- bufferThe buffer this compute is operating on
C++ Type:std::string
Controllable:No
Description:The buffer this compute is operating on
TensorIntegralPostprocessor
Compute the integral over a buffer
Takes the sum over all grid values multiplied by the grid cell volume.
Overview
Integrates the values in a scalar buffer over the domain by summing all entries and multiplying by the cell volume. Select the input with "buffer".
Example Input File Syntax
[Postprocessors<<<{"href": "../../syntax/Postprocessors/index.html"}>>>]
[int_c]
type = TensorIntegralPostprocessor<<<{"description": "Compute the integral over a buffer", "href": "TensorIntegralPostprocessor.html"}>>>
buffer<<<{"description": "The buffer this compute is operating on"}>>> = c
execute_on<<<{"description": "The list of flag(s) indicating when this object should be executed. For a description of each flag, see https://mooseframework.inl.gov/source/interfaces/SetupInterface.html."}>>> = 'INITIAL TIMESTEP_END'
[]
[]Input Parameters
- allow_duplicate_execution_on_initialFalseIn the case where this UserObject is depended upon by an initial condition, allow it to be executed twice during the initial setup (once before the IC and again after mesh adaptivity (if applicable).
Default:False
C++ Type:bool
Controllable:No
Description:In the case where this UserObject is depended upon by an initial condition, allow it to be executed twice during the initial setup (once before the IC and again after mesh adaptivity (if applicable).
- execute_onTIMESTEP_ENDThe list of flag(s) indicating when this object should be executed. For a description of each flag, see https://mooseframework.inl.gov/source/interfaces/SetupInterface.html.
Default:TIMESTEP_END
C++ Type:ExecFlagEnum
Options:NONE, INITIAL, LINEAR, LINEAR_CONVERGENCE, NONLINEAR, NONLINEAR_CONVERGENCE, POSTCHECK, TIMESTEP_END, TIMESTEP_BEGIN, MULTIAPP_FIXED_POINT_END, MULTIAPP_FIXED_POINT_BEGIN, MULTIAPP_FIXED_POINT_CONVERGENCE, MULTISYSTEM_FIXED_POINT_ITERATION_END, FINAL, CUSTOM, TRANSFER
Controllable:No
Description:The list of flag(s) indicating when this object should be executed. For a description of each flag, see https://mooseframework.inl.gov/source/interfaces/SetupInterface.html.
- execution_order_group0Execution order groups are executed in increasing order (e.g., the lowest number is executed first). Note that negative group numbers may be used to execute groups before the default (0) group. Please refer to the user object documentation for ordering of user object execution within a group.
Default:0
C++ Type:int
Controllable:No
Description:Execution order groups are executed in increasing order (e.g., the lowest number is executed first). Note that negative group numbers may be used to execute groups before the default (0) group. Please refer to the user object documentation for ordering of user object execution within a group.
- force_postauxFalseForces the UserObject to be executed in POSTAUX
Default:False
C++ Type:bool
Controllable:No
Description:Forces the UserObject to be executed in POSTAUX
- force_preauxFalseForces the UserObject to be executed in PREAUX
Default:False
C++ Type:bool
Controllable:No
Description:Forces the UserObject to be executed in PREAUX
- force_preicFalseForces the UserObject to be executed in PREIC during initial setup
Default:False
C++ Type:bool
Controllable:No
Description:Forces the UserObject to be executed in PREIC during initial setup
Execution Scheduling Parameters
- control_tagsAdds user-defined labels for accessing object parameters via control logic.
C++ Type:std::vector<std::string>
Controllable:No
Description:Adds user-defined labels for accessing object parameters via control logic.
- enableTrueSet the enabled status of the MooseObject.
Default:True
C++ Type:bool
Controllable:Yes
Description:Set the enabled status of the MooseObject.
- outputsVector of output names where you would like to restrict the output of variables(s) associated with this object
C++ Type:std::vector<OutputName>
Controllable:No
Description:Vector of output names where you would like to restrict the output of variables(s) associated with this object
- use_displaced_meshFalseWhether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.
Default:False
C++ Type:bool
Controllable:No
Description:Whether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.
Advanced Parameters
- prop_getter_suffixAn optional suffix parameter that can be appended to any attempt to retrieve/get material properties. The suffix will be prepended with a '_' character.
C++ Type:MaterialPropertyName
Unit:(no unit assumed)
Controllable:No
Description:An optional suffix parameter that can be appended to any attempt to retrieve/get material properties. The suffix will be prepended with a '_' character.
- use_interpolated_stateFalseFor the old and older state use projected material properties interpolated at the quadrature points. To set up projection use the ProjectedStatefulMaterialStorageAction.
Default:False
C++ Type:bool
Controllable:No
Description:For the old and older state use projected material properties interpolated at the quadrature points. To set up projection use the ProjectedStatefulMaterialStorageAction.
Material Property Retrieval Parameters
Input Files
- (examples/cahn_hilliard/cahnhilliard3.i)
- (test/tests/solvers/nl_coupled.i)
- (test/tests/cahnhilliard/cahnhilliard_explicit_smooth.i)
- (test/tests/postprocessors/postprocessors.i)
- (examples/swift_hohenberg/swifthohenberg.i)
- (test/tests/anisotropic_grain_growth/analytic_hull.i)
- (examples/anisotropic_grain_growth/five_grains_2D.i)
- (test/tests/kks/KKS_no_flux_bc.i)
- (test/tests/real_space/neumann_conservation.i)
- (examples/anisotropic_grain_growth/spherical_grain_Ni.i)
- (test/tests/anisotropic_grain_growth/sigma3_circular_grain.i)
- (test/tests/tensor_compute/parallel_roundtrip_3d.i)
- (test/tests/gradient/gradient_square.i)
- (test/tests/tensor_compute/parallel_roundtrip.i)
- (test/tests/real_space/diffusion.i)
- (test/tests/real_space/deep_ghost_faces.i)
- (test/tests/solvers/etdrk4_diffusion.i)
- (benchmarks/02_oswald_ripening/2a_broyden.i)
- (test/tests/tensor_compute/backandforth.i)
- (test/tests/solvers/coupled.i)
- (test/tests/tensor_compute/coupled_pf_mech.i)
- (benchmarks/01_spinodal_decomposition/1a_secant.i)
- (test/tests/tensor_compute/coupled_pf_mech_secant.i)
- (examples/libtorch_kks/KKS_libtorch.i)
- (examples/cahn_hilliard/cahnhilliard2.i)
- (benchmarks/02_oswald_ripening/2a.i)
- (benchmarks/02_oswald_ripening/2a_secant.i)
- (test/tests/gradient/gradient.i)
- (benchmarks/01_spinodal_decomposition/1a.i)
- (test/tests/tensor_compute/group.i)
- (test/tests/real_space/deep_ghost_periodic.i)
- (test/tests/tensor_compute/parallel.i)
- (examples/swift_hohenberg/rotating_grain.i)
- (test/tests/parsed_tensor/local_vars_derivative.i)
- (examples/cahn_hilliard/cahnhilliard4.i)
- (examples/anisotropic_grain_growth/isotropic_five_grain.i)
- (benchmarks/01_spinodal_decomposition/1a_solver.i)
- (benchmarks/01_spinodal_decomposition/1a_implicit_fd.i)
- (test/tests/solvers/diagonal.i)
- (benchmarks/01_spinodal_decomposition/1b.i)
buffer
C++ Type:std::string
Controllable:No
Description:The buffer this compute is operating on
(test/tests/postprocessors/postprocessors.i)
[Domain]
dim = 2
nx = 40
ny = 40
xmax = 2
ymax = 3
mesh_mode = DUMMY
[]
[TensorBuffers]
[c]
[]
[c_bar]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = -x+y+0.3
[]
[c_bar]
type = ForwardFFT
buffer = c_bar
input = c
[]
[u]
type = ConstantTensor
buffer = u
real = 0
[]
[]
[Solve]
[root]
[test]
type = ForwardFFT
buffer = u_bar
input = u
[]
[]
[]
[]
[TensorSolver]
type = ForwardEulerSolver
time_derivative_reciprocal = c_bar
buffer = u
reciprocal_buffer = u_bar
substeps = 10
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'INITIAL TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'INITIAL TIMESTEP_END'
[]
[avg_c]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'INITIAL TIMESTEP_END'
[]
[int_c]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'INITIAL TIMESTEP_END'
[]
[int_c_bar]
type = ReciprocalIntegral
buffer = c_bar
execute_on = 'INITIAL TIMESTEP_END'
[]
[count]
type = ComputeGroupExecutionCount
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 0
[]
[Outputs]
csv = true
[]
(examples/cahn_hilliard/cahnhilliard3.i)
[Domain]
dim = 3
nx = 100
ny = 100
nz = 100
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
zmax = ${fparse pi*4}
device_names = 'cuda'
mesh_mode = DUMMY
[]
[TensorBuffers]
[c]
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c mu'
output_mode = 'Node Cell'
enable_hdf5 = true
[]
[]
[TensorComputes]
[Initialize]
[c]
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -0.001 # kappa
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2'
derivatives = c
# expression = "0.4*c^3-0.6*c^2+0.2*c"
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = c
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[cavg]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 20
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.8
dt = 0.1
[]
dtmax = 1000
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/solvers/nl_coupled.i)
#
# Simple Cahn-Hilliard solve on a 2D grid.
#
[Domain]
dim = 2
nx = 150
ny = 150
xmax = '${fparse pi*2}'
ymax = '${fparse pi*2}'
mesh_mode = DUMMY
[]
[GlobalParams]
constant_names = 'A B'
constant_expressions = '1 3.5'
[]
[TensorComputes]
[Initialize]
[u]
type = ParsedCompute
buffer = u
extra_symbols = true
expression = 'sin(x)*sin(y)'
expand = REAL
[]
[v]
type = ParsedCompute
buffer = v
extra_symbols = true
expression = 'cos(x)*cos(y)'
expand = REAL
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
[]
# precompute fixed factors for the solve
[D1]
type = ReciprocalLaplacianFactor
factor = 1e-2
buffer = D1
[]
[D2]
type = ReciprocalLaplacianFactor
factor = 1e-3
buffer = D2
[]
[]
[Solve]
[u_bar]
type = ForwardFFT
buffer = u_bar
input = u
[]
[v_bar]
type = ForwardFFT
buffer = v_bar
input = v
[]
[Du]
type = ParsedCompute
buffer = Du
expression = 'D2*v_bar'
inputs = 'D2 v_bar'
[]
[Dv]
type = ParsedCompute
buffer = Dv
expression = 'D2*u_bar'
inputs = 'D2 u_bar'
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'u v'
reciprocal_buffer = 'u_bar v_bar'
linear_reciprocal = 'D1 D1'
nonlinear_reciprocal = 'Du Dv'
substeps = ${ss}
corrector_steps = ${cs}
predictor_order = ${order}
corrector_order = ${order}
[]
[Problem]
type = TensorProblem
[]
[Postprocessors]
[u_min]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MIN
[]
[u_max]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MAX
[]
[v_min]
type = TensorExtremeValuePostprocessor
buffer = v
value_type = MIN
[]
[v_max]
type = TensorExtremeValuePostprocessor
buffer = v
value_type = MAX
[]
[U]
type = TensorIntegralPostprocessor
buffer = u
[]
[V]
type = TensorIntegralPostprocessor
buffer = v
[]
[]
[Executioner]
type = Transient
num_steps = 25
dt = 10
[]
[Outputs]
file_base = nl_coupled_${ss}_${cs}_${order}
csv = true
[]
(test/tests/cahnhilliard/cahnhilliard_explicit_smooth.i)
