Skip to content
GitLab
Explore
Sign in
Primary navigation
Search or go to…
Project
lbmpy
Manage
Activity
Members
Labels
Plan
Issues
Issue boards
Milestones
Wiki
Code
Merge requests
Repository
Branches
Commits
Tags
Repository graph
Compare revisions
Snippets
Build
Pipelines
Jobs
Pipeline schedules
Artifacts
Deploy
Releases
Model registry
Operate
Environments
Monitor
Incidents
Analyze
Value stream analytics
Contributor analytics
CI/CD analytics
Repository analytics
Model experiments
Help
Help
Support
GitLab documentation
Compare GitLab plans
Community forum
Contribute to GitLab
Provide feedback
Terms and privacy
Keyboard shortcuts
?
Snippets
Groups
Projects
Show more breadcrumbs
pycodegen
lbmpy
Commits
19b91847
Commit
19b91847
authored
3 years ago
by
Michael Kuron
Committed by
Markus Holzer
3 years ago
Browse files
Options
Downloads
Patches
Plain Diff
Oldroyd-B
parent
a991402e
Branches
Branches containing commit
Tags
Tags containing commit
1 merge request
!103
Oldroyd-B
Changes
2
Hide whitespace changes
Inline
Side-by-side
Showing
2 changed files
lbmpy/oldroydb.py
+209
-0
209 additions, 0 deletions
lbmpy/oldroydb.py
lbmpy_tests/test_oldroydb.py
+297
-0
297 additions, 0 deletions
lbmpy_tests/test_oldroydb.py
with
506 additions
and
0 deletions
lbmpy/oldroydb.py
0 → 100644
+
209
−
0
View file @
19b91847
import
pystencils
as
ps
import
sympy
as
sp
import
numpy
as
np
from
pystencils.boundaries.boundaryconditions
import
Boundary
from
pystencils.stencil
import
inverse_direction_string
,
direction_string_to_offset
class
OldroydB
:
def
__init__
(
self
,
dim
,
u
,
tau
,
F
,
tauflux
,
tauface
,
lambda_p
,
eta_p
,
vof
=
True
):
assert
not
ps
.
FieldType
.
is_staggered
(
u
)
assert
not
ps
.
FieldType
.
is_staggered
(
tau
)
assert
not
ps
.
FieldType
.
is_staggered
(
F
)
assert
ps
.
FieldType
.
is_staggered
(
tauflux
)
assert
ps
.
FieldType
.
is_staggered
(
tauface
)
self
.
dim
=
dim
self
.
u
=
u
self
.
tau
=
tau
self
.
F
=
F
self
.
tauflux
=
tauflux
self
.
tauface_field
=
tauface
self
.
lambda_p
=
lambda_p
self
.
eta_p
=
eta_p
full_stencil
=
[
"
C
"
]
+
self
.
tauflux
.
staggered_stencil
+
\
list
(
map
(
inverse_direction_string
,
self
.
tauflux
.
staggered_stencil
))
self
.
stencil
=
tuple
(
map
(
lambda
d
:
tuple
(
ps
.
stencil
.
direction_string_to_offset
(
d
,
self
.
dim
)),
full_stencil
))
full_stencil
=
[
"
C
"
]
+
self
.
tauface_field
.
staggered_stencil
+
\
list
(
map
(
inverse_direction_string
,
self
.
tauface_field
.
staggered_stencil
))
self
.
force_stencil
=
tuple
(
map
(
lambda
d
:
tuple
(
ps
.
stencil
.
direction_string_to_offset
(
d
,
self
.
dim
)),
full_stencil
))
self
.
disc
=
ps
.
fd
.
FVM1stOrder
(
self
.
tau
,
self
.
_flux
(),
self
.
_source
())
if
vof
:
self
.
vof
=
ps
.
fd
.
VOF
(
self
.
tauflux
,
self
.
u
,
self
.
tau
)
else
:
self
.
vof
=
None
def
_flux
(
self
):
return
[
self
.
tau
.
center_vector
.
applyfunc
(
lambda
t
:
t
*
self
.
u
.
center_vector
[
i
])
for
i
in
range
(
self
.
dim
)]
def
_source
(
self
):
gradu
=
sp
.
