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# Hedge - the Hybrid'n'Easy DG Environment
# Copyright (C) 2008 Andreas Kloeckner
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from __future__ import division
from __future__ import absolute_import
from __future__ import print_function
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import numpy
import numpy.linalg as la
# modifies isentropic vortex solution so that rho->Arho, P->A^gamma rho^gamma
# this will be analytic solution if appropriate source terms are added
# to the RHS. coded for vel_x=1, vel_y=0
class Vortex:
def __init__(self, beta, gamma, center, velocity, densityA):
self.beta = beta
self.gamma = gamma
self.center = numpy.asarray(center)
self.velocity = numpy.asarray(velocity)
self.densityA = densityA
def __call__(self, t, x_vec):
vortex_loc = self.center + t*self.velocity
# coordinates relative to vortex center
x_rel = x_vec[0] - vortex_loc[0]
y_rel = x_vec[1] - vortex_loc[1]
# Y.C. Zhou, G.W. Wei / Journal of Computational Physics 189 (2003) 159
# also JSH/TW Nodal DG Methods, p. 209
from math import pi
r = numpy.sqrt(x_rel**2+y_rel**2)
expterm = self.beta*numpy.exp(1-r**2)
u = self.velocity[0] - expterm*y_rel/(2*pi)
v = self.velocity[1] + expterm*x_rel/(2*pi)
rho = self.densityA*(1-(self.gamma-1)/(16*self.gamma*pi**2)*expterm**2)**(1/(self.gamma-1))
p = rho**self.gamma
e = p/(self.gamma-1) + rho/2*(u**2+v**2)
from hedge.tools import join_fields
return join_fields(rho, e, rho*u, rho*v)
def volume_interpolant(self, t, discr):
return discr.convert_volume(
self(t, discr.nodes.T
.astype(discr.default_scalar_type)),
kind=discr.compute_kind)
def boundary_interpolant(self, t, discr, tag):
return discr.convert_boundary(
self(t, discr.get_boundary(tag).nodes.T
.astype(discr.default_scalar_type)),
tag=tag, kind=discr.compute_kind)
class SourceTerms:
def __init__(self, beta, gamma, center, velocity, densityA):
self.beta = beta
self.gamma = gamma
self.center = numpy.asarray(center)
self.velocity = numpy.asarray(velocity)
self.densityA = densityA
def __call__(self,t,x_vec,q):
vortex_loc = self.center + t*self.velocity
# coordinates relative to vortex center
x_rel = x_vec[0] - vortex_loc[0]
y_rel = x_vec[1] - vortex_loc[1]
# sources written in terms of A=1.0 solution
# (standard isentropic vortex)
from math import pi
r = numpy.sqrt(x_rel**2+y_rel**2)
expterm = self.beta*numpy.exp(1-r**2)
u = self.velocity[0] - expterm*y_rel/(2*pi)
v = self.velocity[1] + expterm*x_rel/(2*pi)
rho = (1-(self.gamma-1)/(16*self.gamma*pi**2)*expterm**2)**(1/(self.gamma-1))
p = rho**self.gamma
#computed necessary derivatives
expterm_t = 2*expterm*x_rel
expterm_x = -2*expterm*x_rel
expterm_y = -2*expterm*y_rel
u_x = -expterm*y_rel/(2*pi)*(-2*x_rel)
v_y = expterm*x_rel/(2*pi)*(-2*y_rel)
#derivatives for rho (A=1)
facG=self.gamma-1
rho_t = (1/facG)*(1-(facG)/(16*self.gamma*pi**2)*expterm**2)**(1/facG-1)* \
(-facG/(16*self.gamma*pi**2)*2*expterm*expterm_t)
rho_x = (1/facG)*(1-(facG)/(16*self.gamma*pi**2)*expterm**2)**(1/facG-1)* \
(-facG/(16*self.gamma*pi**2)*2*expterm*expterm_x)
rho_y = (1/facG)*(1-(facG)/(16*self.gamma*pi**2)*expterm**2)**(1/facG-1)* \