#
# Simple Cahn-Hilliard solve on a 2D grid. We create a matching (conforming)
# MOOSE mesh (with one element per FFT grid cell) and project the solution onto
# the MOOSE mesh to utilize the exodus output object.
#
[Domain]
dim = 2
nx = 50
ny = 50
xmax = 3
ymax = 3
mesh_mode = DOMAIN
device_names = cpu
[]
[TensorBuffers]
[c]
map_to_aux_variable = c
[]
[cbar]
[]
[mu]
map_to_aux_variable = mu
[]
[]
[TensorComputes]
[Initialize]
[c]
# Random initial condition around a concentration of 1/2
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
seed = 0
[]
[mu_init]
type = ConstantTensor
buffer = mu
[]
# precompute fixed factors for the solve
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[Mkappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = '${fparse 0.2 * 1e-4}' # M * kappa
buffer = Mkappabarbar
[]
[dc_dt_bar_IC]
type = ConstantReciprocalTensor
buffer = dc_dt_bar
[]
[smooth]
type = DeAliasingTensor
buffer = smooth
[]
[]
[Solve]
[cahn_hilliard]
[mu]
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2'
derivatives = c
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[dc_dt_bar]
type = ParsedCompute
buffer = dc_dt_bar
expression = 'smooth * (Mbar*mubar - Mkappabarbar*cbar)'
# expression = '(Mbar*mubar - Mkappabarbar*cbar)'
inputs = 'Mbar mubar Mkappabarbar cbar smooth'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[]
[]
[TensorSolver]
type = ForwardEulerSolver
time_derivative_reciprocal = dc_dt_bar
root_compute = cahn_hilliard
buffer = c
reciprocal_buffer = cbar
substeps = 50
[]
[AuxVariables]
[mu]
# the mu tensor is projected onto this elemental variable
family = MONOMIAL
order = CONSTANT
[]
[c]
# the c tensor is projected onto this nodal variable
[]
[]
[Postprocessors]
[C]
type = TensorIntegralPostprocessor
buffer = c
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 20
dt = 0.5
[]
[Outputs]
exodus = true
csv = true
[]
(test/tests/postprocessors/postprocessors.i)
[Domain]
dim = 2
nx = 40
ny = 40
xmax = 2
ymax = 3
mesh_mode = DUMMY
[]
[TensorBuffers]
[c]
[]
[c_bar]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = -x+y+0.3
[]
[c_bar]
type = ForwardFFT
buffer = c_bar
input = c
[]
[u]
type = ConstantTensor
buffer = u
real = 0
[]
[]
[Solve]
[root]
[test]
type = ForwardFFT
buffer = u_bar
input = u
[]
[]
[]
[]
[TensorSolver]
type = ForwardEulerSolver
time_derivative_reciprocal = c_bar
buffer = u
reciprocal_buffer = u_bar
substeps = 10
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'INITIAL TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'INITIAL TIMESTEP_END'
[]
[avg_c]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'INITIAL TIMESTEP_END'
[]
[int_c]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'INITIAL TIMESTEP_END'
[]
[int_c_bar]
type = ReciprocalIntegral
buffer = c_bar
execute_on = 'INITIAL TIMESTEP_END'
[]
[count]
type = ComputeGroupExecutionCount
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 0
[]
[Outputs]
csv = true
[]
(examples/swift_hohenberg/swifthohenberg.i)
#
# Solve a simple Swift-Hohenberg crystal phase field problem. The initial condition is
# a random melt, which crystalizes out.
#
[Domain]
dim = 2
nx = 400
ny = 400
xmax = ${fparse pi*2*30}
ymax = ${fparse pi*2*30}
device_names = 'cuda'
mesh_mode = DOMAIN
[]
[TensorBuffers]
[psi]
map_to_aux_variable = psi
[]
[psibar]
[]
[psi3]
[]
[psi3bar]
[]
# constant tensors
[linear]
[]
# output
[filter]
map_to_aux_variable = filter
[]
[filterbar]
[]
[]
[AuxVariables]
[psi]
[]
[filter]
[]
[]
[TensorComputes]
[Initialize]
[psi]
type = RandomTensor
buffer = psi
min = 0
max = 0.07
[]
[linear]
type = SwiftHohenbergLinear
buffer = linear
alpha = 1
r = 0.025
[]
[]
[Solve]
[psi3]
type = ParsedCompute
buffer = psi3
expression = "0.20*psi^2-psi^3"
inputs = psi
[]
[psibar]
type = ForwardFFT
buffer = psibar
input = psi
[]
[psi3bar]
type = ForwardFFT
buffer = psi3bar
input = psi3
[]
[]
[Postprocess]
[low_pass]
type = ParsedCompute
buffer = filterbar
extra_symbols = true
expression = 'psibar * exp(-k2*10)'
inputs = psibar
[]
[filter]
type = InverseFFT
buffer = filter
input = filterbar
[]
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = psi
reciprocal_buffer = psibar
linear_reciprocal = linear
nonlinear_reciprocal = psi3bar
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 300
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.2
dt = 10
[]
dtmax = 1000
[]
[Postprocessors]
[min_psi]
type = TensorExtremeValuePostprocessor
buffer = psi
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_psi]
type = TensorExtremeValuePostprocessor
buffer = psi
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[Psi]
type = TensorIntegralPostprocessor
buffer = psi
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'psi'
output_mode = 'Node'
enable_hdf5 = true
[]
[]
[Outputs]
exodus = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/anisotropic_grain_growth/analytic_hull.i)
interface_width = 0.8
r0 = 4
gbe_max = ${units 0.8 J/m^2}
kappa = ${fparse 0.75 * gbe_max * interface_width}
L = 1
g_eta_expr = '(eta^2*(1-eta^2)^2)'
[Domain]
dim = 2
nx = 32
ny = 32
xmax = 16
ymax = 16
mesh_mode = DUMMY
floating_precision = SINGLE
[]
[TensorComputes]
[Initialize]
[eta]
type = ParsedCompute
buffer = 'eta'
extra_symbols = 'true'
expression = 'radius:=sqrt((x-${Domain/xmax}/2)^2+(y-${Domain/ymax}/2)^2);0.5 - 0.5*tanh(2*(radius-${r0})/${interface_width})'
[]
[kappa_linear_term]
type = ReciprocalLaplacianFactor
buffer = kappa_linear_term
factor = ${fparse ${L} * ${kappa}}
[]
[smooth]
type = DeAliasingTensor
method = HOULI
buffer = smooth
[]
[]
[Solve]
[grad_eta_vector]
type = GradientVector
buffer = grad_eta
input = eta
[]
[gb_energy]
type = AnisotropicGBEnergy
buffer = gb_energy
gb_gradient_buffer = grad_eta
dsigma_dn = dsigma_dn
libtorch_model_file = 'marlin:anisotropic_gb_energy/analytic_sigma.pt'
interface_width = ${interface_width}
chunk_size = 256
[]
[bulk_driving_force]
type = ParsedCompute
buffer = 'bulk_driving_force'
expression = '6 * gb_energy * ${g_eta_expr} / ${interface_width}'
inputs = 'mu eta gb_energy'
derivatives = 'eta'
[]
[dmu_dn]
type = ParsedCompute
buffer = 'dmu_dn'
expression = '6 * dsigma_dn / ${interface_width}'
inputs = 'dsigma_dn'
[]
[g]
type = ParsedCompute
buffer = 'g'
expression = '${g_eta_expr}'
inputs = 'eta'
[]
[anisotropy_torque]
type = AnisotropyTorque
buffer = anisotropy_torque
dmu_dn = dmu_dn
g = g
[]
[total_mu_driving_force]
type = ParsedCompute
buffer = 'total_mu_driving_force'
expression = '-${L}*(bulk_driving_force - anisotropy_torque)'
inputs = 'bulk_driving_force anisotropy_torque'
[]
[nonlinear]
type = ForwardFFT
buffer = 'NL'
input = 'total_mu_driving_force'
[]
[smooth_nonlinear]
type = ParsedCompute
buffer = 'smooth_NL'
expression = 'smooth * NL'
inputs = 'smooth NL'
[]
[etabar]
type = ForwardFFT
buffer = etabar
input = eta
[]
[gradient_energy]
type = GradientEnergyDensity
buffer = gradient_energy
gradient_buffers = 'grad_eta'
kappa = ${kappa}
[]
[interface_energy]
type = ParsedCompute
buffer = interface_energy
expression = 'g * 6 * gb_energy / ${interface_width} + gradient_energy'
inputs = 'g gb_energy gradient_energy'
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'eta'
reciprocal_buffer = 'etabar'
linear_reciprocal = 'kappa_linear_term'
nonlinear_reciprocal = 'smooth_NL'
substeps = 1e2
predictor_order = 1
corrector_order = 1
corrector_steps = 1
[]
[Postprocessors]
[total_gb_energy]
type = TensorIntegralPostprocessor
buffer = interface_energy
[]
[]
[TensorOutputs]
active = ''
[xdmf]
type = XDMFTensorOutput
buffer = 'eta gb_energy'
output_mode = 'NODE NODE'
enable_hdf5 = true
transpose = false
[]
[]
[Executioner]
type = Transient
dt = 0.1
num_steps = 2
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(examples/anisotropic_grain_growth/five_grains_2D.i)
interface_width = 1.6
side = 80
gbe_max = '${units 1.24 J/m^2}'
L = '${fparse 1.0 * 1.6 / ${interface_width} }'
# ------------------------------------------------------------------
# Periodic Voronoi-like IC for 5 grains.
#
# Each grain is seeded at a point (xi, yi). We use a smooth *periodic*
# distance metric based on sine functions,
# d_i^2 = (side/pi)^2 * [ sin(pi*(x-xi)/side)^2 + sin(pi*(y-yi)/side)^2 ]
# which reduces to the Euclidean distance near the seed and wraps
# correctly across the periodic boundaries.
#
# The order parameters are then a softmax over the negative distances,
# gr_i = exp(-a*d_i) / sum_j exp(-a*d_j), a = 4/interface_width
# For any two competing grains this reduces exactly to the usual
# 0.5*(1 - tanh(2*(d_i - d_j)/interface_width)) profile, so the
# interfaces come out with the correct width, the partition of unity
# sum_i gr_i = 1 holds identically, and the cell structure is the
# (diffuse) Voronoi tessellation of the seeds under the periodic metric.
# ------------------------------------------------------------------
aexp = '${fparse 4.0 / ${interface_width} }'
lp = '${fparse ${side} / pi }'
kp = '${fparse pi / ${side} }'
# seed points (spread out over the periodic 40x40 domain)
d0 = 'sqrt((${lp}*sin(${kp}*(x-8)))^2 + (${lp}*sin(${kp}*(y-6)))^2)'
d1 = 'sqrt((${lp}*sin(${kp}*(x-28)))^2 + (${lp}*sin(${kp}*(y-10)))^2)'
d2 = 'sqrt((${lp}*sin(${kp}*(x-20)))^2 + (${lp}*sin(${kp}*(y-24)))^2)'
d3 = 'sqrt((${lp}*sin(${kp}*(x-4)))^2 + (${lp}*sin(${kp}*(y-28)))^2)'
d4 = 'sqrt((${lp}*sin(${kp}*(x-34)))^2 + (${lp}*sin(${kp}*(y-33)))^2)'
g_gamma0 = '${fparse sqrt(2) / 3 }' # g(gamma=1.5)
f0_gamma0 = ${fparse 1/8}
kappa = '${fparse gbe_max * interface_width * sqrt(f0_gamma0) / g_gamma0 }'
mu = '${fparse gbe_max / (g_gamma0 * interface_width * sqrt(f0_gamma0) ) }'
g_to_gamma_func = '(1.0/(-3.0944 * g^8 -1.8169*g^6 + 10.323 * g^4 - 8.1819*g^2 + 2.0033))'
dgamma_dsigma = '(g * (24.7552*g^6 + 10.9014*g^4 - 41.292*g^2 + 16.3638) / (-3.0944*g^8 - 1.8169*g^6 + 10.323*g^4 - 8.1819*g^2 + 2.0033)^2 / sqrt(${kappa} * ${mu}) )'
f0 = '((gr0^4/4 - gr0^2/2) + (gr1^4/4 - gr1^2/2) + (gr2^4/4 - gr2^2/2) + (gr3^4/4 - gr3^2/2) + (gr4^4/4 - gr4^2/2) + gamma_01*gr0^2*gr1^2 + gamma_02*gr0^2*gr2^2 + gamma_03*gr0^2*gr3^2 + gamma_04*gr0^2*gr4^2 + gamma_12*gr1^2*gr2^2 + gamma_13*gr1^2*gr3^2 + gamma_14*gr1^2*gr4^2 + gamma_23*gr2^2*gr3^2 + gamma_24*gr2^2*gr4^2 + gamma_34*gr3^2*gr4^2 + 0.25)'
[Domain]
dim = 2
nx = 200
ny = 200
xmax = ${side}
ymax = ${side}
mesh_mode = DUMMY
[]
[TensorComputes]
[Initialize]
# unnormalized softmax weights
[c0]
type = ParsedCompute
buffer = c0
expression = 'exp(-${aexp}*${d0})'
extra_symbols = true
[]
[c1]
type = ParsedCompute
buffer = c1
expression = 'exp(-${aexp}*${d1})'
extra_symbols = true
[]
[c2]
type = ParsedCompute
buffer = c2
expression = 'exp(-${aexp}*${d2})'
extra_symbols = true
[]
[c3]
type = ParsedCompute
buffer = c3
expression = 'exp(-${aexp}*${d3})'
extra_symbols = true
[]
[c4]
type = ParsedCompute
buffer = c4
expression = 'exp(-${aexp}*${d4})'
extra_symbols = true
[]
# normalized order parameters (partition of unity by construction)
[gr0]
type = ParsedCompute
buffer = gr0
expression = 'c0/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr1]
type = ParsedCompute
buffer = gr1
expression = 'c1/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr2]
type = ParsedCompute
buffer = gr2
expression = 'c2/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr3]
type = ParsedCompute
buffer = gr3
expression = 'c3/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr4]
type = ParsedCompute
buffer = gr4
expression = '1 - gr0 - gr1 - gr2 - gr3'
inputs = 'gr0 gr1 gr2 gr3'
[]
[L_kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = 'L_kappa_laplacian'
factor = '${fparse ${L} * ${kappa}}'
[]
[kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = kappa_laplacian
factor = '${kappa}'
[]
[smooth]
type = DeAliasingTensor
method = HOULI
buffer = smooth
[]
[]
[Solve]
[bnds]
type = ParsedCompute
buffer = 'bnds'
inputs = 'gr0 gr1 gr2 gr3 gr4'
expression = 'gr0^2 + gr1^2 + gr2^2 + gr3^2 + gr4^2'
[]
## FFT
[gr0_bar]
type = ForwardFFT
buffer = gr0_bar
input = gr0
[]
[gr1_bar]
type = ForwardFFT
buffer = gr1_bar
input = gr1
[]
[gr2_bar]
type = ForwardFFT
buffer = gr2_bar
input = gr2
[]
[gr3_bar]
type = ForwardFFT
buffer = gr3_bar
input = gr3
[]
[gr4_bar]
type = ForwardFFT
buffer = gr4_bar
input = gr4
[]
[grad_gr0]
type = GradientVector
buffer = grad_gr0
input = gr0
[]
[grad_gr1]
type = GradientVector
buffer = grad_gr1
input = gr1
[]
[grad_gr2]
type = GradientVector
buffer = grad_gr2
input = gr2
[]
[grad_gr3]
type = GradientVector
buffer = grad_gr3
input = gr3
[]
[grad_gr4]
type = GradientVector
buffer = grad_gr4
input = gr4
[]
