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particle_methods
hysop
Commits
c46488ac
Commit
c46488ac
authored
11 years ago
by
Jean-Matthieu Etancelin
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Examples/NS_planeJet.py
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c46488ac
#!/usr/bin/python
"""
Taylor Green 3D : see paper van Rees 2011.
All parameters are set and defined in python module dataTG.
"""
import
parmepy
as
pp
from
parmepy.constants
import
ORDER
,
np
,
PARMES_REAL
from
parmepy.f2py
import
fftw2py
import
numpy
as
np
from
parmepy.fields.continuous
import
Field
from
parmepy.variables.variables
import
Variables
from
parmepy.mpi.topology
import
Cartesian
from
parmepy.operator.advection
import
Advection
from
parmepy.operator.stretching
import
Stretching
from
parmepy.operator.poisson
import
Poisson
from
parmepy.operator.diffusion
import
Diffusion
from
parmepy.operator.adapt_timestep
import
AdaptTimeStep
from
parmepy.operator.redistribute
import
Redistribute
from
parmepy.problem.navier_stokes
import
NSProblem
from
parmepy.operator.monitors.printer
import
Printer
from
parmepy.operator.monitors.energy_enstrophy
import
Energy_enstrophy
from
parmepy.problem.simulation
import
Simulation
from
parmepy.operator.adapt_timestep
import
AdaptTimeStep
from
parmepy.methods_keys
import
Scales
from
parmepy.operator.differential
import
Curl
from
parmepy.numerics.updateGhosts
import
UpdateGhosts
from
parmepy.mpi.main_var
import
main_size
from
parmepy.methods_keys
import
Scales
,
TimeIntegrator
,
Interpolation
,
\
Remesh
,
Support
,
Splitting
,
dtAdvecCrit
,
SpaceDiscretisation
,
GhostUpdate
from
parmepy.numerics.integrators.runge_kutta2
import
RK2
as
RK2
from
parmepy.numerics.integrators.runge_kutta3
import
RK3
as
RK3
from
parmepy.numerics.integrators.runge_kutta4
import
RK4
as
RK4
from
parmepy.numerics.finite_differences
import
FD_C_4
,
FD_C_2
from
parmepy.numerics.interpolation
import
Linear
from
parmepy.numerics.remeshing
import
L4_2
as
rmsh
from
parmepy.f2py
import
fftw2py
# problem dimension
dim
=
3
# resolution
nb
=
129
# number of ghosts in usual cartesian topo
NBGHOSTS
=
2
ADVECTION_METHOD
=
{
Scales
:
'
p_66
'
}
# ADVECTION_METHOD = {TimeIntegrator: RK2,
# Interpolation: Linear,
# Remesh: rmsh,
# Support: '',
# Splitting: 'o2_FullHalf'}
VISCOSITY
=
5e-6
## ----------- A 3d problem -----------
print
"
========= Start Navier-Stokes 3D (Taylor Green benchmark) =========
"
## pi constant
pi
=
np
.
pi
cos
=
np
.
cos
sin
=
np
.
sin
exp
=
np
.
exp
abs
=
np
.
abs
tanh
=
np
.
tanh
## Domain
box
=
pp
.
Box
(
dim
,
length
=
[
1.
,
]
*
3
)
## Global resolution
nbElem
=
[
nb
]
*
dim
randX
=
np
.
asarray
(
np
.
random
.
random
([
nb
-
1
,
nb
-
1
,(
nb
-
1
)
/
main_size
]),
dtype
=
PARMES_REAL
,
order
=
ORDER
)
-
0.5
randY
=
np
.
asarray
(
np
.
random
.
random
([
nb
-
1
,
nb
-
1
,(
nb
-
1
)
/
main_size
]),
dtype
=
PARMES_REAL
,
order
=
ORDER
)
-
0.5
randZ
=
np
.
asarray
(
np
.
random
.
random
([
nb
-
1
,
nb
-
1
,(
nb
-
1
)
/
main_size
]),
dtype
=
PARMES_REAL
,
order
=
ORDER
)
-
0.5
# ##initjet.f
# width = 0.01
# ampl3 = 0.3
# ampl2 = 0.
# ampl = 0.05
# def computeVel(res, x, y, z, t):
# yy = abs(y - 0.5)
# aux=(0.1-2.*yy)/(4.*width)
# res[0][...] =0.5*(1.+tanh(aux))*(1.+ampl3*sin(8.*pi*(x)))*(1.+ampl*exp(-abs((0.1-2.*yy)/(4.*width)**2))*randX)
# res[1][...] = ampl*exp(-abs((0.1-2.*yy)/(4.*width)**2))*randY
# res[2][...] = ampl*exp(-abs((0.1-2.*yy)/(4.*width)**2))*randZ
# return res
# def initScal(res, x, y, z, t):
# yy = abs(y - 0.5)
# aux=(0.1-2.*yy)/(4.*width)
# res[0][...] = 0.5*(1.+tanh(aux))*(1.+ampl2*exp(-abs((0.1-2.*yy)/(4.*width)**2))*randZ)
# return res
# ## JCP initial condition
def
computeVel
(
res
,
x
,
y
,
z
,
t
):
res
[
0
][...]
=
0.5
*
(
1.
-
tanh
((
abs
(
y
-
0.5
)
-
0.1
/
2.
)
/
0.02
))
*
(
1.
+
0.3
*
sin
(
8
*
pi
*
x
))
res
[
1
][...]
=
0.
res
[
2
][...]
=
0.
return
res
def
initScal
(
res
,
x
,
y
,
z
,
t
):
res
[
0
][...]
=
0.5
*
(
1.
-
tanh
((
abs
(
y
-
0.5
)
-
0.1
/
2.