Matrix
([[
ps
.
fd
.
diff
(
self
.
u
.
center_vector
[
j
],
i
)
for
j
in
range
(
self
.
dim
)]
for
i
in
range
(
self
.
dim
)])
gamma
=
gradu
+
gradu
.
transpose
()
return
self
.
tau
.
center_vector
*
gradu
+
gradu
.
transpose
()
*
self
.
tau
.
center_vector
+
\
(
self
.
eta_p
*
gamma
-
self
.
tau
.
center_vector
)
/
self
.
lambda_p
def
tauface
(
self
):
return
ps
.
AssignmentCollection
([
ps
.
Assignment
(
self
.
tauface_field
.
staggered_vector_access
(
d
),
(
self
.
tau
.
center_vector
+
self
.
tau
.
neighbor_vector
(
d
))
/
2
)
for
d
in
self
.
tauface_field
.
staggered_stencil
])
def
force
(
self
):
full_stencil
=
self
.
tauface_field
.
staggered_stencil
+
\
list
(
map
(
inverse_direction_string
,
self
.
tauface_field
.
staggered_stencil
))
dtau
=
sp
.
Matrix
([
sum
([
sum
([
self
.
tauface_field
.
staggered_access
(
d
,
(
i
,
j
))
*
direction_string_to_offset
(
d
)[
i
]
for
i
in
range
(
self
.
dim
)])
/
sp
.
Matrix
(
direction_string_to_offset
(
d
)).
norm
()
for
d
in
full_stencil
])
for
j
in
range
(
self
.
dim
)])
A0
=
sum
([
sp
.
Matrix
(
direction_string_to_offset
(
d
)).
norm
()
for
d
in
full_stencil
])
return
ps
.
AssignmentCollection
(
ps
.
Assignment
(
self
.
F
.
center_vector
,
dtau
/
A0
*
2
*
self
.
dim
))
def
flux
(
self
):
if
self
.
vof
is
not
None
:
return
self
.
vof
else
:
return
self
.
disc
.
discrete_flux
(
self
.
tauflux
)
def
continuity
(
self
):
cont
=
self
.
disc
.
discrete_continuity
(
self
.
tauflux
)
tau_copy
=
sp
.
Matrix
(
self
.
dim
,
self
.
dim
,
lambda
i
,
j
:
sp
.
Symbol
(
"
tau_old_%d_%d
"
%
(
i
,
j
)))
tau_subs
=
{
self
.
tau
.
center_vector
[
i
,
j
]:
tau_copy
[
i
,
j
]
for
i
in
range
(
self
.
dim
)
for
j
in
range
(
self
.
dim
)}
return
[
ps
.
Assignment
(
tau_copy
[
i
,
j
],
self
.
tau
.
center_vector
[
i
,
j
])
for
i
in
range
(
self
.
dim
)
for
j
in
range
(
self
.
dim
)]
+
\
[
ps
.
Assignment
(
a
.
lhs
,
a
.
rhs
.
subs
(
tau_subs
))
for
a
in
cont
]
class
Flux
(
Boundary
):
inner_or_boundary
=
True
# call the boundary condition with the fluid cell
single_link
=
False
# needs to be called for all directional fluxes
def
__init__
(
self
,
stencil
,
value
=
None
):
self
.
stencil
=
stencil
self
.
value
=
value
def
__call__
(
self
,
field
,
direction_symbol
,
**
kwargs
):
assert
ps
.
FieldType
.
is_staggered
(
field
)
assert
all
([
s
==
0
for
s
in
self
.
stencil
[
0
]])
accesses
=
[
field
.
staggered_vector_access
(
ps
.
stencil
.
offset_to_direction_string
(
d
))
for
d
in
self
.
stencil
[
1
:]]
conds
=
[
sp
.