## Pairwise anisotropic GB energies (10 pairs)
# NOTE: the per-pair libtorch misorientation models (Ri_Rj.pt) will be
# developed separately; placeholder file names below follow the
# existing convention and location.
[sigma_gr0_gr1]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr0_gr1'
dsigma_dgrad_grain1 = 'dsigma_gr0_gr1_dgrad_gr0'
dsigma_dgrad_grain2 = 'dsigma_gr0_gr1_dgrad_gr1'
grad_grain1_buffer = 'grad_gr0'
grad_grain2_buffer = 'grad_gr1'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R1_R2.pt'
chunk_size = 1e5
[]
[sigma_gr0_gr2]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr0_gr2'
dsigma_dgrad_grain1 = 'dsigma_gr0_gr2_dgrad_gr0'
dsigma_dgrad_grain2 = 'dsigma_gr0_gr2_dgrad_gr2'
grad_grain1_buffer = 'grad_gr0'
grad_grain2_buffer = 'grad_gr2'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R1_R3.pt'
chunk_size = 1e5
[]
[sigma_gr0_gr3]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr0_gr3'
dsigma_dgrad_grain1 = 'dsigma_gr0_gr3_dgrad_gr0'
dsigma_dgrad_grain2 = 'dsigma_gr0_gr3_dgrad_gr3'
grad_grain1_buffer = 'grad_gr0'
grad_grain2_buffer = 'grad_gr3'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R1_R4.pt'
chunk_size = 1e5
[]
[sigma_gr0_gr4]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr0_gr4'
dsigma_dgrad_grain1 = 'dsigma_gr0_gr4_dgrad_gr0'
dsigma_dgrad_grain2 = 'dsigma_gr0_gr4_dgrad_gr4'
grad_grain1_buffer = 'grad_gr0'
grad_grain2_buffer = 'grad_gr4'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R1_R5.pt'
chunk_size = 1e5
[]
[sigma_gr1_gr2]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr1_gr2'
dsigma_dgrad_grain1 = 'dsigma_gr1_gr2_dgrad_gr1'
dsigma_dgrad_grain2 = 'dsigma_gr1_gr2_dgrad_gr2'
grad_grain1_buffer = 'grad_gr1'
grad_grain2_buffer = 'grad_gr2'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R2_R3.pt'
chunk_size = 1e5
[]
[sigma_gr1_gr3]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr1_gr3'
dsigma_dgrad_grain1 = 'dsigma_gr1_gr3_dgrad_gr1'
dsigma_dgrad_grain2 = 'dsigma_gr1_gr3_dgrad_gr3'
grad_grain1_buffer = 'grad_gr1'
grad_grain2_buffer = 'grad_gr3'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R2_R4.pt'
chunk_size = 1e5
[]
[sigma_gr1_gr4]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr1_gr4'
dsigma_dgrad_grain1 = 'dsigma_gr1_gr4_dgrad_gr1'
dsigma_dgrad_grain2 = 'dsigma_gr1_gr4_dgrad_gr4'
grad_grain1_buffer = 'grad_gr1'
grad_grain2_buffer = 'grad_gr4'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R2_R5.pt'
chunk_size = 1e5
[]
[sigma_gr2_gr3]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr2_gr3'
dsigma_dgrad_grain1 = 'dsigma_gr2_gr3_dgrad_gr2'
dsigma_dgrad_grain2 = 'dsigma_gr2_gr3_dgrad_gr3'
grad_grain1_buffer = 'grad_gr2'
grad_grain2_buffer = 'grad_gr3'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R3_R4.pt'
chunk_size = 1e5
[]
[sigma_gr2_gr4]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr2_gr4'
dsigma_dgrad_grain1 = 'dsigma_gr2_gr4_dgrad_gr2'
dsigma_dgrad_grain2 = 'dsigma_gr2_gr4_dgrad_gr4'
grad_grain1_buffer = 'grad_gr2'
grad_grain2_buffer = 'grad_gr4'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R3_R5.pt'
chunk_size = 1e5
[]
[sigma_gr3_gr4]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr3_gr4'
dsigma_dgrad_grain1 = 'dsigma_gr3_gr4_dgrad_gr3'
dsigma_dgrad_grain2 = 'dsigma_gr3_gr4_dgrad_gr4'
grad_grain1_buffer = 'grad_gr3'
grad_grain2_buffer = 'grad_gr4'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R4_R5.pt'
chunk_size = 1e5
[]
## gamma_ij(sigma_ij)
[gamma_01]
type = ParsedCompute
buffer = 'gamma_01'
expression = 'g:=sigma_gr0_gr1/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr0_gr1'
[]
[gamma_02]
type = ParsedCompute
buffer = 'gamma_02'
expression = 'g:=sigma_gr0_gr2/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr0_gr2'
[]
[gamma_03]
type = ParsedCompute
buffer = 'gamma_03'
expression = 'g:=sigma_gr0_gr3/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr0_gr3'
[]
[gamma_04]
type = ParsedCompute
buffer = 'gamma_04'
expression = 'g:=sigma_gr0_gr4/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr0_gr4'
[]
[gamma_12]
type = ParsedCompute
buffer = 'gamma_12'
expression = 'g:=sigma_gr1_gr2/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr1_gr2'
[]
[gamma_13]
type = ParsedCompute
buffer = 'gamma_13'
expression = 'g:=sigma_gr1_gr3/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr1_gr3'
[]
[gamma_14]
type = ParsedCompute
buffer = 'gamma_14'
expression = 'g:=sigma_gr1_gr4/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr1_gr4'
[]
[gamma_23]
type = ParsedCompute
buffer = 'gamma_23'
expression = 'g:=sigma_gr2_gr3/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr2_gr3'
[]
[gamma_24]
type = ParsedCompute
buffer = 'gamma_24'
expression = 'g:=sigma_gr2_gr4/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr2_gr4'
[]
[gamma_34]
type = ParsedCompute
buffer = 'gamma_34'
expression = 'g:=sigma_gr3_gr4/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr3_gr4'
[]
## torque prefactors dgamma/dsigma * gr_i^2 * gr_j^2
[coeff_01]
type = ParsedCompute
buffer = 'coeff_01'
expression = 'g:=sigma_gr0_gr1/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr0^2 *gr1^2'
inputs = 'sigma_gr0_gr1 gr0 gr1'
[]
[coeff_02]
type = ParsedCompute
buffer = 'coeff_02'
expression = 'g:=sigma_gr0_gr2/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr0^2 *gr2^2'
inputs = 'sigma_gr0_gr2 gr0 gr2'
[]
[coeff_03]
type = ParsedCompute
buffer = 'coeff_03'
expression = 'g:=sigma_gr0_gr3/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr0^2 *gr3^2'
inputs = 'sigma_gr0_gr3 gr0 gr3'
[]
[coeff_04]
type = ParsedCompute
buffer = 'coeff_04'
expression = 'g:=sigma_gr0_gr4/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr0^2 *gr4^2'
inputs = 'sigma_gr0_gr4 gr0 gr4'
[]
[coeff_12]
type = ParsedCompute
buffer = 'coeff_12'
expression = 'g:=sigma_gr1_gr2/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr1^2 *gr2^2'
inputs = 'sigma_gr1_gr2 gr1 gr2'
[]
[coeff_13]
type = ParsedCompute
buffer = 'coeff_13'
expression = 'g:=sigma_gr1_gr3/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr1^2 *gr3^2'
inputs = 'sigma_gr1_gr3 gr1 gr3'
[]
[coeff_14]
type = ParsedCompute
buffer = 'coeff_14'
expression = 'g:=sigma_gr1_gr4/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr1^2 *gr4^2'
inputs = 'sigma_gr1_gr4 gr1 gr4'
[]
[coeff_23]
type = ParsedCompute
buffer = 'coeff_23'
expression = 'g:=sigma_gr2_gr3/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr2^2 *gr3^2'
inputs = 'sigma_gr2_gr3 gr2 gr3'
[]
[coeff_24]
type = ParsedCompute
buffer = 'coeff_24'
expression = 'g:=sigma_gr2_gr4/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr2^2 *gr4^2'
inputs = 'sigma_gr2_gr4 gr2 gr4'
[]
[coeff_34]
type = ParsedCompute
buffer = 'coeff_34'
expression = 'g:=sigma_gr3_gr4/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr3^2 *gr4^2'
inputs = 'sigma_gr3_gr4 gr3 gr4'
[]
## anisotropy torques (2 per pair)
[torque_01_gr0]
type = AnisotropyTorque
buffer = torque_01_gr0
dmu_dn = dsigma_gr0_gr1_dgrad_gr0
g = 'coeff_01'
[]
[torque_01_gr1]
type = AnisotropyTorque
buffer = torque_01_gr1
dmu_dn = dsigma_gr0_gr1_dgrad_gr1
g = 'coeff_01'
[]
[torque_02_gr0]
type = AnisotropyTorque
buffer = torque_02_gr0
dmu_dn = dsigma_gr0_gr2_dgrad_gr0
g = 'coeff_02'
[]
[torque_02_gr2]
type = AnisotropyTorque
buffer = torque_02_gr2
dmu_dn = dsigma_gr0_gr2_dgrad_gr2
g = 'coeff_02'
[]
[torque_03_gr0]
type = AnisotropyTorque
buffer = torque_03_gr0
dmu_dn = dsigma_gr0_gr3_dgrad_gr0
g = 'coeff_03'
[]
[torque_03_gr3]
type = AnisotropyTorque
buffer = torque_03_gr3
dmu_dn = dsigma_gr0_gr3_dgrad_gr3
g = 'coeff_03'
[]
[torque_04_gr0]
type = AnisotropyTorque
buffer = torque_04_gr0
dmu_dn = dsigma_gr0_gr4_dgrad_gr0
g = 'coeff_04'
[]
[torque_04_gr4]
type = AnisotropyTorque
buffer = torque_04_gr4
dmu_dn = dsigma_gr0_gr4_dgrad_gr4
g = 'coeff_04'
[]
[torque_12_gr1]
type = AnisotropyTorque
buffer = torque_12_gr1
dmu_dn = dsigma_gr1_gr2_dgrad_gr1
g = 'coeff_12'
[]
[torque_12_gr2]
type = AnisotropyTorque
buffer = torque_12_gr2
dmu_dn = dsigma_gr1_gr2_dgrad_gr2
g = 'coeff_12'
[]
[torque_13_gr1]
type = AnisotropyTorque
buffer = torque_13_gr1
dmu_dn = dsigma_gr1_gr3_dgrad_gr1
g = 'coeff_13'
[]
[torque_13_gr3]
type = AnisotropyTorque
buffer = torque_13_gr3
dmu_dn = dsigma_gr1_gr3_dgrad_gr3
g = 'coeff_13'
[]
[torque_14_gr1]
type = AnisotropyTorque
buffer = torque_14_gr1
dmu_dn = dsigma_gr1_gr4_dgrad_gr1
g = 'coeff_14'
[]
[torque_14_gr4]
type = AnisotropyTorque
buffer = torque_14_gr4
dmu_dn = dsigma_gr1_gr4_dgrad_gr4
g = 'coeff_14'
[]
[torque_23_gr2]
type = AnisotropyTorque
buffer = torque_23_gr2
dmu_dn = dsigma_gr2_gr3_dgrad_gr2
g = 'coeff_23'
[]
[torque_23_gr3]
type = AnisotropyTorque
buffer = torque_23_gr3
dmu_dn = dsigma_gr2_gr3_dgrad_gr3
g = 'coeff_23'
[]
[torque_24_gr2]
type = AnisotropyTorque
buffer = torque_24_gr2
dmu_dn = dsigma_gr2_gr4_dgrad_gr2
g = 'coeff_24'
[]
[torque_24_gr4]
type = AnisotropyTorque
buffer = torque_24_gr4
dmu_dn = dsigma_gr2_gr4_dgrad_gr4
g = 'coeff_24'
[]
[torque_34_gr3]
type = AnisotropyTorque
buffer = torque_34_gr3
dmu_dn = dsigma_gr3_gr4_dgrad_gr3
g = 'coeff_34'
[]
[torque_34_gr4]
type = AnisotropyTorque
buffer = torque_34_gr4
dmu_dn = dsigma_gr3_gr4_dgrad_gr4
g = 'coeff_34'
[]
## interpolated local GB energy and nonlinear mobility
[sigma]
type = ParsedCompute
buffer = 'sigma'
expression = '(gr0^2*gr1^2*sigma_gr0_gr1 + gr0^2*gr2^2*sigma_gr0_gr2 + gr0^2*gr3^2*sigma_gr0_gr3 + gr0^2*gr4^2*sigma_gr0_gr4 + gr1^2*gr2^2*sigma_gr1_gr2 + gr1^2*gr3^2*sigma_gr1_gr3 + gr1^2*gr4^2*sigma_gr1_gr4 + gr2^2*gr3^2*sigma_gr2_gr3 + gr2^2*gr4^2*sigma_gr2_gr4 + gr3^2*gr4^2*sigma_gr3_gr4)/(gr0^2*gr1^2 + gr0^2*gr2^2 + gr0^2*gr3^2 + gr0^2*gr4^2 + gr1^2*gr2^2 + gr1^2*gr3^2 + gr1^2*gr4^2 + gr2^2*gr3^2 + gr2^2*gr4^2 + gr3^2*gr4^2 + 1e-4)'
