compressible package¶

The pyro compressible hydrodynamics solver. This implements the second-order (piecewise-linear), unsplit method of Colella 1990.

Subpackages¶

compressible.problems package

Submodules¶

compressible.BC module¶

compressible-specific boundary conditions. Here, in particular, we implement an HSE BC in the vertical direction.

Note: the pyro BC routines operate on a single variable at a time, so some work will necessarily be repeated.

Also note: we may come in here with the aux_data (source terms), so we’ll do a special case for them

compressible.BC.inflow_post_bc(var, g)[source]¶

compressible.BC.inflow_pre_bc(var, g)[source]¶

compressible.BC.user(bc_name, bc_edge, variable, ccdata)[source]¶

A hydrostatic boundary. This integrates the equation of HSE into the ghost cells to get the pressure and density under the assumption that the specific internal energy is constant.

Upon exit, the ghost cells for the input variable will be set

Parameters:

bc_name : {‘hse’}

The descriptive name for the boundary condition – this allows for pyro to have multiple types of user-supplied boundary conditions. For this module, it needs to be ‘hse’.

bc_edge : {‘ylb’, ‘yrb’}

The boundary to update: ylb = lower y boundary; yrb = upper y boundary.

variable : {‘density’, ‘x-momentum’, ‘y-momentum’, ‘energy’}

The variable whose ghost cells we are filling

ccdata : CellCenterData2d object

The data object

compressible.derives module¶

compressible.derives.derive_primitives(myd, varnames)[source]¶: derive desired primitive variables from conserved state

compressible.eos module¶

This is a gamma-law equation of state: p = rho e (gamma - 1), where gamma is the constant ratio of specific heats.

compressible.eos.dens(gamma, pres, eint)[source]¶

Given the pressure and the specific internal energy, return the density

Parameters:

gamma : float

The ratio of specific heats

pres : float

The pressure

eint : float

The specific internal energy

Returns:

out : float

The density

compressible.eos.pres(gamma, dens, eint)[source]¶

Given the density and the specific internal energy, return the pressure

Parameters:

gamma : float

The ratio of specific heats

dens : float

The density

eint : float

The specific internal energy

Returns:

out : float

The pressure

compressible.eos.rhoe(gamma, pres)[source]¶

Given the pressure, return (rho * e)

Parameters:

gamma : float

The ratio of specific heats

pres : float

The pressure

Returns:

out : float

The internal energy density, rho e

compressible.simulation module¶

class compressible.simulation.Simulation(solver_name, problem_name, rp, timers=None, data_class=<class 'mesh.patch.CellCenterData2d'>)[source]¶

Bases: simulation_null.NullSimulation

The main simulation class for the corner transport upwind compressible hydrodynamics solver

dovis()[source]¶: Do runtime visualization.

evolve()[source]¶: Evolve the equations of compressible hydrodynamics through a timestep dt.

initialize(extra_vars=None, ng=4)[source]¶: Initialize the grid and variables for compressible flow and set the initial conditions for the chosen problem.

method_compute_timestep()[source]¶

The timestep function computes the advective timestep (CFL) constraint. The CFL constraint says that information cannot propagate further than one zone per timestep.

We use the driver.cfl parameter to control what fraction of the CFL step we actually take.

write_extras(f)[source]¶: Output simulation-specific data to the h5py file f

class compressible.simulation.Variables(myd)[source]¶

Bases: object

a container class for easy access to the different compressible variable by an integer key

compressible.simulation.cons_to_prim(U, gamma, ivars, myg)[source]¶: convert an input vector of conserved variables to primitive variables

compressible.simulation.prim_to_cons(q, gamma, ivars, myg)[source]¶: convert an input vector of primitive variables to conserved variables

compressible.unsplit_fluxes module¶

Implementation of the Colella 2nd order unsplit Godunov scheme. This is a 2-dimensional implementation only. We assume that the grid is uniform, but it is relatively straightforward to relax this assumption.