Equality
(
direction_symbol
,
d
+
1
)
for
d
in
range
(
len
(
accesses
))]
if
self
.
value
is
None
:
val
=
sp
.
Matrix
(
np
.
zeros
(
accesses
[
0
].
shape
,
dtype
=
int
))
else
:
val
=
self
.
value
# use conditional
conditional
=
None
for
a
,
c
,
d
in
zip
(
accesses
,
conds
,
self
.
stencil
[
1
:]):
d
=
ps
.
stencil
.
offset_to_direction_string
(
d
)
assignments
=
[]
for
i
in
range
(
len
(
a
)):
fac
=
1
if
ps
.
FieldType
.
is_staggered_flux
(
field
)
and
type
(
a
[
i
])
is
sp
.
Mul
and
a
[
i
].
args
[
0
]
==
-
1
:
fac
=
a
[
i
].
args
[
0
]
a
[
i
]
*=
a
[
i
].
args
[
0
]
assignments
.
append
(
ps
.
Assignment
(
a
[
i
],
fac
*
val
[
i
]))
if
len
(
assignments
)
>
0
:
conditional
=
ps
.
astnodes
.
Conditional
(
ps
.
data_types
.
type_all_numbers
(
c
,
"
int
"
),
ps
.
astnodes
.
Block
(
assignments
),
conditional
)
return
[
conditional
]
def
__hash__
(
self
):
return
hash
((
Flux
,
self
.
stencil
,
self
.
value
))
def
__eq__
(
self
,
other
):
return
type
(
other
)
==
Flux
and
other
.
stencil
==
self
.
stencil
and
self
.
value
==
other
.
value
class
Extrapolation
(
Boundary
):
inner_or_boundary
=
True
# call the boundary condition with the fluid cell
single_link
=
False
# needs to be called for all directional fluxes
def
__init__
(
self
,
stencil
,
src_field
,
order
):
self
.
stencil
=
stencil
self
.
src
=
src_field
if
order
==
0
:
self
.
weights
=
(
1
,)
elif
order
==
1
:
self
.
weights
=
(
sp
.
Rational
(
3
,
2
),
-
sp
.
Rational
(
1
,
2
))
elif
order
==
2
:
self
.
weights
=
(
sp
.
Rational
(
15
,
8
),
-
sp
.
Rational
(
10
,
8
),
sp
.
Rational
(
3
,
8
))
else
:
raise
NotImplementedError
(
"
weights are not known for extrapolation orders > 2
"
)
def
__call__
(
self
,
field
,
direction_symbol
,
**
kwargs
):
assert
ps
.
FieldType
.
is_staggered
(
field
)
assert
all
([
s
==
0
for
s
in
self
.
stencil
[
0
]])
accesses
=
[
field
.
staggered_vector_access
(
ps
.
stencil
.
offset_to_direction_string
(
d
))
for
d
in
self
.
stencil
[
1
:]]
conds
=
[
sp
.
Equality
(
direction_symbol
,
d
+
1
)
for
d
in
range
(
len
(
accesses
))]
# use conditional
conditional
=
None
for
a
,
c
,
o
in
zip
(
accesses
,
conds
,
self
.
stencil
[
1
:]):
assignments
=
[]
src
=
[
self
.
src
.
neighbor_vector
(
tuple
([
-
1
*
n
*
i
for
i
in
o
]))
for
n
in
range
(
len
(
self
.
weights
))]
interp
=
self
.
weights
[
0
]
*
src
[
0
]
for
i
in
range
(
1
,
len
(
self
.
weights
)):
interp
+=
self
.
weights
[
i
]
*
src
[
i
]
for
i
in
range
(
len
(
a
)):
fac
=
1
if
ps
.
FieldType
.
is_staggered_flux
(
field
)
and
type
(
a
[
i
])
is
sp
.
Mul
and
a
[
i
].
args
[
0
]
==
-
1
:
fac
=
a
[
i
].
args
[
0
]
a
[
i
]
*=
a
[
i
].
args
[
0
]
assignments
.
append
(
ps
.