inputs = 'sigma_gr0_gr1 sigma_gr0_gr2 sigma_gr0_gr3 sigma_gr0_gr4 sigma_gr1_gr2 sigma_gr1_gr3 sigma_gr1_gr4 sigma_gr2_gr3 sigma_gr2_gr4 sigma_gr3_gr4 gr0 gr1 gr2 gr3 gr4'
[]
[L_NL]
type = ParsedCompute
buffer = 'L_NL'
expression = '${L} * sigma / ${gbe_max}'
inputs = 'sigma'
[]
## kappa * laplacian(gr_i) in real space (for the mobility-split correction)
[kappa_laplacian_gr0_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr0_hat
inputs = 'gr0_bar kappa_laplacian'
expression = 'gr0_bar * kappa_laplacian'
[]
[kappa_laplacian_gr1_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr1_hat
inputs = 'gr1_bar kappa_laplacian'
expression = 'gr1_bar * kappa_laplacian'
[]
[kappa_laplacian_gr2_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr2_hat
inputs = 'gr2_bar kappa_laplacian'
expression = 'gr2_bar * kappa_laplacian'
[]
[kappa_laplacian_gr3_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr3_hat
inputs = 'gr3_bar kappa_laplacian'
expression = 'gr3_bar * kappa_laplacian'
[]
[kappa_laplacian_gr4_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr4_hat
inputs = 'gr4_bar kappa_laplacian'
expression = 'gr4_bar * kappa_laplacian'
[]
[kappa_laplacian_gr0]
type = InverseFFT
buffer = kappa_laplacian_gr0
input = kappa_laplacian_gr0_hat
[]
[kappa_laplacian_gr1]
type = InverseFFT
buffer = kappa_laplacian_gr1
input = kappa_laplacian_gr1_hat
[]
[kappa_laplacian_gr2]
type = InverseFFT
buffer = kappa_laplacian_gr2
input = kappa_laplacian_gr2_hat
[]
[kappa_laplacian_gr3]
type = InverseFFT
buffer = kappa_laplacian_gr3
input = kappa_laplacian_gr3_hat
[]
[kappa_laplacian_gr4]
type = InverseFFT
buffer = kappa_laplacian_gr4
input = kappa_laplacian_gr4_hat
[]
## bulk driving forces
[gr0_bulk_term]
type = ParsedCompute
buffer = 'gr0_bulk_term'
expression = '-L_NL*${mu} * (gr0^3 - gr0 + 2*gr0*(gamma_01*gr1^2 + gamma_02*gr2^2 + gamma_03*gr3^2 + gamma_04*gr4^2) - torque_01_gr0 - torque_02_gr0 - torque_03_gr0 - torque_04_gr0) + (L_NL - ${L}) * kappa_laplacian_gr0'
inputs = 'gr0 gr1 gr2 gr3 gr4 gamma_01 gamma_02 gamma_03 gamma_04 torque_01_gr0 torque_02_gr0 torque_03_gr0 torque_04_gr0 L_NL kappa_laplacian_gr0'
[]
[gr1_bulk_term]
type = ParsedCompute
buffer = 'gr1_bulk_term'
expression = '-L_NL*${mu} * (gr1^3 - gr1 + 2*gr1*(gamma_01*gr0^2 + gamma_12*gr2^2 + gamma_13*gr3^2 + gamma_14*gr4^2) - torque_01_gr1 - torque_12_gr1 - torque_13_gr1 - torque_14_gr1) + (L_NL - ${L}) * kappa_laplacian_gr1'
inputs = 'gr0 gr1 gr2 gr3 gr4 gamma_01 gamma_12 gamma_13 gamma_14 torque_01_gr1 torque_12_gr1 torque_13_gr1 torque_14_gr1 L_NL kappa_laplacian_gr1'
[]
[gr2_bulk_term]
type = ParsedCompute
buffer = 'gr2_bulk_term'
expression = '-L_NL*${mu} * (gr2^3 - gr2 + 2*gr2*(gamma_02*gr0^2 + gamma_12*gr1^2 + gamma_23*gr3^2 + gamma_24*gr4^2) - torque_02_gr2 - torque_12_gr2 - torque_23_gr2 - torque_24_gr2) + (L_NL - ${L}) * kappa_laplacian_gr2'
inputs = 'gr0 gr1 gr2 gr3 gr4 gamma_02 gamma_12 gamma_23 gamma_24 torque_02_gr2 torque_12_gr2 torque_23_gr2 torque_24_gr2 L_NL kappa_laplacian_gr2'
[]
[gr3_bulk_term]
type = ParsedCompute
buffer = 'gr3_bulk_term'
expression = '-L_NL*${mu} * (gr3^3 - gr3 + 2*gr3*(gamma_03*gr0^2 + gamma_13*gr1^2 + gamma_23*gr2^2 + gamma_34*gr4^2) - torque_03_gr3 - torque_13_gr3 - torque_23_gr3 - torque_34_gr3) + (L_NL - ${L}) * kappa_laplacian_gr3'
inputs = 'gr0 gr1 gr2 gr3 gr4 gamma_03 gamma_13 gamma_23 gamma_34 torque_03_gr3 torque_13_gr3 torque_23_gr3 torque_34_gr3 L_NL kappa_laplacian_gr3'
[]
[gr4_bulk_term]
type = ParsedCompute
buffer = 'gr4_bulk_term'
expression = '-L_NL*${mu} * (gr4^3 - gr4 + 2*gr4*(gamma_04*gr0^2 + gamma_14*gr1^2 + gamma_24*gr2^2 + gamma_34*gr3^2) - torque_04_gr4 - torque_14_gr4 - torque_24_gr4 - torque_34_gr4) + (L_NL - ${L}) * kappa_laplacian_gr4'
inputs = 'gr0 gr1 gr2 gr3 gr4 gamma_04 gamma_14 gamma_24 gamma_34 torque_04_gr4 torque_14_gr4 torque_24_gr4 torque_34_gr4 L_NL kappa_laplacian_gr4'
[]
[NL_gr0]
type = ForwardFFT
buffer = NL_gr0
input = 'gr0_bulk_term'
[]
[NL_gr1]
type = ForwardFFT
buffer = NL_gr1
input = 'gr1_bulk_term'
[]
[NL_gr2]
type = ForwardFFT
buffer = NL_gr2
input = 'gr2_bulk_term'
[]
[NL_gr3]
type = ForwardFFT
buffer = NL_gr3
input = 'gr3_bulk_term'
[]
[NL_gr4]
type = ForwardFFT
buffer = NL_gr4
input = 'gr4_bulk_term'
[]
[NL_gr0_smooth]
type = ParsedCompute
buffer = NL_gr0_smooth
expression = 'smooth*NL_gr0'
inputs = 'smooth NL_gr0'
[]
[NL_gr1_smooth]
type = ParsedCompute
buffer = NL_gr1_smooth
expression = 'smooth*NL_gr1'
inputs = 'smooth NL_gr1'
[]
[NL_gr2_smooth]
type = ParsedCompute
buffer = NL_gr2_smooth
expression = 'smooth*NL_gr2'
inputs = 'smooth NL_gr2'
[]
[NL_gr3_smooth]
type = ParsedCompute
buffer = NL_gr3_smooth
expression = 'smooth*NL_gr3'
inputs = 'smooth NL_gr3'
[]
[NL_gr4_smooth]
type = ParsedCompute
buffer = NL_gr4_smooth
expression = 'smooth*NL_gr4'
inputs = 'smooth NL_gr4'
[]
# Properties for output
[grain_ID]
type = ParsedCompute
buffer = 'grain_ID'
expression = 'if(gr0>=max(gr1,max(gr2,max(gr3,gr4))), 0, if(gr1>=max(gr2,max(gr3,gr4)), 1, if(gr2>=max(gr3,gr4), 2, if(gr3>=gr4, 3, 4))))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[gradient_energy]
type = GradientEnergyDensity
buffer = gradient_energy
gradient_buffers = 'grad_gr0 grad_gr1 grad_gr2 grad_gr3 grad_gr4'
kappa = ${kappa}
[]
[total_energy]
type = ParsedCompute
buffer = 'total_energy'
expression = '${mu} * (${f0}) + gradient_energy'
inputs = 'gr0 gr1 gr2 gr3 gr4 gamma_01 gamma_02 gamma_03 gamma_04 gamma_12 gamma_13 gamma_14 gamma_23 gamma_24 gamma_34 gradient_energy'
[]
[]
[]
[Postprocessors]
[total_gb_energy]
type = TensorIntegralPostprocessor
buffer = total_energy
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'gr0 gr1 gr2 gr3 gr4'
reciprocal_buffer = 'gr0_bar gr1_bar gr2_bar gr3_bar gr4_bar'
linear_reciprocal = 'L_kappa_laplacian L_kappa_laplacian L_kappa_laplacian L_kappa_laplacian L_kappa_laplacian'
nonlinear_reciprocal = 'NL_gr0_smooth NL_gr1_smooth NL_gr2_smooth NL_gr3_smooth NL_gr4_smooth'
substeps = 1000
predictor_order = 1
corrector_order = 1
corrector_steps = 1
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'gr0 gr1 gr2 gr3 gr4 bnds sigma grain_ID'
output_mode = 'NODE NODE NODE NODE NODE NODE NODE CELL'
enable_hdf5 = true
transpose = true
[]
[]
[Executioner]
type = Transient
dt = 5
num_steps = 50
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(test/tests/kks/KKS_no_flux_bc.i)
#
# Kim-Kim-Suzuki with no-flux BC imposed using the smooth boundary method (SBM), solved on a 2D grid.
# Mask tensor 'psi' supplies the mask for the solve region to the system.
# Note: c is not directly conserved here - the masked value (psi > 0.0)*c will however be conserved.
#
# Constants for Initial Conditions
r = 30
l = 4.2
# Initial condition function for order parameter
eta_IC = '0.5*(1-tanh(2*(sqrt(x^2+y^2)-${r})/${l}))'
# Phase-field model parameters
kappa_eta = 5
rho_sq = 2
w = 1
M = 5
L = 5
c0_a = 0.3
c0_b = 0.7
# Expressions for switching function and bulk Gibbs energy
h_eta = 'eta^3*(6*eta^2-15*eta+10)'
F = '${h_eta}*(${rho_sq}*((c - (1-${h_eta})*(${c0_b} - ${c0_a}))-${c0_a})^2) + (1-${h_eta})*(${rho_sq}*((c + (${h_eta})*(${c0_b} - ${c0_a}))-${c0_b})^2 ) + ${w}*(eta^2)*(1-eta)^2'
[Domain]
dim = 2
nx = 20
ny = 20
xmin = -50
xmax = 50
ymin = -50
ymax = 50
# run on a CUDA device (adjust this to `cpu` if not available)
device_names = 'cpu'
# automatically create a matching mesh
mesh_mode = DUMMY
[]
[Functions]
[psi_func]
type = ParsedFunction
expression = 'if(x<x_min-${l},0,if(x>x_min+${l},1,0.5-0.5*cos(pi*(x-(x_min-${l}))/2/${l}) )) * if(x<x_max-${l},1,if(x>x_max+${l},0,0.5+0.5*cos(pi*(x-(x_max-${l}))/2/${l}) ))'
symbol_names = 'x_min x_max y_min y_max'
symbol_values = '-20 20 -50 50'
[]
[]
[TensorComputes]
[Initialize]
[c_IC]
type = ParsedCompute
buffer = c
expression = '0.6 + (${c0_a}-0.6)*${eta_IC}'
extra_symbols = 'true'
[]
[eta_IC]
type = ParsedCompute
buffer = eta
expression = '${eta_IC}'
extra_symbols = 'true'
[]
[psi_init]
type = MooseFunctionTensor
function = psi_func
buffer = psi
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
[]
[M]
type = ConstantTensor
buffer = M
real = ${M}
[]
[L]
type = ConstantTensor
buffer = L
real = ${L}
[]
[L_kappa]
type = ConstantTensor
buffer = L_kappa
real = ${fparse ${L} * ${kappa_eta} }
[]
[]
[Solve]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[etabar]
type = ForwardFFT
buffer = etabar
input = eta
[]
[mu]
type = ParsedCompute
buffer = 'mu'
expression = '${F}'
inputs = 'c eta'
derivatives = 'c'
[]
[div_J]
type = ReciprocalMatDiffusion
buffer = 'div_J'
chemical_potential = mu
mobility = M
psi = psi
[]
[domega_chem_deta]
type = ParsedCompute
buffer = 'domega_chem_deta'
expression = '${F} - mu*c'
inputs = 'mu c eta'
derivatives = 'eta'
[]
[AC_bulk]
type = ReciprocalAllenCahn
buffer = AC_bulk
dF_chem_deta = domega_chem_deta
L = L
psi = psi
[]
[kappa_grad_eta]
type = ReciprocalMatDiffusion
buffer = 'kappa_grad_eta'
chemical_potential = 'eta'
mobility = 'L_kappa'
psi = psi
[]
[AC_bar]
type = ParsedCompute
buffer = AC_bar
expression = 'kappa_grad_eta + AC_bulk'
inputs = 'AC_bulk kappa_grad_eta'
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'c eta'
reciprocal_buffer = 'cbar etabar'
linear_reciprocal = 'zero zero'
nonlinear_reciprocal = 'div_J AC_bar'
substeps = 1e3
predictor_order = 3
[]
[Postprocessors]
[total_C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'INITIAL TIMESTEP_END'
[]
[total_eta]
type = TensorIntegralPostprocessor
buffer = eta
execute_on = 'INITIAL TIMESTEP_END'
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'eta c mu psi'
enable_hdf5 = true
transpose = false
[]
[]
[Executioner]
type = Transient
dt = 0.1
num_steps = 10
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(test/tests/real_space/neumann_conservation.i)
