Simple one-dimensional examples of various hydrodynamics techniques
This is a collection of simple python codes that demonstrate some basic techniques used in hydrodynamics codes. All the codes are standalone -- there are no interdependencies.
These codes go together with the lecture notes at:
http://bender.astro.sunysb.edu/hydro_by_example/CompHydroTutorial.pdf
and with the pyro2 code:
https://github.com/zingale/pyro2
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advection/
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advection.py
: a 1-d second-order linear advection solver with a wide range of limiters. -
fdadvect_implicit.py
: a 1-d first-order implicit finite-difference linear advection solver using periodic boundary conditions. -
fdadvect.py
: a 1-d first-order explicit finite-difference linear advection solver using upwinded differencing.
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basic-numerics
orbit-converge.py
(andorbit.py
): a demonstration of the convergence of different ODE integration methods for the problem of Earth orbiting around the Sun.
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burgers/
burgers.py
: a 1-d second-order solver for the inviscid Burgers’ equation, with initial conditions corresponding to a shock and a rarefaction.
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compressible/
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euler.ipynb
: aSymPy
IPython
notebook that derives the eigenvalues and eigenvectors for the Euler equations. -
riemann-phase.py
: a simple script that plots the Hugoniot curves for a compressible Riemann problem (assuming a gamma-law gas)
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diffusion/
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diffusion-explicit.py
: solve the constant-diffusivity diffusion equation explicitly. The method is first-order accurate in time, but second- order in space. A Gaussian profile is diffused--the analytic solution is also a Gaussian. -
diffusion-implicit.py
: solve the constant-diffusivity diffusion equation implicitly. Crank-Nicolson time-discretization is used, resulting in a second-order method. A Gaussian profile is diffused.
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elliptic/
poisson_fft.py
: an FFT solver for a 2-d Poisson problem with periodic boundaries.
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finite-volume/
conservative-interpolation.ipynb
: an IPython notebook that illustrates how to derive high-order conservative interpolants for finite-volume data.
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multigrid/
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mg_converge.py
: a convergence test of the multigrid solver. A Poisson problem is solved at various resolutions and compared to the exact solution. This demonstrates second-order accuracy. -
mg_test.py
: a simple driver for the multigrid solver. This sets up and solves a Poisson problem and plots the behavior of the solution as a function of V-cycle number. -
multigrid.py
: a multigrid class for cell-centered data. This implements pure V-cycles. A square domain with 2 N zones (N a positive integer) is required. -
patch1d.py
: a class for 1-d cell-centered data that lives on a grid. This manages the data, handles boundary conditions, and provides routines for prolongation and restriction to other grids.
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multiphysics/
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burgersvisc.py
: solve the viscous Burgers equation. The advective terms are treated explicitly with a second-order accurate method. The diffusive term is solved using an implicit Crank-Nicolson discretiza- tion. The overall coupling is second-order accurate. -
diffusion-reaction.py
: solve a diffusion-reaction equation that propagates a diffusive reacting front (flame). A simple reaction term is modeled. The diffusion is solved using a second-order Crank-Nicolson discretization. The reactions are evolved using the VODE ODE solver (via SciPy). The two processes are coupled together using Strang-splitting to be second-order accurate in time.
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