Assignment
(
a
[
i
],
fac
*
interp
[
i
]))
if
len
(
assignments
)
>
0
:
conditional
=
ps
.
astnodes
.
Conditional
(
ps
.
data_types
.
type_all_numbers
(
c
,
"
int
"
),
ps
.
astnodes
.
Block
(
assignments
),
conditional
)
return
[
conditional
]
def
__hash__
(
self
):
return
hash
((
Extrapolation
,
self
.
stencil
,
self
.
src
,
self
.
weights
))
def
__eq__
(
self
,
other
):
return
type
(
other
)
==
Extrapolation
and
other
.
stencil
==
self
.
stencil
and
\
other
.
src
==
self
.
src
and
other
.
weights
==
self
.
weights
class
ForceOnBoundary
(
Boundary
):
inner_or_boundary
=
False
# call the boundary condition with the boundary cell
single_link
=
False
# needs to be called for all directional fluxes
def
__init__
(
self
,
stencil
,
force_field
):
self
.
stencil
=
stencil
self
.
force_field
=
force_field
assert
not
ps
.
FieldType
.
is_staggered
(
force_field
)
def
__call__
(
self
,
face_stress_field
,
direction_symbol
,
**
kwargs
):
assert
ps
.
FieldType
.
is_staggered
(
face_stress_field
)
assert
all
([
s
==
0
for
s
in
self
.
stencil
[
0
]])
accesses
=
[
face_stress_field
.
staggered_vector_access
(
ps
.
stencil
.
offset_to_direction_string
(
d
))
for
d
in
self
.
stencil
[
1
:]]
conds
=
[
sp
.
Equality
(
direction_symbol
,
d
+
1
)
for
d
in
range
(
len
(
accesses
))]
# use conditional
conditional
=
None
for
a
,
c
,
o
in
zip
(
accesses
,
conds
,
self
.
stencil
[
1
:]):
assignments
=
ps
.
Assignment
(
self
.
force_field
.
center_vector
,
self
.
force_field
.
center_vector
+
1
*
a
.
transpose
()
*
sp
.
Matrix
(
o
))
conditional
=
ps
.
astnodes
.
Conditional
(
ps
.
data_types
.
type_all_numbers
(
c
,
"
int
"
),
ps
.
astnodes
.
Block
(
assignments
),
conditional
)
return
[
conditional
]
def
__hash__
(
self
):
return
hash
((
ForceOnBoundary
,
self
.
stencil
,
self
.
force_field
))
def
__eq__
(
self
,
other
):
return
type
(
other
)
==
ForceOnBoundary
and
other
.
stencil
==
self
.
stencil
and
\
other
.
force_field
==
self
.
force_field
This diff is collapsed.
Click to expand it.
lbmpy_tests/test_oldroydb.py
0 → 100755
+
297
−
0
View file @
19b91847
import
pystencils
as
ps
from
lbmpy.stencils
import
get_stencil
from
lbmpy.updatekernels
import
create_stream_pull_with_output_kernel
from
lbmpy
import
create_lb_update_rule
,
relaxation_rate_from_lattice_viscosity
,
ForceModel
,
Method
,
LBStencil
from
lbmpy.macroscopic_value_kernels
import
macroscopic_values_setter
from
pystencils.boundaries.boundaryhandling
import
BoundaryHandling
from
pystencils.boundaries.boundaryconditions
import
Boundary
,
Neumann
,
Dirichlet
from
lbmpy.boundaries.boundaryhandling
import
LatticeBoltzmannBoundaryHandling
from
lbmpy.boundaries
import
NoSlip
from
lbmpy.oldroydb
import
*
import
pytest
# # Lattice Boltzmann with Finite-Volume Oldroyd-B
# # taken from the electronic supplement of https://doi.org/10.1140/epje/s10189-020-00005-6,
# # available at https://doi.org/10.24416/UU01-2AFZSW
pytest
.
importorskip
(
'
scipy.optimize
'
)
def
test_oldroydb
():
import
scipy.optimize
# ## Definitions
# In[2]:
L
=
(
34
,
34
)
lambda_p
=
sp
.