# Zero-flux Neumann boundary condition: pure diffusion with zero flux on the X faces
# and periodic Y, from a non-uniform initial condition. The total integral of u must
# be conserved to near machine precision while u relaxes to its mean.
[Domain]
dim = 2
nx = 20
ny = 8
parallel_mode = REAL_SPACE
periodic_directions = 'Y'
xmin = 0
xmax = 1
ymin = -1
ymax = 1
[]
[TensorComputes]
[Initialize]
[u_ic]
type = ParsedCompute
buffer = u
# non-uniform in x and y, so diffusion moves mass internally
expression = '1 + sin(2 * pi * x) + 0.3 * cos(pi * y)'
extra_symbols = true
[]
[]
[BCs]
[left]
type = TensorNeumannBC
variable = u
boundary = left
flux = 0
[]
[right]
type = TensorNeumannBC
variable = u
boundary = right
flux = 0
[]
[]
[Solve]
[dt]
type = FiniteDifferenceLaplacian
input = u
buffer = dudt
[]
[]
[]
[TensorSolver]
type = RealSpaceForwardEuler
buffer = u
time_derivative = dudt
substeps = 1000
[]
[Postprocessors]
[mass]
type = TensorIntegralPostprocessor
buffer = u
execute_on = 'INITIAL TIMESTEP_END'
[]
[]
[Executioner]
type = Transient
# same grid and CFL margin as dirichlet_linear.i
dt = 1
num_steps = 4
[]
[Outputs]
[out]
type = CSV
[]
[]
(examples/anisotropic_grain_growth/spherical_grain_Ni.i)
interface_width = 1.6
r0 = 7.5
# Ni
gbe_max = '${units 0.8797226 J/m^2}'
L = '${fparse 1.0 * 1.6 / ${interface_width}}'
g_gamma0 = '${fparse sqrt(2) / 3}' # g(gamma=1.5)
f0_gamma0 = ${fparse 1/8}
kappa = '${fparse gbe_max * interface_width * sqrt(f0_gamma0) / g_gamma0}'
mu = '${fparse gbe_max / (g_gamma0 * interface_width * sqrt(f0_gamma0))}'
g_to_gamma_func = '(1.0/(-3.0944 * g^8 -1.8169*g^6 + 10.323 * g^4 - 8.1819*g^2 + 2.0033))'
dgamma_dsigma = '(g * (24.7552*g^6 + 10.9014*g^4 - 41.292*g^2 + 16.3638) / (-3.0944*g^8 - 1.8169*g^6 + 10.323*g^4 - 8.1819*g^2 + 2.0033)^2 / sqrt(${kappa} * ${mu}))'
f0 = '((gr0^4/4 - gr0^2/2) + (gr1^4/4 - gr1^2/2) + gamma_01*gr0^2*gr1^2 + 0.25)'
[Domain]
dim = 3
nx = 100
ny = 100
nz = 100
xmax = 20
ymax = 20
zmax = 20
mesh_mode = DUMMY
[]
[TensorComputes]
[Initialize]
[gr0]
type = ParsedCompute
buffer = 'gr0'
extra_symbols = 'true'
expression = 'radius:=sqrt((x-${Domain/xmax}/2)^2+(y-${Domain/ymax}/2)^2+(z-${Domain/zmax}/2)^2);0.5 - 0.5*tanh(2*(radius-${r0})/${interface_width})'
[]
[gr1]
type = ParsedCompute
buffer = 'gr1'
extra_symbols = 'true'
expression = 'radius:=sqrt((x-${Domain/xmax}/2)^2+(y-${Domain/ymax}/2)^2+(z-${Domain/zmax}/2)^2);0.5 + 0.5*tanh(2*(radius-${r0})/${interface_width})'
[]
[L_kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = L_kappa_laplacian
factor = ${fparse ${L} * ${kappa}}
[]
[kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = kappa_laplacian
factor = '${kappa}'
[]
[smooth]
type = DeAliasingTensor
method = HOULI
buffer = smooth
[]
[]
[Solve]
## FFT
[gr0_bar]
type = ForwardFFT
buffer = gr0_bar
input = gr0
[]
[gr1_bar]
type = ForwardFFT
buffer = gr1_bar
input = gr1
[]
[gr0_bar_smooth]
type = ParsedCompute
buffer = gr0_bar_smooth
expression = 'gr0_bar * smooth'
inputs = 'gr0_bar smooth'
[]
[gr1_bar_smooth]
type = ParsedCompute
buffer = gr1_bar_smooth
expression = 'gr1_bar * smooth'
inputs = 'gr1_bar smooth'
[]
# Gradients
[grad_gr0]
type = GradientVector
buffer = grad_gr0
input = gr0_bar_smooth
input_is_reciprocal = true
[]
[grad_gr1]
type = GradientVector
buffer = grad_gr1
input = gr1_bar_smooth
input_is_reciprocal = true
[]
# Get interface energy
[sigma_gr0_gr1]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr0_gr1'
dsigma_dgrad_grain1 = 'dsigma_gr0_gr1_dgrad_gr0'
dsigma_dgrad_grain2 = 'dsigma_gr0_gr1_dgrad_gr1'
grad_grain1_buffer = 'grad_gr0'
grad_grain2_buffer = 'grad_gr1'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/Ni_R1_R3.pt'
chunk_size = 1e5
[]
[gamma_01]
type = ParsedCompute
buffer = 'gamma_01'
expression = 'g:=sigma_gr0_gr1/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr0_gr1'
[]
[coeff_01]
type = ParsedCompute
buffer = 'coeff_01'
expression = 'g:=sigma_gr0_gr1/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr0^2 *gr1^2'
inputs = 'sigma_gr0_gr1 gr0 gr1'
[]
[torque_01_gr0]
type = AnisotropyTorque
buffer = torque_01_gr0
dmu_dn = dsigma_gr0_gr1_dgrad_gr0
g = 'coeff_01'
[]
[torque_01_gr1]
type = AnisotropyTorque
buffer = torque_01_gr1
dmu_dn = dsigma_gr0_gr1_dgrad_gr1
g = 'coeff_01'
[]
[kappa_laplacian_gr0_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr0_hat
inputs = 'gr0_bar kappa_laplacian'
expression = 'gr0_bar * kappa_laplacian'
[]
[kappa_laplacian_gr1_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr1_hat
inputs = 'gr1_bar kappa_laplacian'
expression = 'gr1_bar * kappa_laplacian'
[]
[kappa_laplacian_gr0]
type = InverseFFT
buffer = kappa_laplacian_gr0
input = kappa_laplacian_gr0_hat
[]
[kappa_laplacian_gr1]
type = InverseFFT
buffer = kappa_laplacian_gr1
input = kappa_laplacian_gr1_hat
[]
[gr0_bulk_term]
type = ParsedCompute
buffer = 'gr0_bulk_term'
expression = 'L_NL:=${L}*(sigma_gr0_gr1)/${gbe_max};-L_NL*${mu} * (gr0^3 - gr0 + 2*gr0*(gamma_01*gr1^2) - torque_01_gr0) + (L_NL - ${L})*kappa_laplacian_gr0'
inputs = 'gr0 gr1 gamma_01 torque_01_gr0 sigma_gr0_gr1 kappa_laplacian_gr0'
[]
[gr1_bulk_term]
type = ParsedCompute
buffer = 'gr1_bulk_term'
expression = 'L_NL:=${L}*(sigma_gr0_gr1)/${gbe_max};-L_NL*${mu} * (gr1^3 - gr1 + 2*gr1*(gamma_01*gr0^2) - torque_01_gr1) + (L_NL - ${L})*kappa_laplacian_gr1'
inputs = 'gr0 gr1 gamma_01 torque_01_gr1 sigma_gr0_gr1 kappa_laplacian_gr1'
[]
## build non-linear terms and smooth them
[NL_gr0]
type = ForwardFFT
buffer = NL_gr0
input = 'gr0_bulk_term'
[]
[NL_gr1]
type = ForwardFFT
buffer = NL_gr1
input = 'gr1_bulk_term'
[]
[NL_gr0_smooth]
type = ParsedCompute
buffer = NL_gr0_smooth
expression = 'smooth*NL_gr0'
inputs = 'smooth NL_gr0'
[]
[NL_gr1_smooth]
type = ParsedCompute
buffer = NL_gr1_smooth
expression = 'smooth*NL_gr1'
inputs = 'smooth NL_gr1'
[]
# Properties for output
[sigma]
type = ParsedCompute
buffer = 'sigma'
expression = 'gr0^2*gr1^2*sigma_gr0_gr1'
inputs = 'sigma_gr0_gr1 gr0 gr1'
[]
[gradient_energy]
type = GradientEnergyDensity
buffer = gradient_energy
gradient_buffers = 'grad_gr0 grad_gr1'
kappa = ${kappa}
[]
[total_energy]
type = ParsedCompute
buffer = 'total_energy'
expression = '${mu} * (${f0}) + gradient_energy'
inputs = 'gr0 gr1 gamma_01 gradient_energy'
[]
[]
[]
[Postprocessors]
[total_gb_energy]
type = TensorIntegralPostprocessor
buffer = total_energy
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'gr0 gr1'
reciprocal_buffer = 'gr0_bar gr1_bar'
linear_reciprocal = 'L_kappa_laplacian L_kappa_laplacian'
nonlinear_reciprocal = 'NL_gr0_smooth NL_gr1_smooth'
substeps = 100
predictor_order = 2
corrector_order = 1
corrector_steps = 2
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'gr0 gr1 sigma_gr0_gr1'
output_mode = 'NODE NODE NODE'
enable_hdf5 = true
transpose = false
[]
[]
[Executioner]
type = Transient
dt = 0.1
num_steps = 200
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(test/tests/anisotropic_grain_growth/sigma3_circular_grain.i)
interface_width = 2.0
r0 = 3
gbe_max = '${units 0.8797226 J/m^2}'
L = '${fparse 1.0 * 1.6 / ${interface_width}}'
g_gamma0 = '${fparse sqrt(2) / 3}' # g(gamma=1.5)
f0_gamma0 = ${fparse 1/8}
kappa = '${fparse gbe_max * interface_width * sqrt(f0_gamma0) / g_gamma0}'
mu = '${fparse gbe_max / (g_gamma0 * interface_width * sqrt(f0_gamma0))}'
g_to_gamma_func = '(1.0/(-3.0944 * g^8 -1.8169*g^6 + 10.323 * g^4 - 8.1819*g^2 + 2.0033))'
dgamma_dsigma = '(g * (24.7552*g^6 + 10.9014*g^4 - 41.292*g^2 + 16.3638) / (-3.0944*g^8 - 1.8169*g^6 + 10.323*g^4 - 8.1819*g^2 + 2.0033)^2 / sqrt(${kappa} * ${mu}))'
f0 = '((gr0^4/4 - gr0^2/2) + (gr1^4/4 - gr1^2/2) + gamma_01*gr0^2*gr1^2 + 0.25)'
[Domain]
dim = 2
nx = 32
ny = 32
xmax = 8
ymax = 8
mesh_mode = DUMMY
floating_precision = SINGLE
[]
[TensorComputes]
[Initialize]
[gr0]
type = ParsedCompute
buffer = 'gr0'
extra_symbols = 'true'
expression = 'radius:=sqrt((x-${Domain/xmax}/2)^2+(y-${Domain/ymax}/2)^2);0.5 - 0.5*tanh(2*(radius-${r0})/${interface_width})'
[]
[gr1]
type = ParsedCompute
buffer = 'gr1'
extra_symbols = 'true'
expression = 'radius:=sqrt((x-${Domain/xmax}/2)^2+(y-${Domain/ymax}/2)^2);0.5 + 0.5*tanh(2*(radius-${r0})/${interface_width})'
[]
[L_kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = L_kappa_laplacian
factor = ${fparse ${L} * ${kappa}}
[]
[kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = kappa_laplacian
factor = '${kappa}'
[]
[smooth]
type = DeAliasingTensor
method = HOULI
buffer = smooth
[]
[]
[Solve]
## FFT
[gr0_bar]
type = ForwardFFT
buffer = gr0_bar
input = gr0
[]
[gr1_bar]
type = ForwardFFT
buffer = gr1_bar
input = gr1
[]
# Gradients
[grad_gr0]