)
/
0.02
))
*
(
1.
+
0.3
*
sin
(
8
*
pi
*
x
))
return
res
## Fields
velo
=
Field
(
domain
=
box
,
formula
=
computeVel
,
name
=
'
Velocity
'
,
isVector
=
True
)
vorti
=
Field
(
domain
=
box
,
name
=
'
Vorticity
'
,
isVector
=
True
)
scal
=
Field
(
domain
=
box
,
formula
=
initScal
,
name
=
'
PassiveScalar
'
,
isVector
=
False
)
## Variables
dt_adapt
=
Variables
(
domain
=
box
,
name
=
'
adaptative time step
'
,
data
=
[
0.01
])
## Variables
## Usual Cartesian topology definition
# At the moment we use two (or three?) topologies :
# - "topo" for Stretching and all operators based on finite differences.
# --> ghost layer = 2
# - topo from Advection operator for all the other operators.
# --> no ghost layer
# - topo from fftw for Poisson and Diffusion.
# Todo : check compat between scales and fft operators topologies.
ghosts
=
[
NBGHOSTS
]
*
box
.
dimension
topo
=
Cartesian
(
box
,
box
.
dimension
,
nbElem
,
ghosts
=
ghosts
)
## Navier Stokes Operators
advec
=
Advection
(
velo
,
vorti
,
resolutions
=
{
velo
:
nbElem
,
vorti
:
nbElem
},
method
=
ADVECTION_METHOD
)
advecScal
=
Advection
(
velo
,
scal
,
resolutions
=
{
velo
:
nbElem
,
scal
:
nbElem
},
method
=
ADVECTION_METHOD
)
stretch
=
Stretching
(
velo
,
vorti
,
resolutions
=
{
velo
:
nbElem
,
vorti
:
nbElem
},
topo
=
topo
)
diffusion
=
Diffusion
(
vorti
,
resolution
=
nbElem
,
viscosity
=
VISCOSITY
)
poisson
=
Poisson
(
velo
,
vorti
,
resolutions
=
{
velo
:
nbElem
,
vorti
:
nbElem
},
projection
=
[
True
,
1
,
False
],
)
c
=
Curl
(
velo
,
vorti
,
resolutions
=
{
velo
:
nbElem
,
vorti
:
nbElem
},
method
=
{
SpaceDiscretisation
:
fftw2py
,
GhostUpdate
:
False
},
)
## Tools Operators
dtAdapt
=
AdaptTimeStep
(
velo
,
vorti
,
resolutions
=
{
velo
:
nbElem
,
vorti
:
nbElem
},
dt_adapt
=
dt_adapt
,
method
=
{
TimeIntegrator
:
RK3
,
SpaceDiscretisation
:
FD_C_4
,
dtAdvecCrit
:
'
deform
'
},
topo
=
topo
,
lcfl
=
0.125
,
cfl
=
None
,
# 0.5,
prefix
=
'
./res_PS/dt_2p
'
)
## Simulation
simu
=
Simulation
(
tinit
=
0.0
,
tend
=
4.5
,
timeStep
=
dt_adapt
,
iterMax
=
10000
)
# Bridges between the different topologies in order to
# redistribute data.
# 1 -Advection to stretching
toGhost_vorti
=
Redistribute
([
vorti
],
advec
,
stretch
)
toGhost_velo
=
Redistribute
([
velo
],
poisson
,
stretch
)
# 2 - Stretching to Poisson/Diffusion
fromGhost_vorti
=
Redistribute
([
vorti
],
stretch
,
diffusion
)
# 3 - Poisson to TimeStep
distrPoissTimeStep
=
Redistribute
([
velo
,
vorti
],
poisson
,
dtAdapt
)
# Define the problem to solve
pb
=
NSProblem
(
operators
=
[
toGhost_velo
,
advecScal
,
advec
,
toGhost_vorti
,
stretch
,
fromGhost_vorti
,
diffusion
,
poisson
,
distrPoissTimeStep
,
dtAdapt
],
simulation
=
simu
,
dumpFreq
=-
1
)
## Setting solver to Problem (only operators for computational tasks)
pb
.
pre_setUp
()
## Diagnostics related to the problem
topofft
=
poisson
.
discreteFields
[
poisson
.
vorticity
].
topology
# energy = Energy_enstrophy(velo, vorti, isNormalized=True,
# topo=topofft,
# viscosity=VISCOSITY,
# frequency=1,
# prefix='./res_PS/energy_S128_2p.dat')
# initialisation
vorti
.
setTopoInit
(
topofft
)
velo
.
setTopoInit
(
topofft
)
scal
.
setTopoInit
(
topofft
)
#pb.addMonitors([energy])
pb
.
setUp
()
c
.
discretize
()
c
.
setUp
()
c
.
apply
(
simu
)
# p = Printer(variables=[scal,],
# topo=topofft,
# frequency=1,
# prefix='./res_PS/scal_S128_2p',
# ext=".vtk")
# pb.addMonitors([p])
# p._printStep()
# pf = Printer(variables=[velo, vorti],
# topo=topofft,
# frequency=1,
# prefix='./res_PS/fields_S128_2p',
# ext=".vtk")
# pb.addMonitors([pf])
# pf._printStep()
def
run
():
pb
.
solve
()
## Solve problem
from
parmepy.mpi
import
MPI
print
"
Start computation ...
"
time
=
MPI
.
Wtime
()
run
()
print
'
total time (rank):
'
,
MPI
.
Wtime
()
-
time
,
'
(
'
,
topo
.
rank
,
'
)
'
pb
.
finalize
()
## Clean memory buffers
#fftw2py.clean_fftw_solver(box.dimension)
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