Symbol
(
"
lambda_p
"
)
eta_p
=
sp
.
Symbol
(
"
eta_p
"
)
lb_stencil
=
LBStencil
(
"
D2Q9
"
)
fv_stencil
=
LBStencil
(
"
D2Q9
"
)
eta
=
1
-
eta_p
omega
=
relaxation_rate_from_lattice_viscosity
(
eta
)
f_pre
=
0.00001
# ## Data structures
# In[3]:
dh
=
ps
.
create_data_handling
(
L
,
periodicity
=
(
True
,
False
),
default_target
=
ps
.
Target
.
CPU
)
opts
=
{
'
cpu_openmp
'
:
True
,
'
cpu_vectorize_info
'
:
None
,
'
target
'
:
dh
.
default_target
}
src
=
dh
.
add_array
(
'
src
'
,
values_per_cell
=
len
(
lb_stencil
),
layout
=
'
c
'
)
dst
=
dh
.
add_array_like
(
'
dst
'
,
'
src
'
)
ρ
=
dh
.
add_array
(
'
rho
'
,
layout
=
'
c
'
,
latex_name
=
'
\\
rho
'
)
u
=
dh
.
add_array
(
'
u
'
,
values_per_cell
=
dh
.
dim
,
layout
=
'
c
'
)
tauface
=
dh
.
add_array
(
'
tau_face
'
,
values_per_cell
=
(
len
(
fv_stencil
)
//
2
,
dh
.
dim
,
dh
.
dim
),
latex_name
=
'
\\
tau_f
'
,
field_type
=
ps
.
FieldType
.
STAGGERED
,
layout
=
'
c
'
)
tau
=
dh
.
add_array
(
'
tau
'
,
values_per_cell
=
(
dh
.
dim
,
dh
.
dim
),
layout
=
'
c
'
,
latex_name
=
'
\\
tau
'
)
tauflux
=
dh
.
add_array
(
'
j_tau
'
,
values_per_cell
=
(
len
(
fv_stencil
)
//
2
,
dh
.
dim
,
dh
.
dim
),
latex_name
=
'
j_
\\
tau
'
,
field_type
=
ps
.
FieldType
.
STAGGERED_FLUX
,
layout
=
'
c
'
)
F
=
dh
.
add_array
(
'
F
'
,
values_per_cell
=
dh
.
dim
,
layout
=
'
c
'
)
fluxbh
=
BoundaryHandling
(
dh
,
tauflux
.
name
,
fv_stencil
,
name
=
"
flux_boundary_handling
"
,
openmp
=
opts
[
'
cpu_openmp
'
],
target
=
dh
.
default_target
)
ubh
=
BoundaryHandling
(
dh
,
u
.
name
,
lb_stencil
,
name
=
"
velocity_boundary_handling
"
,
openmp
=
opts
[
'
cpu_openmp
'
],
target
=
dh
.
default_target
)
taufacebh
=
BoundaryHandling
(
dh
,
tauface
.
name
,
fv_stencil
,
name
=
"
tauface_boundary_handling
"
,
openmp
=
opts
[
'
cpu_openmp
'
],
target
=
dh
.
default_target
)
# ## Solver
# In[4]:
collision
=
create_lb_update_rule
(
stencil
=
lb_stencil
,
method
=
Method
.
TRT
,
relaxation_rate
=
omega
,
compressible
=
True
,
force_model
=
ForceModel
.
GUO
,
force
=
F
.
center_vector
+
sp
.