type = GradientVector
buffer = grad_gr0
input = gr0_bar
input_is_reciprocal = true
[]
[grad_gr1]
type = GradientVector
buffer = grad_gr1
input = gr1_bar
input_is_reciprocal = true
[]
# Get interface energy
[sigma_gr0_gr1]
type = PairwiseAnisotropicGBEnergy
buffer = 'sigma_gr0_gr1'
dsigma_dgrad_grain1 = 'dsigma_gr0_gr1_dgrad_gr0'
dsigma_dgrad_grain2 = 'dsigma_gr0_gr1_dgrad_gr1'
grad_grain1_buffer = 'grad_gr0'
grad_grain2_buffer = 'grad_gr1'
interface_width = '${interface_width}'
libtorch_model_file = 'marlin:anisotropic_gb_energy/gb_energy_hull_2d.pt'
chunk_size = 256
[]
[gamma_01]
type = ParsedCompute
buffer = 'gamma_01'
expression = 'g:=sigma_gr0_gr1/sqrt(${kappa}*${mu});${g_to_gamma_func}'
inputs = 'sigma_gr0_gr1'
[]
[coeff_01]
type = ParsedCompute
buffer = 'coeff_01'
expression = 'g:=sigma_gr0_gr1/sqrt(${kappa}*${mu});${dgamma_dsigma} * gr0^2 *gr1^2'
inputs = 'sigma_gr0_gr1 gr0 gr1'
[]
[torque_01_gr0]
type = AnisotropyTorque
buffer = torque_01_gr0
dmu_dn = dsigma_gr0_gr1_dgrad_gr0
g = 'coeff_01'
[]
[torque_01_gr1]
type = AnisotropyTorque
buffer = torque_01_gr1
dmu_dn = dsigma_gr0_gr1_dgrad_gr1
g = 'coeff_01'
[]
[kappa_laplacian_gr0_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr0_hat
inputs = 'gr0_bar kappa_laplacian'
expression = 'gr0_bar * kappa_laplacian'
[]
[kappa_laplacian_gr1_hat]
type = ParsedCompute
buffer = kappa_laplacian_gr1_hat
inputs = 'gr1_bar kappa_laplacian'
expression = 'gr1_bar * kappa_laplacian'
[]
[kappa_laplacian_gr0]
type = InverseFFT
buffer = kappa_laplacian_gr0
input = kappa_laplacian_gr0_hat
[]
[kappa_laplacian_gr1]
type = InverseFFT
buffer = kappa_laplacian_gr1
input = kappa_laplacian_gr1_hat
[]
[gr0_bulk_term]
type = ParsedCompute
buffer = 'gr0_bulk_term'
expression = 'L_NL:=${L}*(sigma_gr0_gr1)/${gbe_max};-L_NL*${mu} * (gr0^3 - gr0 + 2*gr0*(gamma_01*gr1^2) - torque_01_gr0) + (L_NL - ${L})*kappa_laplacian_gr0'
inputs = 'gr0 gr1 gamma_01 torque_01_gr0 sigma_gr0_gr1 kappa_laplacian_gr0'
[]
[gr1_bulk_term]
type = ParsedCompute
buffer = 'gr1_bulk_term'
expression = 'L_NL:=${L}*(sigma_gr0_gr1)/${gbe_max};-L_NL*${mu} * (gr1^3 - gr1 + 2*gr1*(gamma_01*gr0^2) - torque_01_gr1) + (L_NL - ${L})*kappa_laplacian_gr1'
inputs = 'gr0 gr1 gamma_01 torque_01_gr1 sigma_gr0_gr1 kappa_laplacian_gr1'
[]
## build non-linear terms and smooth them
[NL_gr0]
type = ForwardFFT
buffer = NL_gr0
input = 'gr0_bulk_term'
[]
[NL_gr1]
type = ForwardFFT
buffer = NL_gr1
input = 'gr1_bulk_term'
[]
[NL_gr0_smooth]
type = ParsedCompute
buffer = NL_gr0_smooth
expression = 'smooth*NL_gr0'
inputs = 'smooth NL_gr0'
[]
[NL_gr1_smooth]
type = ParsedCompute
buffer = NL_gr1_smooth
expression = 'smooth*NL_gr1'
inputs = 'smooth NL_gr1'
[]
# Properties for output
[sigma]
type = ParsedCompute
buffer = 'sigma'
expression = 'gr0^2*gr1^2*sigma_gr0_gr1'
inputs = 'sigma_gr0_gr1 gr0 gr1'
[]
[gradient_energy]
type = GradientEnergyDensity
buffer = gradient_energy
gradient_buffers = 'grad_gr0 grad_gr1'
kappa = ${kappa}
[]
[total_energy]
type = ParsedCompute
buffer = 'total_energy'
expression = '${mu} * (${f0}) + gradient_energy'
inputs = 'gr0 gr1 gamma_01 gradient_energy'
[]
[]
[]
[Postprocessors]
[total_gb_energy]
type = TensorIntegralPostprocessor
buffer = total_energy
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'gr0 gr1'
reciprocal_buffer = 'gr0_bar gr1_bar'
linear_reciprocal = 'L_kappa_laplacian L_kappa_laplacian'
nonlinear_reciprocal = 'NL_gr0_smooth NL_gr1_smooth'
substeps = 1e2
predictor_order = 1
corrector_order = 1
corrector_steps = 1
[]
[TensorOutputs]
active = ''
[xdmf]
type = XDMFTensorOutput
buffer = 'gr0 gr1 sigma_gr0_gr1 sigma total_energy'
output_mode = 'NODE NODE NODE NODE NODE'
enable_hdf5 = true
transpose = false
[]
[]
[Executioner]
type = Transient
dt = 1
num_steps = 2
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(test/tests/tensor_compute/parallel_roundtrip_3d.i)
[Domain]
# Test parallel FFT round-trip with slab decomposition in 3D
device_names = "cpu cpu cpu"
device_weights = "1 1 1"
dim = 3
nx = 64
ny = 64
nz = 64
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
zmax = ${fparse pi*4}
[]
[TensorBuffers]
[eta_gold]
[]
[eta]
[]
[eta_bar]
[]
[eta_roundtrip]
[]
[diff]
[]
[zero]
[]
[]
[TensorComputes]
[Initialize]
[eta_gold]
type = ParsedCompute
buffer = eta_gold
expression = 'sin(x)+sin(y)+sin(z)+cos(2*x)*sin(3*y)*cos(z)'
extra_symbols = true
[]
[eta]
type = ParsedCompute
buffer = eta
expression = eta_gold
inputs = eta_gold
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
real = 0
imaginary = 0
[]
[]
[Solve]
# Test: eta -> FFT -> iFFT -> eta_roundtrip
# eta_roundtrip should equal eta (within numerical precision)
[eta_bar]
type = ForwardFFT
buffer = eta_bar
input = eta
[]
[eta_roundtrip]
type = InverseFFT
buffer = eta_roundtrip
input = eta_bar
[]
[]
[Postprocess]
[diff]
type = ParsedCompute
buffer = diff
expression = 'abs(eta - eta_roundtrip) + abs(eta - eta_gold)'
inputs = 'eta eta_roundtrip eta_gold'
[]
[]
[]
[Postprocessors]
[max_error]
type = TensorExtremeValuePostprocessor
buffer = diff
value_type = MAX
[]
[l2_error]
type = TensorIntegralPostprocessor
buffer = diff
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = eta
reciprocal_buffer = eta_bar
linear_reciprocal = zero
nonlinear_reciprocal = zero
[]
[TensorOutputs]
[eta]
type = XDMFTensorOutput
buffer = 'eta'
output_mode = 'CELL'
enable_hdf5 = true
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(test/tests/gradient/gradient_square.i)
[Domain]
dim = 3
nx = 40
ny = 40
nz = 40
xmax = ${fparse pi*2}
ymax = ${fparse pi*4}
zmax = ${fparse pi*6}
mesh_mode = DUMMY
device_names = cpu
[]
[TensorBuffers]
[s]
[]
[grad_sq]
[]
[c2]
[]
[diff]
[]
[]
[TensorComputes]
[Initialize]
[sin]
type = ParsedCompute
buffer = s
extra_symbols = true
expression = 'sin(x)+sin(y)+sin(z)'
[]
[cos2]
type = ParsedCompute
buffer = c2
extra_symbols = true
expression = 'cos(x)^2+cos(y)^2+cos(z)^2'
[]
[grad_sq]
type = FFTGradientSquare
buffer = grad_sq
input = s
[]
[diff]
type = ParsedCompute
buffer = diff
inputs = 'grad_sq c2'
expression = 'abs(grad_sq - c2)'
[]
[]
[]
[Postprocessors]
[diff]
type = TensorIntegralPostprocessor
buffer = diff
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1
[]
[Outputs]
csv = true
[]
(test/tests/tensor_compute/parallel_roundtrip.i)
[Domain]
# Test parallel FFT round-trip with slab decomposition
device_names = "cpu cpu cpu"
device_weights = "1 1 1"
parallel_mode = FFT_SLAB
dim = 2
nx = 128
ny = 128
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
[]
[TensorBuffers]
[eta_gold]
[]
[eta]
[]
[eta_bar]
[]
[eta_roundtrip]
[]
[diff]
[]
[zero]
[]
[]
[TensorComputes]
[Initialize]
[eta_gold]
type = ParsedCompute
buffer = eta_gold
expression = 'sin(x)+sin(y)+cos(2*x)*sin(3*y)'
extra_symbols = true
[]
[eta]
type = ParsedCompute
buffer = eta
expression = eta_gold
inputs = eta_gold
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
real = 0
imaginary = 0
[]
[]
[Solve]
# Test: eta -> FFT -> iFFT -> eta_roundtrip
# eta_roundtrip should equal eta (within numerical precision)
[eta_bar]
type = ForwardFFT
buffer = eta_bar
input = eta
[]
[eta_roundtrip]
type = InverseFFT
buffer = eta_roundtrip
input = eta_bar
[]
[]
[Postprocess]
[diff]
type = ParsedCompute
buffer = diff
expression = 'abs(eta - eta_roundtrip) + abs(eta - eta_gold)'
inputs = 'eta eta_roundtrip eta_gold'
[]
[]
[]
[Postprocessors]
[max_error]
type = TensorExtremeValuePostprocessor
buffer = diff
value_type = MAX
[]
[l2_error]
type = TensorIntegralPostprocessor
buffer = diff
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = eta
reciprocal_buffer = eta_bar
linear_reciprocal = zero
nonlinear_reciprocal = zero
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(test/tests/real_space/diffusion.i)
[Domain]
dim = 2
nx = 80
ny = 60
parallel_mode = REAL_SPACE
periodic_directions = 'X Y'
xmin = -1
ymin = -1
xmax = 1
ymax = 1
[]
[TensorComputes]
[Initialize]
[u_ic]
type = ParsedCompute
buffer = u
expression = 'exp((-x^2-y^2)*100)'
extra_symbols = true
[]
[]
[Solve]
[dt]
type = FiniteDifferenceLaplacian
input = u
buffer = dudt
[]
[]
[]
[TensorSolver]
type = RealSpaceForwardEuler
buffer = u
time_derivative = dudt
substeps = 100
[]
[Postprocessors]
[max_u]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MAX
execute_on = 'INITIAL TIMESTEP_END'
[]
[U]
type = TensorIntegralPostprocessor
buffer = u
execute_on = 'INITIAL TIMESTEP_END'
[]
[]
[TensorOutputs]
# active = ''
[u]
type = XDMFTensorOutput
buffer = 'u dudt'
enable_hdf5 = true
[]
[]
[Executioner]
type = Transient
dt = 1e-2
num_steps = 100
[]
[Outputs]
[out]
type = CSV
[]
[]
(test/tests/real_space/deep_ghost_faces.i)
