1-dimensional variable-velocity advection

One-dimensional advection with variable velocity

Solve the conservative variable-coefficient advection equation:

\[q_t + (u(x)q)_x = 0.\]

Here q is the density of some conserved quantity and u(x) is the velocity. The velocity field used is

\[u(x) = 2 + sin(2\pi x).\]

The boundary conditions are periodic. The initial data get stretched and compressed as they move through the fast and slow parts of the velocity field.

Output:

../../_images/pyclaw_examples_advection_1d_variable__plots_variable_coefficient_advection_frame0000fig1.png ../../_images/pyclaw_examples_advection_1d_variable__plots_variable_coefficient_advection_frame0004fig1.png ../../_images/pyclaw_examples_advection_1d_variable__plots_variable_coefficient_advection_frame0008fig1.png

Source:

#!/usr/bin/env python
# encoding: utf-8
r"""
One-dimensional advection with variable velocity
================================================

Solve the conservative variable-coefficient advection equation:

.. math:: q_t + (u(x)q)_x = 0.

Here q is the density of some conserved quantity and u(x) is the velocity.
The velocity field used is

.. math:: u(x) = 2 + sin(2\pi x).

The boundary conditions are periodic.
The initial data get stretched and compressed as they move through the
fast and slow parts of the velocity field.
"""


from __future__ import absolute_import
import numpy as np

def qinit(state):

    # Initial Data parameters
    ic = 3
    beta = 100.
    gamma = 0.
    x0 = 0.3
    x1 = 0.7
    x2 = 0.9

    x =state.grid.x.centers
    
    # Gaussian
    qg = np.exp(-beta * (x-x0)**2) * np.cos(gamma * (x - x0))
    # Step Function
    qs = (x > x1) * 1.0 - (x > x2) * 1.0
    
    if   ic == 1: state.q[0,:] = qg
    elif ic == 2: state.q[0,:] = qs
    elif ic == 3: state.q[0,:] = qg + qs


def auxinit(state):
    # Initilize petsc Structures for aux
    xc=state.grid.x.centers
    state.aux[0,:] = np.sin(2.*np.pi*xc)+2
    

def setup(use_petsc=False,solver_type='classic',kernel_language='Python',outdir='./_output'):
    from clawpack import riemann

    if use_petsc:
        import clawpack.petclaw as pyclaw
    else:
        from clawpack import pyclaw

    if solver_type=='classic':
        if kernel_language == 'Fortran':
            solver = pyclaw.ClawSolver1D(riemann.vc_advection_1D)
        elif kernel_language=='Python': 
            solver = pyclaw.ClawSolver1D(riemann.vc_advection_1D_py.vc_advection_1D)
    elif solver_type=='sharpclaw':
        if kernel_language == 'Fortran':
            solver = pyclaw.SharpClawSolver1D(riemann.vc_advection_1D)
        elif kernel_language=='Python': 
            solver = pyclaw.SharpClawSolver1D(riemann.vc_advection_1D_py.vc_advection_1D)
        solver.weno_order=weno_order
    else: raise Exception('Unrecognized value of solver_type.')

    solver.kernel_language = kernel_language

    solver.limiters = pyclaw.limiters.tvd.MC
    solver.bc_lower[0] = 2
    solver.bc_upper[0] = 2
    solver.aux_bc_lower[0] = 2
    solver.aux_bc_upper[0] = 2

    xlower=0.0; xupper=1.0; mx=100
    x    = pyclaw.Dimension(xlower,xupper,mx,name='x')
    domain = pyclaw.Domain(x)
    num_aux=1
    num_eqn = 1
    state = pyclaw.State(domain,num_eqn,num_aux)

    qinit(state)
    auxinit(state)

    claw = pyclaw.Controller()
    claw.outdir = outdir
    claw.solution = pyclaw.Solution(state,domain)
    claw.solver = solver

    claw.tfinal = 1.0
    claw.setplot = setplot
    claw.keep_copy = True
    
    return claw

#--------------------------
def setplot(plotdata):
#--------------------------
    """ 
    Specify what is to be plotted at each frame.
    Input:  plotdata, an instance of visclaw.data.ClawPlotData.
    Output: a modified version of plotdata.
    """ 
    plotdata.clearfigures()  # clear any old figures,axes,items data

    # Figure for q[0]
    plotfigure = plotdata.new_plotfigure(name='q', figno=1)

    # Set up for axes in this figure:
    plotaxes = plotfigure.new_plotaxes()
    plotaxes.ylimits = [-.1,1.1]
    plotaxes.title = 'q'

    # Set up for item on these axes:
    plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
    plotitem.plot_var = 0
    plotitem.plotstyle = '-o'
    plotitem.color = 'b'
    plotitem.kwargs = {'linewidth':2,'markersize':5}
    
    return plotdata

 
if __name__=="__main__":
    from clawpack.pyclaw.util import run_app_from_main
    output = run_app_from_main(setup,setplot)