvers and show its performance on eleven test problems.

Authors:
; ; ;
Publication Date:
Research Org.:
Stanford Linear Accelerator Center (SLAC)
Sponsoring Org.:
USDOE
OSTI Identifier:
901845
Report Number(s):
SLAC-PUB-12433
astro-ph/0703742; TRN: US200717%%5
DOE Contract Number:  
AC02-76SF00515
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; HYDRODYNAMICS; PERFORMANCE; RESOLUTION; RELATIVISTIC RANGE; CALCULATION METHODS; SPACE DEPENDENCE; TIME DEPENDENCE; ASTROPHYSICS; Astrophysics,ASTRO

Citation Formats

Wang, Peng, Abel, Tom, Zhang, Weiqun, and /KIPAC, Menlo Park. Relativistic Flows Using Spatial And Temporal Adaptive Structured Mesh Refinement. I. Hydrodynamics. United States: N. p., 2007. Web. doi:10.2172/901845.
Wang, Peng, Abel, Tom, Zhang, Weiqun, & /KIPAC, Menlo Park. Relativistic Flows Using Spatial And Temporal Adaptive Structured Mesh Refinement. I. Hydrodynamics. United States. doi:10.2172/901845.
Wang, Peng, Abel, Tom, Zhang, Weiqun, and /KIPAC, Menlo Park. Mon . "Relativistic Flows Using Spatial And Temporal Adaptive Structured Mesh Refinement. I. Hydrodynamics". United States. doi:10.2172/901845. https://www.osti.gov/servlets/purl/901845.
@article{osti_901845,
title = {Relativistic Flows Using Spatial And Temporal Adaptive Structured Mesh Refinement. I. Hydrodynamics},
author = {Wang, Peng and Abel, Tom and Zhang, Weiqun and /KIPAC, Menlo Park},
abstractNote = {Astrophysical relativistic flow problems require high resolution three-dimensional numerical simulations. In this paper, we describe a new parallel three-dimensional code for simulations of special relativistic hydrodynamics (SRHD) using both spatially and temporally structured adaptive mesh refinement (AMR). We used method of lines to discrete SRHD equations spatially and used a total variation diminishing (TVD) Runge-Kutta scheme for time integration. For spatial reconstruction, we have implemented piecewise linear method (PLM), piecewise parabolic method (PPM), third order convex essentially non-oscillatory (CENO) and third and fifth order weighted essentially non-oscillatory (WENO) schemes. Flux is computed using either direct flux reconstruction or approximate Riemann solvers including HLL, modified Marquina flux, local Lax-Friedrichs flux formulas and HLLC. The AMR part of the code is built on top of the cosmological Eulerian AMR code enzo, which uses the Berger-Colella AMR algorithm and is parallel with dynamical load balancing using the widely available Message Passing Interface library. We discuss the coupling of the AMR framework with the relativistic solvers and show its performance on eleven test problems.},
doi = {10.2172/901845},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Apr 02 00:00:00 EDT 2007},
month = {Mon Apr 02 00:00:00 EDT 2007}
}

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