# A stencil reaching four cells across a face (the 5-point biharmonic) with Neumann faces in x:
# its four ghost layers are the even mirror of the owned cells about the face. The result on
# 0 < x < 16 then equals the same stencil on the periodic domain 0 < x < 32 of the mirrored field
# (deep_ghost_periodic.i), which needs no ghost fill at a face, to round-off.
#
# u = exp(cos(pi x / 16)) sin(2 pi y / 8) is even about x = 0 and x = 16. With Dirichlet faces and
# u_ic = sin(pi x / 16) exp(cos(2 pi y / 8)), odd about both, the ghosts are the odd mirror.
u_ic = 'exp(cos(pi*x/16))*sin(2*pi*y/8)'
[Domain]
dim = 2
nx = 16
ny = 8
xmax = 16
ymax = 8
parallel_mode = REAL_SPACE
periodic_directions = 'Y'
[]
[TensorBuffers]
[u]
[]
[bih]
[]
[bih_sq]
[]
[]
[TensorComputes]
[Initialize]
[u_ic]
type = ParsedCompute
buffer = u
extra_symbols = true
expression = ${u_ic}
[]
[]
[BCs]
[left]
type = TensorNeumannBC
variable = u
boundary = left
[]
[right]
type = TensorNeumannBC
variable = u
boundary = right
[]
[]
[Postprocess]
[bih]
type = FiniteDifferenceBiharmonic
buffer = bih
input = u
stencil_width = 5
[]
[bih_sq]
type = ParsedCompute
buffer = bih_sq
expression = 'bih^2'
inputs = bih
[]
[]
[]
[Postprocessors]
[integral_bih_sq]
type = TensorIntegralPostprocessor
buffer = bih_sq
[]
[max_bih]
type = TensorExtremeValuePostprocessor
buffer = bih
value_type = MAX
[]
[min_bih]
type = TensorExtremeValuePostprocessor
buffer = bih
value_type = MIN
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1
[]
[Outputs]
csv = true
[]
(test/tests/solvers/etdrk4_diffusion.i)
D = 0.05
k = 1.0
ss = 1
dt = '${units 10 s }'
[Domain]
dim = 1
nx = 64
xmax = '${fparse 2*pi}'
mesh_mode = DUMMY
[]
[TensorComputes]
[Initialize]
[u0]
type = ParsedCompute
buffer = u0
extra_symbols = true
expression = 'sin(${k}*x)'
[]
[u]
type = ParsedCompute
buffer = u
inputs = u0
expression = 'u0'
[]
[L]
type = ReciprocalLaplacianFactor
factor = ${D}
buffer = L
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
[]
[]
[Solve]
[u_bar]
type = ForwardFFT
buffer = u_bar
input = u
[]
[u_exact]
type = ParsedCompute
buffer = u_exact
inputs = u0
extra_symbols = true
expression = 'u0*exp(-${D}*${k}^2*t)'
[]
[u_diff_sq]
type = ParsedCompute
buffer = u_diff_sq
inputs = 'u u_exact'
expression = '(u - u_exact)^2'
[]
[]
[]
[TensorSolver]
type = ETDRK4Solver
buffer = 'u'
reciprocal_buffer = 'u_bar'
linear_reciprocal = 'L'
nonlinear_reciprocal = 'zero'
substeps = ${ss}
[]
[Problem]
type = TensorProblem
[]
[Postprocessors]
[mse]
type = TensorIntegralPostprocessor
buffer = u_diff_sq
[]
[rmse]
type = ParsedPostprocessor
expression = 'sqrt(mse)'
pp_names = 'mse'
pp_symbols = 'mse'
[]
[]
[Executioner]
type = Transient
num_steps = 10
dt = ${dt}
[]
[Outputs]
file_base = etdrk4_diffusion_rmse
csv = true
[]
(benchmarks/02_oswald_ripening/2a_broyden.i)
[Domain]
dim = 2
nx = 200
ny = 200
xmax = 200
ymax = 200
device_names = 'cuda:0'
mesh_mode = DOMAIN
[]
fchem='fa:=rho^2*(c-ca)^2;
fb:=rho^2*(cb-c)^2;
h:=n1^3*(6*n1^2-15*n1+10) +
n2^3*(6*n2^2-15*n2+10) +
n3^3*(6*n3^2-15*n3+10) +
n4^3*(6*n4^2-15*n4+10);
g:=n1^2*(1-n1)^2 +
n2^2*(1-n2)^2 +
n3^2*(1-n3)^2 +
n4^2*(1-n4)^2 +
alpha*(
n1^2*n2^2 + n1^2*n3^2 + n1^2*n4^2 +
n2^2*n1^2 + n2^2*n3^2 + n2^2*n4^2 +
n3^2*n1^2 + n3^2*n2^2 + n3^2*n4^2 +
n4^2*n1^2 + n4^2*n2^2 + n4^2*n3^2);
(fa*(1-h) + fb*h + w*g)'
nic = 'epsilon*(cos((0.01*idx)*x-4)*cos((0.007+0.01*idx)*y)
+cos((0.11+0.01*idx)*x)*cos((0.11+0.01*idx)*y)
+psi*(cos((0.046+0.001*idx)*x+(0.0405+0.001*idx)*y)
*cos((0.031+0.001*idx)*x-(0.004+0.001*idx)*y))^2)^2'
cnames = 'rho ca cb alpha w L M'
cvalues= 'sqrt(2) 0.3 0.7 5 1 5 5'
[TensorBuffers]
# variables
[c]
map_to_aux_variable = c
[]
[n1]
[]
[n2]
[]
[n3]
[]
[n4]
[]
[c_bar]
[]
[n1_bar]
[]
[n2_bar]
[]
[n3_bar]
[]
[n4_bar]
[]
[mu_c]
# map_to_aux_variable = mu
[]
[mu_n1]
[]
[mu_n2]
[]
[mu_n3]
[]
[mu_n4]
[]
[mu_c_bar]
[]
[mu_n1_bar]
[]
[mu_n2_bar]
[]
[mu_n3_bar]
[]
[mu_n4_bar]
[]
[Mbar_mu_c_bar]
[]
# constant tensors
[Lbar] # FFT(M*laplacian)
[]
[MkappaL2bar] # FFT(-M*kappa*laplacian^2)
[]
[kappaLbar] # FFT(L*kappa*laplacian)
[]
# postprocessing
[F]
[]
[Fgrad_c]
[]
[Fgrad_n1]
[]
[Fgrad_n2]
[]
[Fgrad_n3]
[]
[Fgrad_n4]
[]
[bnds]
map_to_aux_variable = bnds
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Lbar]
type = ReciprocalLaplacianFactor
# Mobility is pulled into the chemical potential below
buffer = Lbar
[]
[MkappaL2bar]
type = ReciprocalLaplacianSquareFactor
factor = -15 # -kappa_c*M
buffer = MkappaL2bar
[]
[kappaLbar]
type = ReciprocalLaplacianFactor
buffer = kappaLbar
factor = 15 # kappa_ni*L
[]
[n1]
type = ParsedCompute
buffer = n1
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 1 0.1 1.5'
[]
[n2]
type = ParsedCompute
buffer = n2
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 2 0.1 1.5'
[]
[n3]
type = ParsedCompute
buffer = n3
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 3 0.1 1.5'
[]
[n4]
type = ParsedCompute
buffer = n4
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 4 0.1 1.5'
[]
[]
[Solve]
[mu_c]
type = ParsedCompute
buffer = mu_c
expression = '${fchem}*M'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = c
inputs = 'c n1 n2 n3 n4'
[]
[mu_n1]
type = ParsedCompute
buffer = mu_n1
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n1
inputs = 'c n1 n2 n3 n4'
[]
[mu_n2]
type = ParsedCompute
buffer = mu_n2
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n2
inputs = 'c n1 n2 n3 n4'
[]
[mu_n3]
type = ParsedCompute
buffer = mu_n3
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n3
inputs = 'c n1 n2 n3 n4'
[]
[mu_n4]
type = ParsedCompute
buffer = mu_n4
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n4
inputs = 'c n1 n2 n3 n4'
[]
[mu_c_bar]
type = ForwardFFT
buffer = mu_c_bar
input = mu_c
[]
[mu_n1_bar]
type = ForwardFFT
buffer = mu_n1_bar
input = mu_n1
[]
[mu_n2_bar]
type = ForwardFFT
buffer = mu_n2_bar
input = mu_n2
[]
[mu_n3_bar]
type = ForwardFFT
buffer = mu_n3_bar
input = mu_n3
[]
[mu_n4_bar]
type = ForwardFFT
buffer = mu_n4_bar
input = mu_n4
[]
[Mbar_mu_c_bar]
type = ParsedCompute
buffer = Mbar_mu_c_bar
expression = 'Lbar*mu_c_bar'
inputs = 'Lbar mu_c_bar'
[]
[c_bar]
type = ForwardFFT
buffer = c_bar
input = c
[]
[n1_bar]
type = ForwardFFT
buffer = n1_bar
input = n1
[]
[n2_bar]
type = ForwardFFT
buffer = n2_bar
input = n2
[]
[n3_bar]
type = ForwardFFT
buffer = n3_bar
input = n3
[]
[n4_bar]
type = ForwardFFT
buffer = n4_bar
input = n4
[]
[]
[Postprocess]
[Fgrad_c]
type = FFTGradientSquare
buffer = Fgrad_c
input = c
factor = 1.5 # kappa/2
[]
[Fgrad_n1]
type = FFTGradientSquare
buffer = Fgrad_n1
input = n1
factor = 1.5 # kappa/2
[]
[Fgrad_n2]
type = FFTGradientSquare
buffer = Fgrad_n2
input = n2
factor = 1.5 # kappa/2
[]
[Fgrad_n3]
type = FFTGradientSquare
buffer = Fgrad_n3
input = n3
factor = 1.5 # kappa/2
[]
[Fgrad_n4]
type = FFTGradientSquare
buffer = Fgrad_n4
input = n4
factor = 1.5 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = '${fchem} + Fgrad_c + Fgrad_n1 + Fgrad_n2 + Fgrad_n3 + Fgrad_n4'
constant_names = ${cnames}
constant_expressions = ${cvalues}
inputs = 'c n1 n2 n3 n4 Fgrad_c Fgrad_n1 Fgrad_n2 Fgrad_n3 Fgrad_n4'
[]
[bnds]
type = ParsedCompute
buffer = bnds
expression = 'n1^2 + n2^2 + n3^2 + n4^2'
inputs = 'n1 n2 n3 n4'
[]
[]
[]
[TensorSolver]
type = BroydenSolver
substeps = 10
max_iterations = 1000
damping = 0.5
relative_tolerance = 1e-6
absolute_tolerance = 1e-5
buffer = 'c n1 n2 n3 n4'
dt_epsilon = 1e-5
reciprocal_buffer = 'c_bar n1_bar n2_bar n3_bar n4_bar'
linear_reciprocal = 'MkappaL2bar kappaLbar kappaLbar kappaLbar kappaLbar'
nonlinear_reciprocal = 'Mbar_mu_c_bar mu_n1_bar mu_n2_bar mu_n3_bar mu_n4_bar'
# verbose = true
[]
[AuxVariables]
[c]
[]
[bnds]
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
# num_steps = 2
end_time = 1e+5
[TimeStepper]
type = TensorSolveIterationAdaptiveDT
dt = 1e-4
max_iterations = 500
min_iterations = 100
growth_factor = 1.1
[]
[]
[Outputs]
exodus = true
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/tensor_compute/backandforth.i)
[Domain]
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
mesh_mode = DUMMY
[]
[TensorBuffers]
[eta_gold]
[]
[eta]
[]
[eta_bar]
[]
[eta2]
[]
[zero]
[]
[diff]
[]
[]
[TensorComputes]
[Initialize]
[eta_gold]
type = ParsedCompute
buffer = eta_gold
expression = 'sin(x)+sin(y)+sin(z)'
extra_symbols = true
[]
[eta]
type = ParsedCompute
buffer = eta
expression = eta_gold
inputs = eta_gold
[]
[eta2]
type = ConstantTensor
buffer = eta2
real = 1
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
real = 0
imaginary = 0
[]
[]
[Solve]
[eta_bar]
type = ForwardFFT
buffer = eta_bar
input = eta
[]
[eta_2]
type = InverseFFT
buffer = eta2
input = eta_bar
[]
[]
[Postprocess]
[diff]
type = ParsedCompute
buffer = diff
expression = 'abs(eta - eta2) + abs(eta - eta_gold)'
inputs = 'eta eta2 eta_gold'
[]
[]
[]
[Postprocessors]
[norm]
type = TensorIntegralPostprocessor
buffer = diff
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = eta
reciprocal_buffer = eta_bar
linear_reciprocal = zero
nonlinear_reciprocal = zero
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 4
[]
[Outputs]
csv = true
[]
(test/tests/solvers/coupled.i)
