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compressible: add the ability for a problem-dependent external source (…
…#289) this also adds a "heating" test problem.
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"""A test of the energy sources. This uses a uniform domain and | ||
slowly adds heat to the center over time.""" | ||
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import numpy as np | ||
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from pyro.util import msg | ||
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DEFAULT_INPUTS = "inputs.heating" | ||
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PROBLEM_PARAMS = {"heating.rho_ambient": 1.0, # ambient density | ||
"heating.p_ambient": 10.0, # ambient pressure | ||
"heating.r_src": 0.1, # physical size of the heating src | ||
"heating.e_rate": 0.1} # energy generation rate (energy / mass / time) | ||
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def init_data(my_data, rp): | ||
""" initialize the heating problem """ | ||
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if rp.get_param("driver.verbose"): | ||
msg.bold("initializing the heating problem...") | ||
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# get the density, momenta, and energy as separate variables | ||
dens = my_data.get_var("density") | ||
xmom = my_data.get_var("x-momentum") | ||
ymom = my_data.get_var("y-momentum") | ||
ener = my_data.get_var("energy") | ||
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gamma = rp.get_param("eos.gamma") | ||
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# initialize the components, remember, that ener here is rho*eint | ||
# + 0.5*rho*v**2, where eint is the specific internal energy | ||
# (erg/g) | ||
dens[:, :] = rp.get_param("heating.rho_ambient") | ||
xmom[:, :] = 0.0 | ||
ymom[:, :] = 0.0 | ||
ener[:, :] = rp.get_param("heating.p_ambient") / (gamma - 1.0) | ||
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def source_terms(myg, U, ivars, rp): | ||
"""source terms to be added to the evolution""" | ||
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S = myg.scratch_array(nvar=ivars.nvar) | ||
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xctr = 0.5 * (myg.xmin + myg.xmax) | ||
yctr = 0.5 * (myg.ymin + myg.ymax) | ||
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dist = np.sqrt((myg.x2d - xctr)**2 + | ||
(myg.y2d - yctr)**2) | ||
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e_rate = rp.get_param("heating.e_rate") | ||
r_src = rp.get_param("heating.r_src") | ||
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S[:, :, ivars.iener] = U[:, :, ivars.idens] * e_rate * np.exp(-(dist / r_src)**2) | ||
return S | ||
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def finalize(): | ||
""" print out any information to the user at the end of the run """ | ||
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print(""" | ||
The script analysis/sedov_compare.py can be used to analyze these | ||
results. That will perform an average at constant radius and | ||
compare the radial profiles to the exact solution. Sample exact | ||
data is provided as analysis/cylindrical-sedov.out | ||
""") |
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[driver] | ||
max_steps = 5000 | ||
tmax = 1.0 | ||
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[compressible] | ||
limiter = 2 | ||
cvisc = 0.1 | ||
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[io] | ||
basename = heating_ | ||
dt_out = 0.1 | ||
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[eos] | ||
gamma = 1.4 | ||
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[mesh] | ||
nx = 64 | ||
ny = 64 | ||
xmax = 1.0 | ||
ymax = 1.0 | ||
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xlboundary = outflow | ||
xrboundary = outflow | ||
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ylboundary = outflow | ||
yrboundary = outflow | ||
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[heating] | ||
rho_ambient = 1.0 | ||
p_ambient = 10.0 | ||
r_src = 0.05 | ||
e_rate = 0.1 | ||
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[vis] | ||
dovis = 1 |
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# simple inputs files for the four-corner problem. | ||
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[driver] | ||
max_steps = 10000 | ||
tmax = 10.0 | ||
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[io] | ||
basename = plume_ | ||
n_out = 100 | ||
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[mesh] | ||
nx = 128 | ||
ny = 256 | ||
xmax = 4.0 | ||
ymax = 8.0 | ||