There are several different options for this solver (they are all discussed in the Colella paper).

limiter: 0 = no limiting; 1 = 2nd order MC limiter; 2 = 4th order MC limiter
riemann: HLLC or CGF (for Colella, Glaz, and Freguson solver)
use_flattening: set to 1 to use the multidimensional flattening at shocks
delta, z0, z1: flattening parameters (we use Colella 1990 defaults)

The grid indices look like:

j+3/2--+---------+---------+---------+
       |         |         |         |
  j+1 _|         |         |         |
       |         |         |         |
       |         |         |         |
j+1/2--+---------XXXXXXXXXXX---------+
       |         X         X         |
    j _|         X         X         |
       |         X         X         |
       |         X         X         |
j-1/2--+---------XXXXXXXXXXX---------+
       |         |         |         |
  j-1 _|         |         |         |
       |         |         |         |
       |         |         |         |
j-3/2--+---------+---------+---------+
       |    |    |    |    |    |    |
           i-1        i        i+1
     i-3/2     i-1/2     i+1/2     i+3/2

We wish to solve

$U_t + F^x_x + F^y_y = H$

we want U_{i+1/2}^{n+1/2} – the interface values that are input to the Riemann problem through the faces for each zone.

Taylor expanding yields:

 n+1/2                     dU           dU
U          = U   + 0.5 dx  --  + 0.5 dt --
 i+1/2,j,L    i,j          dx           dt


                           dU             dF^x   dF^y
           = U   + 0.5 dx  --  - 0.5 dt ( ---- + ---- - H )
              i,j          dx              dx     dy


                            dU      dF^x            dF^y
           = U   + 0.5 ( dx -- - dt ---- ) - 0.5 dt ---- + 0.5 dt H
              i,j           dx       dx              dy


                                dt       dU           dF^y
           = U   + 0.5 dx ( 1 - -- A^x ) --  - 0.5 dt ---- + 0.5 dt H
              i,j               dx       dx            dy


                              dt       _            dF^y
           = U   + 0.5  ( 1 - -- A^x ) DU  - 0.5 dt ---- + 0.5 dt H
              i,j             dx                     dy

                   +----------+-----------+  +----+----+   +---+---+
                              |                   |            |

                  this is the monotonized   this is the   source term
                  central difference term   transverse
                                            flux term

There are two components, the central difference in the normal to the interface, and the transverse flux difference. This is done for the left and right sides of all 4 interfaces in a zone, which are then used as input to the Riemann problem, yielding the 1/2 time interface values:

 n+1/2
U
 i+1/2,j

Then, the zone average values are updated in the usual finite-volume way:

 n+1    n     dt    x  n+1/2       x  n+1/2
U    = U    + -- { F (U       ) - F (U       ) }
 i,j    i,j   dx       i-1/2,j        i+1/2,j


              dt    y  n+1/2       y  n+1/2
            + -- { F (U       ) - F (U       ) }
              dy       i,j-1/2        i,j+1/2

Updating U_{i,j}:

We want to find the state to the left and right (or top and bottom) of each interface, ex. U_{i+1/2,j,[lr]}^{n+1/2}, and use them to solve a Riemann problem across each of the four interfaces.
U_{i+1/2,j,[lr]}^{n+1/2} is comprised of two parts, the computation of the monotonized central differences in the normal direction (eqs. 2.8, 2.10) and the computation of the transverse derivatives, which requires the solution of a Riemann problem in the transverse direction (eqs. 2.9, 2.14).
- the monotonized central difference part is computed using the primitive variables.
- We compute the central difference part in both directions before doing the transverse flux differencing, since for the high-order transverse flux implementation, we use these as the input to the transverse Riemann problem.

compressible.unsplit_fluxes.unsplit_fluxes(my_data, my_aux, rp, ivars, solid, tc, dt)[source]¶

unsplitFluxes returns the fluxes through the x and y interfaces by doing an unsplit reconstruction of the interface values and then solving the Riemann problem through all the interfaces at once

currently we assume a gamma-law EOS

The runtime parameter grav is assumed to be the gravitational acceleration in the y-direction

Parameters:

my_data : CellCenterData2d object

The data object containing the grid and advective scalar that we are advecting.

rp : RuntimeParameters object

The runtime parameters for the simulation

vars : Variables object

The Variables object that tells us which indices refer to which variables

tc : TimerCollection object

The timers we are using to profile

dt : float

The timestep we are advancing through.

Returns:

out : ndarray, ndarray

The fluxes on the x- and y-interfaces