Matrix
([
f_pre
,
0
]),
kernel_type
=
'
collide_only
'
,
optimization
=
{
'
symbolic_field
'
:
src
})
stream
=
create_stream_pull_with_output_kernel
(
collision
.
method
,
src
,
dst
,
{
'
density
'
:
ρ
,
'
velocity
'
:
u
})
lbbh
=
LatticeBoltzmannBoundaryHandling
(
collision
.
method
,
dh
,
src
.
name
,
openmp
=
opts
[
'
cpu_openmp
'
],
target
=
dh
.
default_target
)
stream_kernel
=
ps
.
create_kernel
(
stream
,
**
opts
).
compile
()
collision_kernel
=
ps
.
create_kernel
(
collision
,
**
opts
).
compile
()
# In[5]:
ob
=
OldroydB
(
dh
.
dim
,
u
,
tau
,
F
,
tauflux
,
tauface
,
lambda_p
,
eta_p
)
flux_kernel
=
ps
.
create_staggered_kernel
(
ob
.
flux
(),
**
opts
).
compile
()
tauface_kernel
=
ps
.
create_staggered_kernel
(
ob
.
tauface
(),
**
opts
).
compile
()
continuity_kernel
=
ps
.
create_kernel
(
ob
.
continuity
(),
**
opts
).
compile
()
force_kernel
=
ps
.
create_kernel
(
ob
.
force
(),
**
opts
).
compile
()
# ## Set up the simulation
# In[6]:
init
=
macroscopic_values_setter
(
collision
.
method
,
velocity
=
(
0
,)
*
dh
.
dim
,
pdfs
=
src
.
center_vector
,
density
=
ρ
.
center
)
init_kernel
=
ps
.
create_kernel
(
init
,
ghost_layers
=
0
).
compile
()
# no-slip for the fluid, no-flux for the stress
noslip
=
NoSlip
()
noflux
=
Flux
(
fv_stencil
)
nostressdiff
=
Flux
(
fv_stencil
,
tau
.
center_vector
)
# put some good values into the boundaries so we can take derivatives
noforce
=
Neumann
()
# put the same stress into the boundary cells that is in the nearest fluid cell
noflow
=
Dirichlet
((
0
,)
*
dh
.
dim
)
# put zero velocity into the boundary cells
lbbh
.
set_boundary
(
noslip
,
ps
.
make_slice
[:,
:
4
])
lbbh
.
set_boundary
(
noslip
,
ps
.
make_slice
[:,
-
4
:])
fluxbh
.
set_boundary
(
noflux
,
ps
.
make_slice
[:,
:
4
])
fluxbh
.
set_boundary
(
noflux
,
ps
.
make_slice
[:,
-
4
:])
ubh
.
set_boundary
(
noflow
,
ps
.
make_slice
[:,
:
4
])
ubh
.
set_boundary
(
noflow
,
ps
.
make_slice
[:,
-
4
:])
taufacebh
.
set_boundary
(
nostressdiff
,
ps
.
make_slice
[:,
:
4
])
taufacebh
.
set_boundary
(
nostressdiff
,
ps
.
make_slice
[:,
-
4
:])
for
bh
in
lbbh
,
fluxbh
,
ubh
,
taufacebh
:
assert
len
(
bh
.
_boundary_object_to_boundary_info
)
==
1
,
"
Restart kernel to clear boundaries
"
def
init
():
dh
.
fill
(
ρ
.
name
,
np
.
nan
,
ghost_layers
=
True
,
inner_ghost_layers
=
True
)
dh
.
fill
(
ρ
.
name
,
1
)
dh
.
fill
(
u
.
name
,
np
.
nan
,
ghost_layers
=
True
,
inner_ghost_layers
=
True
)
dh
.
fill
(
u
.
name
,
0
)
dh
.
fill
(
tau
.
name
,
np
.
nan
,
ghost_layers
=
True
,
inner_ghost_layers
=
True
)
dh
.
fill
(
tau
.
name
,
0
)
dh
.
fill
(
tauflux
.
name
,
np
.
nan
,
ghost_layers
=
True
,
inner_ghost_layers
=
True
)
dh
.
fill
(
tauface
.
name
,
np
.
nan
,
ghost_layers
=
True
,
inner_ghost_layers
=
True
)
dh
.
fill
(
F
.
name
,
np
.
nan
,
ghost_layers
=
True
,
inner_ghost_layers
=
True
)
dh
.
fill
(
F
.