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xlboundary = outflow | ||
xrboundary = outflow | ||
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ylboundary = hse | ||
yrboundary = hse | ||
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[plume] | ||
scale_height = 3.0 | ||
dens_base = 1000.0 | ||
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x_pert = 2.0 | ||
y_pert = 2.0 | ||
r_pert = 0.25 | ||
e_rate = 0.5 | ||
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[compressible] | ||
grav = -2.0 | ||
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limiter = 2 |
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"""A heat source at a point creates a plume that buoynantly rises in | ||
an adiabatically stratified atmosphere.""" | ||
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import numpy as np | ||
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from pyro.util import msg | ||
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DEFAULT_INPUTS = "inputs.plume" | ||
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PROBLEM_PARAMS = {"plume.dens_base": 10.0, # density at the base of the atmosphere | ||
"plume.scale_height": 4.0, # scale height of the isothermal atmosphere | ||
"plume.x_pert": 2.0, | ||
"plume.y_pert": 2.0, | ||
"plume.r_pert": 0.25, | ||
"plume.e_rate": 0.1, | ||
"plume.dens_cutoff": 0.01} | ||
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def init_data(my_data, rp): | ||
""" initialize the bubble problem """ | ||
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if rp.get_param("driver.verbose"): | ||
msg.bold("initializing the bubble problem...") | ||
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# get the density, momenta, and energy as separate variables | ||
dens = my_data.get_var("density") | ||
xmom = my_data.get_var("x-momentum") | ||
ymom = my_data.get_var("y-momentum") | ||
ener = my_data.get_var("energy") | ||
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gamma = rp.get_param("eos.gamma") | ||
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grav = rp.get_param("compressible.grav") | ||
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scale_height = rp.get_param("plume.scale_height") | ||
dens_base = rp.get_param("plume.dens_base") | ||
dens_cutoff = rp.get_param("plume.dens_cutoff") | ||
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# initialize the components, remember, that ener here is | ||
# rho*eint + 0.5*rho*v**2, where eint is the specific | ||
# internal energy (erg/g) | ||
xmom[:, :] = 0.0 | ||
ymom[:, :] = 0.0 | ||
dens[:, :] = dens_cutoff | ||
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# set the density to be stratified in the y-direction | ||
myg = my_data.grid | ||
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p = myg.scratch_array() | ||
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pres_base = scale_height*dens_base*abs(grav) | ||
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for j in range(myg.jlo, myg.jhi+1): | ||
profile = 1.0 - (gamma-1.0)/gamma * myg.y[j]/scale_height | ||
if profile > 0.0: | ||
dens[:, j] = max(dens_base*(profile)**(1.0/(gamma-1.0)), | ||
dens_cutoff) | ||
else: | ||
dens[:, j] = dens_cutoff | ||
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if j == myg.jlo: | ||
p[:, j] = pres_base | ||
else: | ||
p[:, j] = p[:, j-1] + 0.5*myg.dy*(dens[:, j] + dens[:, j-1])*grav | ||
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# set the energy (P = cs2*dens) | ||
ener[:, :] = p[:, :]/(gamma - 1.0) + \ | ||
0.5*(xmom[:, :]**2 + ymom[:, :]**2)/dens[:, :] | ||
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def source_terms(myg, U, ivars, rp): | ||
"""source terms to be added to the evolution""" | ||
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S = myg.scratch_array(nvar=ivars.nvar) | ||
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x_pert = rp.get_param("plume.x_pert") | ||
y_pert = rp.get_param("plume.y_pert") | ||
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dist = np.sqrt((myg.x2d - x_pert)**2 + | ||
(myg.y2d - y_pert)**2) | ||
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e_rate = rp.get_param("plume.e_rate") | ||
r_pert = rp.get_param("plume.r_pert") | ||
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S[:, :, ivars.iener] = U[:, :, ivars.idens] * e_rate * np.exp(-(dist / r_pert)**2) | ||
return S | ||
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def finalize(): | ||
""" print out any information to the user at the end of the run """ |
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