(-facG/(16*self.gamma*pi**2)*2*expterm*expterm_y)
#derivatives for rho (A=1) to the power of gamma
rho_gamma_t = self.gamma*rho**(self.gamma-1)*rho_t
rho_gamma_x = self.gamma*rho**(self.gamma-1)*rho_x
rho_gamma_y = self.gamma*rho**(self.gamma-1)*rho_y
factorA=self.densityA**self.gamma-self.densityA
#construct source terms
source_rho = x_vec[0]-x_vec[0]
source_e = (factorA/(self.gamma-1))*(rho_gamma_t + self.gamma*(u_x*rho**self.gamma+u*rho_gamma_x)+ \
self.gamma*(v_y*rho**self.gamma+v*rho_gamma_y))
source_rhou = factorA*rho_gamma_x
source_rhov = factorA*rho_gamma_y
from hedge.tools import join_fields
return join_fields(source_rho, source_e, source_rhou, source_rhov, x_vec[0]-x_vec[0])
def volume_interpolant(self,t,q,discr):
return discr.convert_volume(
self(t,discr.nodes.T,q),
kind=discr.compute_kind)
def main(write_output=True):
from hedge.backends import guess_run_context
rcon = guess_run_context(
#["cuda"]
)
gamma = 1.4
# at A=1 we have case of isentropic vortex, source terms
# arise for other values
densityA = 2.0
from hedge.tools import EOCRecorder, to_obj_array
eoc_rec = EOCRecorder()
if rcon.is_head_rank:
from hedge.mesh import \
make_rect_mesh, \
make_centered_regular_rect_mesh
refine = 1
mesh = make_centered_regular_rect_mesh((0,-5), (10,5), n=(9,9),
post_refine_factor=refine)
mesh_data = rcon.distribute_mesh(mesh)
else:
mesh_data = rcon.receive_mesh()
for order in [4,5]:
discr = rcon.make_discretization(mesh_data, order=order,
debug=[#"cuda_no_plan",
#"print_op_code"
],
default_scalar_type=numpy.float64)
from hedge.visualization import SiloVisualizer, VtkVisualizer
#vis = VtkVisualizer(discr, rcon, "vortex-%d" % order)
vis = SiloVisualizer(discr, rcon)
vortex = Vortex(beta=5, gamma=gamma,
center=[5,0],
velocity=[1,0], densityA=densityA)
fields = vortex.volume_interpolant(0, discr)
sources=SourceTerms(beta=5, gamma=gamma,
center=[5,0],
velocity=[1,0], densityA=densityA)
from hedge.models.gas_dynamics import (
GasDynamicsOperator, GammaLawEOS)
from hedge.mesh import TAG_ALL
op = GasDynamicsOperator(dimensions=2,
mu=0.0, prandtl=0.72, spec_gas_const=287.1,
equation_of_state=GammaLawEOS(vortex.gamma),
bc_inflow=vortex, bc_outflow=vortex, bc_noslip=vortex,
inflow_tag=TAG_ALL, source=sources)
euler_ex = op.bind(discr)
max_eigval = [0]
def rhs(t, q):
ode_rhs, speed = euler_ex(t, q)
max_eigval[0] = speed
return ode_rhs
rhs(0, fields)
if rcon.is_head_rank:
print("---------------------------------------------")
print("order %d" % order)
print("---------------------------------------------")
print("#elements=", len(mesh.elements))
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# limiter setup -------------------------------------------------------
from hedge.models.gas_dynamics import SlopeLimiter1NEuler
limiter = SlopeLimiter1NEuler(discr, gamma, 2, op)
# time stepper --------------------------------------------------------
from hedge.timestep import SSPRK3TimeStepper, RK4TimeStepper
#stepper = SSPRK3TimeStepper(limiter=limiter)
#stepper = SSPRK3TimeStepper()
stepper = RK4TimeStepper()
# diagnostics setup ---------------------------------------------------
from pytools.log import LogManager, add_general_quantities, \