name
,
0
)
# needed for LB initialization
sync_tau
()
# force calculation inside the initialization needs neighbor taus
dh
.
run_kernel
(
init_kernel
)
dh
.
fill
(
F
.
name
,
np
.
nan
)
# In[7]:
sync_pdfs
=
dh
.
synchronization_function
([
src
.
name
])
# needed before stream, but after collision
sync_u
=
dh
.
synchronization_function
([
u
.
name
])
# needed before continuity, but after stream
sync_tau
=
dh
.
synchronization_function
([
tau
.
name
])
# needed before flux and tauface, but after continuity
def
time_loop
(
steps
,
lambda_p_val
,
eta_p_val
):
dh
.
all_to_gpu
()
vmid
=
np
.
empty
((
2
,
steps
//
10
+
1
))
sync_tau
()
sync_u
()
ubh
()
i
=
-
1
for
i
in
range
(
steps
):
dh
.
run_kernel
(
flux_kernel
)
fluxbh
()
# zero the fluxes into/out of boundaries
dh
.
run_kernel
(
continuity_kernel
,
**
{
lambda_p
.
name
:
lambda_p_val
,
eta_p
.
name
:
eta_p_val
})
sync_tau
()
dh
.
run_kernel
(
tauface_kernel
)
# needed for force
taufacebh
()
dh
.
run_kernel
(
force_kernel
)
dh
.
run_kernel
(
collision_kernel
,
**
{
eta_p
.
name
:
eta_p_val
})
sync_pdfs
()
lbbh
()
# bounce-back populations into boundaries
dh
.
run_kernel
(
stream_kernel
)
sync_u
()
ubh
()
# need neighboring us for flux and continuity
dh
.
swap
(
src
.
name
,
dst
.
name
)
if
i
%
10
==
0
:
if
u
.
name
in
dh
.
gpu_arrays
:
dh
.
to_cpu
(
u
.
name
)
uu
=
dh
.
gather_array
(
u
.
name
)
uu
=
uu
[
L
[
0
]
//
2
-
1
:
L
[
0
]
//
2
+
1
,
L
[
1
]
//
2
-
1
:
L
[
1
]
//
2
+
1
,
0
].
mean
()
if
np
.
isnan
(
uu
):
raise
Exception
(
f
"
NaN encountered after
{
i
}
steps
"
)
vmid
[:,
i
//
10
]
=
[
i
,
uu
]
sync_u
()
dh
.
all_to_cpu
()
return
vmid
[:,:
i
//
10
+
1
]
# ## Analytical solution
#
# comes from Waters and King, Unsteady flow of an elastico-viscous liquid, Rheologica Acta 9, 345–355 (1970).
# In[9]:
def
N
(
n
):
return
(
2
*
n
-
1
)
*
np
.
pi
def
Alpha_n
(
N
,
El
,
eta_p
):
return
1
+
(
1
-
eta_p
)
*
El
*
N
*
N
/
4
def
Beta_n
(
alpha_n
,
N
,
El
):
return
np
.
sqrt
(
np
.
abs
(
alpha_n
*
alpha_n
-
El
*
N
*
N
))
def
Gamma_n
(
N
,
El
,
eta_p
):
return
1
-
(
1
+
eta_p
)
*
El
*
N
*
N
/
4
def
G
(
alpha_n
,
beta_n
,
gamma_n
,
flag
,
T
):
if
(
flag
):
return
((
1.0
-
gamma_n
/
beta_n
)
*
np
.
exp
(
-
(
alpha_n
+
beta_n
)
*
T
/
2
)
+
(
1.0
+
gamma_n
/
beta_n
)
*
np
.
exp
((
beta_n
-
alpha_n
)
*
T
/
2
))
else
:
return
2
*
np
.
exp
(
-
alpha_n
*
T
/
2
)
*
(
np
.
cos
(
beta_n
*
T
/
2
)
+
(
gamma_n
/
beta_n
)
*
np
.