add_simulation_quantities, add_run_info
if write_output:
log_file_name = "euler-%d.dat" % order
else:
log_file_name = None
logmgr = LogManager(log_file_name, "w", rcon.communicator)
add_run_info(logmgr)
add_general_quantities(logmgr)
add_simulation_quantities(logmgr)
discr.add_instrumentation(logmgr)
stepper.add_instrumentation(logmgr)
logmgr.add_watches(["step.max", "t_sim.max", "t_step.max"])
# timestep loop -------------------------------------------------------
t = 0
#fields = limiter(fields)
try:
from hedge.timestep import times_and_steps
step_it = times_and_steps(
final_time=.1,
#max_steps=500,
logmgr=logmgr,
max_dt_getter=lambda t: 0.4*op.estimate_timestep(discr,
stepper=stepper, t=t, max_eigenvalue=max_eigval[0]))
for step, t, dt in step_it:
if step % 1 == 0 and write_output:
#if False:
visf = vis.make_file("vortex-%d-%04d" % (order, step))
true_fields = vortex.volume_interpolant(t, discr)
#rhs_fields = rhs(t, fields)
from pyvisfile.silo import DB_VARTYPE_VECTOR
vis.add_data(visf,
[
("rho", discr.convert_volume(op.rho(fields), kind="numpy")),
("e", discr.convert_volume(op.e(fields), kind="numpy")),
("rho_u", discr.convert_volume(op.rho_u(fields), kind="numpy")),
("u", discr.convert_volume(op.u(fields), kind="numpy")),
#("true_rho", discr.convert_volume(op.rho(true_fields), kind="numpy")),
#("true_e", discr.convert_volume(op.e(true_fields), kind="numpy")),
#("true_rho_u", discr.convert_volume(op.rho_u(true_fields), kind="numpy")),
#("true_u", discr.convert_volume(op.u(true_fields), kind="numpy")),
#("rhs_rho", discr.convert_volume(op.rho(rhs_fields), kind="numpy")),
#("rhs_e", discr.convert_volume(op.e(rhs_fields), kind="numpy")),
#("rhs_rho_u", discr.convert_volume(op.rho_u(rhs_fields), kind="numpy")),
],
expressions=[
#("diff_rho", "rho-true_rho"),
#("diff_e", "e-true_e"),
#("diff_rho_u", "rho_u-true_rho_u", DB_VARTYPE_VECTOR),
("p", "0.4*(e- 0.5*(rho_u*u))"),
],
time=t, step=step
)
visf.close()
fields = stepper(fields, t, dt, rhs)
true_fields = vortex.volume_interpolant(t, discr)
l2_error = discr.norm(fields-true_fields)
l2_error_rho = discr.norm(op.rho(fields)-op.rho(true_fields))
l2_error_e = discr.norm(op.e(fields)-op.e(true_fields))
l2_error_rhou = discr.norm(op.rho_u(fields)-op.rho_u(true_fields))
l2_error_u = discr.norm(op.u(fields)-op.u(true_fields))
eoc_rec.add_data_point(order, l2_error_rho)
print()
print(eoc_rec.pretty_print("P.Deg.", "L2 Error"))
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logmgr.set_constant("l2_error", l2_error)
logmgr.set_constant("l2_error_rho", l2_error_rho)
logmgr.set_constant("l2_error_e", l2_error_e)
logmgr.set_constant("l2_error_rhou", l2_error_rhou)
logmgr.set_constant("l2_error_u", l2_error_u)
logmgr.set_constant("refinement", refine)
finally:
if write_output:
vis.close()
logmgr.close()
discr.close()
# after order loop
#assert eoc_rec.estimate_order_of_convergence()[0,1] > 6
if __name__ == "__main__":
main()
# entry points for py.test ----------------------------------------------------
from pytools.test import mark_test
@mark_test.long
def test_euler_vortex():
main(write_output=False)