sin
(
beta_n
*
T
/
2
))
def
W
(
T
,
El
,
eta_p
):
W_
=
1.5
for
n
in
range
(
1
,
1000
):
N_
=
N
(
n
)
alpha_n
=
Alpha_n
(
N_
,
El
,
eta_p
)
if
(
alpha_n
*
alpha_n
-
El
*
N_
*
N_
<
0
):
flag_
=
False
else
:
flag_
=
True
beta_n
=
Beta_n
(
alpha_n
,
N_
,
El
)
gamma_n
=
Gamma_n
(
N_
,
El
,
eta_p
)
G_
=
G
(
alpha_n
,
beta_n
,
gamma_n
,
flag_
,
T
)
W_
-=
24
*
(
np
.
sin
(
N_
/
2
)
/
(
N_
*
N_
*
N_
))
*
G_
return
W_
# ## Run the simulation
# In[11]:
lambda_p_val
=
3000
eta_p_val
=
0.9
init
()
vmid
=
time_loop
(
lambda_p_val
*
4
,
lambda_p_val
,
eta_p_val
)
actual_width
=
sum
(
dh
.
gather_array
(
lbbh
.
flag_array_name
)[
L
[
0
]
//
2
,:]
==
1
)
uref
=
float
(
f_pre
*
actual_width
**
2
/
(
8
*
(
eta
+
eta_p
)))
Wi
=
lambda_p_val
*
uref
/
(
actual_width
/
2
)
Re
=
uref
*
(
actual_width
/
2
)
/
(
eta
+
eta_p
)
El
=
float
(
Wi
/
Re
)
pref
=
1
/
W
(
vmid
[
0
,
-
1
]
/
lambda_p_val
,
El
,
eta_p_val
)
El_measured
,
pref_measured
=
scipy
.
optimize
.
curve_fit
(
lambda
a
,
b
,
c
:
W
(
a
,
b
,
eta_p_val
)
*
c
,
vmid
[
0
,:]
/
lambda_p_val
,
vmid
[
1
,:]
/
vmid
[
1
,
-
1
],
p0
=
(
El
,
pref
))[
0
]
measured_width
=
np
.
sqrt
(
4
*
lambda_p_val
*
float
(
eta
+
eta_p
)
/
El_measured
)
print
(
f
"
El=
{
El
}
, El_measured=
{
El_measured
}
"
)
print
(
f
"
L=
{
actual_width
}
, L_measured=
{
measured_width
}
"
)
assert
abs
(
measured_width
-
actual_width
)
<
1
,
"
effective channel width differs significantly from defined width
"
an
=
W
(
vmid
[
0
,:]
/
lambda_p_val
,
El
,
eta_p_val
)
*
pref
an_measured
=
W
(
vmid
[
0
,:]
/
lambda_p_val
,
El_measured
,
eta_p_val
)
*
pref_measured
diff
=
abs
(
vmid
[
1
,:]
/
vmid
[
1
,
-
1
]
-
an_measured
)
/
an_measured
assert
diff
[
lambda_p_val
//
5
:].
max
()
<
0.03
,
"
maximum velocity deviation is too large
"
# from pystencils import plot as plt
#
# plt.xlabel("$t$")
# plt.ylabel(r"$u_{max}/u_{max}^{Newtonian}$")
# plt.plot(vmid[0,:], vmid[1,:]/vmid[1,-1] if vmid[1,-1] != 0 else 0, label='FVM')
# plt.plot(vmid[0,:], np.ones_like(vmid[0,:]), 'k--', label='Newtonian')
#
# plt.plot(vmid[0,:], an, label="analytic")
# plt.plot(vmid[0,:], an_measured, label="analytic, fit width")
# plt.legend()
#
# if eta_p_val == 0.1:
# plt.ylim(0.9, 1.15)
# elif lambda_p_val == 9000:
# plt.ylim(0.8, 1.5)
# elif eta_p_val == 0.3:
# plt.ylim(0.8, 1.4)
# plt.show()
This diff is collapsed.
Click to expand it.
Preview
0%
Loading
Try again
or
attach a new file
.
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Save comment
Cancel
Please
register
or
sign in
to comment