#
# Simple Cahn-Hilliard solve on a 2D grid.
#
[Domain]
dim = 2
nx = 150
ny = 150
xmax = '${fparse pi*2}'
ymax = '${fparse pi*2}'
mesh_mode = DUMMY
[]
[GlobalParams]
constant_names = 'A B'
constant_expressions = '1 3.5'
[]
[TensorComputes]
[Initialize]
[u]
type = ParsedCompute
buffer = u
extra_symbols = true
expression = 'sin(x)*sin(y)'
expand = REAL
[]
[v]
type = ParsedCompute
buffer = v
extra_symbols = true
expression = 'cos(x)*cos(y)'
expand = REAL
[]
[zero]
type = ConstantReciprocalTensor
buffer = zero
[]
# precompute fixed factors for the solve
[D1]
type = ReciprocalLaplacianFactor
factor = 1e-2
buffer = D1
[]
[D2]
type = ReciprocalLaplacianFactor
factor = 1e-3
buffer = D2
[]
[]
[Solve]
[u_bar]
type = ForwardFFT
buffer = u_bar
input = u
[]
[v_bar]
type = ForwardFFT
buffer = v_bar
input = v
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoultonCoupled
buffer = 'u v'
reciprocal_buffer = 'u_bar v_bar'
linear_reciprocal = 'D1 D1'
linear_offdiag_cols = '0 1'
linear_offdiag_rows = '1 0'
linear_offdiag = 'D2 D2'
nonlinear_reciprocal = 'zero zero'
substeps = ${ss}
corrector_steps = ${cs}
predictor_order = ${order}
corrector_order = ${order}
[]
[Problem]
type = TensorProblem
[]
[Postprocessors]
[u_min]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MIN
[]
[u_max]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MAX
[]
[v_min]
type = TensorExtremeValuePostprocessor
buffer = v
value_type = MIN
[]
[v_max]
type = TensorExtremeValuePostprocessor
buffer = v
value_type = MAX
[]
[U]
type = TensorIntegralPostprocessor
buffer = u
[]
[V]
type = TensorIntegralPostprocessor
buffer = v
[]
[]
[Executioner]
type = Transient
num_steps = 25
dt = 10
[]
[Outputs]
file_base = coupled_${ss}_${cs}_${order}
csv = true
[]
(test/tests/tensor_compute/coupled_pf_mech.i)
[Domain]
dim = 3
nx = 128
ny = 128
nz = 128
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
zmax = ${fparse pi*4}
mesh_mode = DUMMY
[]
[TensorBuffers]
# phase field
[c]
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# mechanics
[disp_x]
[]
[disp_y]
[]
[disp_z]
[]
[mumechbar]
[]
[mumech]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c disp_x disp_y disp_z mu mumech'
output_mode = 'Node Node Node Node Cell Cell'
enable_hdf5 = true
[]
[]
[TensorComputes]
[Initialize]
[c]
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
[]
[disp_x]
type = RandomTensor
buffer = disp_x
min = 0
max = 0
[]
[disp_y]
type = RandomTensor
buffer = disp_y
min = 0
max = 0
[]
[disp_z]
type = RandomTensor
buffer = disp_z
min = 0
max = 0
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -0.001 # kappa
buffer = kappabarbar
[]
[]
[Solve]
[mu]
# chemical potential (real space)
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2' # + c*sin(x/2)*0.005'
extra_symbols = true
derivatives = c
inputs = c
[]
[mubar]
# chemical potential (reciprocal space)
type = ForwardFFT
buffer = mubar
input = mu
[]
[mumechbar]
# mechanical chemical potential (reciprocal space)
type = FFTElasticChemicalPotential
buffer = mumechbar
cbar = cbar
displacements = 'disp_x disp_y disp_z'
lambda = 100
mu = 50
e0 = 0.02
[]
[mumech]
# chemical potential (reciprocal space)
type = InverseFFT
buffer = mumech
input = mumechbar
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*(mubar+mumechbar)'
inputs = 'Mbar mubar mumechbar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[qsmech]
type = FFTQuasistaticElasticity
displacements = 'disp_x disp_y disp_z'
cbar = cbar
lambda = 100
mu = 50
e0 = 0.02
[]
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = c
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_x]
type = TensorExtremeValuePostprocessor
buffer = disp_x
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_x]
type = TensorExtremeValuePostprocessor
buffer = disp_x
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_y]
type = TensorExtremeValuePostprocessor
buffer = disp_y
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_y]
type = TensorExtremeValuePostprocessor
buffer = disp_y
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_z]
type = TensorExtremeValuePostprocessor
buffer = disp_z
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_z]
type = TensorExtremeValuePostprocessor
buffer = disp_z
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[cavg]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
print_debug_output = true
[]
[Executioner]
type = Transient
num_steps = 100
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.8
dt = 0.1
[]
dtmax = 1000
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(benchmarks/01_spinodal_decomposition/1a_secant.i)
[Domain]
dim = 2
nx = 200
ny = 200
xmax = 200
ymax = 200
device_names = 'cuda'
mesh_mode = DOMAIN
[]
[TensorBuffers]
[c]
map_to_aux_variable = c
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
# postprocessing
[F]
[]
[Fgrad]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 5 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -10 # -kappa*M
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = 'rho_s*(c-c_alpha)^2*(c_beta-c)^2'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
derivatives = c
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[Postprocess]
[Fgrad]
type = FFTGradientSquare
buffer = Fgrad
input = c
factor = 1 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = 'rho_s * (c-c_alpha)^2 * (c_beta-c)^2 + Fgrad'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
inputs = 'c Fgrad'
[]
[]
[]
[TensorSolver]
type = SecantSolver
substeps = 5
max_iterations = 50
tolerance = 1e-7
dt_epsilon = 1e-5
buffer = c
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[AuxVariables]
[c]
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 900
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.01
dt = 1
[]
# dtmax = 200
[]
[Outputs]
exodus = true
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/tensor_compute/coupled_pf_mech_secant.i)
[Domain]
dim = 3
nx = 128
ny = 128
nz = 128
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
zmax = ${fparse pi*4}
mesh_mode = DUMMY
[]
[TensorBuffers]
# phase field
[c]
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# mechanics
[disp_x]
[]
[disp_y]
[]
[disp_z]
[]
[mumechbar]
[]
[mumech]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c disp_x disp_y disp_z mu mumech'
output_mode = 'Node Node Node Node Cell Cell'
enable_hdf5 = true
[]
[]
[TensorComputes]
[Initialize]
[c]
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
[]
[mu_init]
type = ConstantTensor
buffer = mu
[]
[mumech_init]
type = ConstantTensor
buffer = mumech
[]
[disp_x]
type = RandomTensor
buffer = disp_x
min = 0
max = 0
[]
[disp_y]
type = RandomTensor
buffer = disp_y
min = 0
max = 0
[]
[disp_z]
type = RandomTensor
buffer = disp_z
min = 0
max = 0
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -0.001 # kappa
buffer = kappabarbar
[]
[]
[Solve]
[mu]
# chemical potential (real space)
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2' # + c*sin(x/2)*0.005'
extra_symbols = true
derivatives = c
inputs = c
[]
[mubar]
# chemical potential (reciprocal space)
type = ForwardFFT
buffer = mubar
input = mu
[]
[mumechbar]
# mechanical chemical potential (reciprocal space)
type = FFTElasticChemicalPotential
buffer = mumechbar
cbar = cbar
displacements = 'disp_x disp_y disp_z'
lambda = 100
mu = 50
e0 = 0.02
[]
[mumech]
# chemical potential (reciprocal space)
type = InverseFFT
buffer = mumech
input = mumechbar
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*(mubar+mumechbar)'
inputs = 'Mbar mubar mumechbar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[qsmech]
type = FFTQuasistaticElasticity
displacements = 'disp_x disp_y disp_z'
cbar = cbar
lambda = 100
mu = 50
e0 = 0.02
[]
[]
[]
[TensorSolver]
type = SecantSolver
substeps = 1
max_iterations = 1000
# damping = 0.75
relative_tolerance = 1e-6
absolute_tolerance = 1e-6
buffer = c
dt_epsilon = 1e-7
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
verbose = true
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_x]
type = TensorExtremeValuePostprocessor
buffer = disp_x
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_x]
type = TensorExtremeValuePostprocessor
buffer = disp_x
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_y]
type = TensorExtremeValuePostprocessor
buffer = disp_y
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_y]
type = TensorExtremeValuePostprocessor
buffer = disp_y
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_z]
type = TensorExtremeValuePostprocessor
buffer = disp_z
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_z]
type = TensorExtremeValuePostprocessor
buffer = disp_z
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[cavg]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
end_time = 100
[TimeStepper]
type = TensorSolveIterationAdaptiveDT
dt = 0.1
max_iterations = 500
min_iterations = 300
growth_factor = 1.1
cutback_factor = 0.9
[]
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(examples/libtorch_kks/KKS_libtorch.i)
#
# Kim-Kim-Suzuki with Gibbs energy supplied by a torch model, solved on a 2D grid.
#
# Constants for Initial Conditions
r = 30
l = 4.2
# Initial condition function for order parameter
eta_IC = '0.5*(1-tanh(2*(sqrt(x^2+y^2)-${r})/${l}))'
# Phase-field model parameters
kappa_eta = 5
w = 1
M = 5
L = 5
# Expressions for switching function and bulk Gibbs energy
h_eta = 'eta^3*(6*eta^2-15*eta+10)'
[Domain]
dim = 2
nx = 100
ny = 100
xmin = -50
xmax = 50
ymin = -50
ymax = 50
# automatically create a matching mesh
mesh_mode = DUMMY
[]
[TensorComputes]
[Initialize]
[c_IC]
type = ParsedCompute
buffer = c
expression = '0.6 + (0.3-0.6)*${eta_IC}'
extra_symbols = 'true'
[]
[eta_IC]
type = ParsedCompute
buffer = eta
expression = '${eta_IC}'
extra_symbols = 'true'
[]
[psi_init]
type = ConstantTensor
buffer = psi
real = 1
[]
[M]
type = ConstantTensor
buffer = M
real = ${M}
[]
[L]
type = ConstantTensor
buffer = L
real = ${L}
[]
[L_kappa]
type = ReciprocalLaplacianFactor
buffer = L_kappa
factor = ${fparse ${L} * ${kappa_eta} }
[]
[h_eta_IC]
type = ParsedCompute
buffer = h_eta
expression = '${h_eta}'
inputs = eta
[]
[G_func_IC]
type = LibtorchGibbsEnergy
buffer = 'G'
phase_fractions = 'h_eta'
concentrations = 'c'
domega_detas = 'dG_dh'
chem_pots = 'mu'
libtorch_model_file = 'torch_NN_gibbs_model.pt'
[]
[smooth]
type = DeAliasingTensor
method = HOULI
buffer = smooth
[]
[]
[Solve]
[h_eta]
type = ParsedCompute
buffer = h_eta
expression = '${h_eta}'
inputs = eta
[]
[G_func]
type = LibtorchGibbsEnergy
buffer = 'G'
phase_fractions = 'h_eta'
concentrations = 'c'
domega_detas = 'dG_dh'
chem_pots = 'mu'
libtorch_model_file = 'torch_NN_gibbs_model.pt'
[]
[dG_deta]
type = ParsedCompute
buffer = 'dG_deta'
inputs = 'eta dG_dh'
expression = 'dG_dh * ${h_eta} + ${w} * eta^2 * (1-eta^2)^2'
derivatives = 'eta'
[]
[etabar]
type = ForwardFFT
buffer = etabar
input = eta
[]
[AC_bulk]
type = ReciprocalAllenCahn
L = L
buffer = AC_bulk
dF_chem_deta = dG_deta
psi = psi
[]
[NL_eta]
type = ParsedCompute
buffer = NL_eta
expression = 'AC_bulk '
inputs = 'AC_bulk'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[div_J]
type = ReciprocalMatDiffusion
buffer = 'div_J'
chemical_potential = mu
mobility = M
psi = psi
[]
[NL_c]
type = ParsedCompute
buffer = 'NL_c'
inputs = 'div_J smooth'
expression = 'smooth * div_J'
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'c eta'
reciprocal_buffer = 'cbar etabar'
linear_reciprocal = '0 L_kappa'
nonlinear_reciprocal = 'NL_c NL_eta'
substeps = 1e3
predictor_order = 3
corrector_order = 1
corrector_steps = 1
[]
[Postprocessors]
[total_c]
type = TensorIntegralPostprocessor
buffer = c
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'eta c mu psi dG_deta dG_dh G'
enable_hdf5 = true
transpose = false
[]
[]
[Executioner]
type = Transient
num_steps = 100
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.25
dt = 0.1
[]
dtmax = 10
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(examples/cahn_hilliard/cahnhilliard2.i)
#
# The same simple Cahn-Hilliard solve as cahnhilliard.i, but on a 3D grid
# and using the faster TensorOutputs system.
#
[Domain]
dim = 3
nx = 200
ny = 200
nz = 200
xmax = ${fparse pi*8}
ymax = ${fparse pi*8}
zmax = ${fparse pi*8}
# run on a CUDA device (adjust this to `cpu` if not available)
device_names = 'cuda'
# create a single element dummy mesh. Output will use the custom XDMF output
# in the `TensorOutputs` system.
mesh_mode = DUMMY
[]
[TensorBuffers]
[c]
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
[]
[TensorOutputs]
# the TensorOutouts system supports asynchronous threaded output.
# for GOU calculations a copy of the solution fields is moved to the CPU,
# and while the output files are written the next time step is already
# starting to compute.
[xdmf]
type = XDMFTensorOutput
buffer = 'c mu'
enable_hdf5 = true
[]
[]
[TensorComputes]
[Initialize]
[c]
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -0.001 # kappa
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2'
derivatives = c
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = c
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
substeps = 1000
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[cavg]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 100
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.8
dt = 0.1
[]
dtmax = 1000
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(benchmarks/02_oswald_ripening/2a.i)
[Domain]
dim = 2
nx = 200
ny = 200
xmax = 200
ymax = 200
mesh_mode = DOMAIN
[]
fchem = 'fa:=rho^2*(c-ca)^2;
fb:=rho^2*(cb-c)^2;
h:=n1^3*(6*n1^2-15*n1+10) +
n2^3*(6*n2^2-15*n2+10) +
n3^3*(6*n3^2-15*n3+10) +
n4^3*(6*n4^2-15*n4+10);
g:=n1^2*(1-n1)^2 +
n2^2*(1-n2)^2 +
n3^2*(1-n3)^2 +
n4^2*(1-n4)^2 +
alpha*(
n1^2*n2^2 + n1^2*n3^2 + n1^2*n4^2 +
n2^2*n1^2 + n2^2*n3^2 + n2^2*n4^2 +
n3^2*n1^2 + n3^2*n2^2 + n3^2*n4^2 +
n4^2*n1^2 + n4^2*n2^2 + n4^2*n3^2);
(fa*(1-h) + fb*h + w*g)'
nic = 'epsilon*(cos((0.01*idx)*x-4)*cos((0.007+0.01*idx)*y)
+cos((0.11+0.01*idx)*x)*cos((0.11+0.01*idx)*y)
+psi*(cos((0.046+0.001*idx)*x+(0.0405+0.001*idx)*y)
*cos((0.031+0.001*idx)*x-(0.004+0.001*idx)*y))^2)^2'
cnames = 'rho ca cb alpha w L M'
cvalues = 'sqrt(2) 0.3 0.7 5 1 5 5'
[TensorBuffers]
# variables
[c]
# map_to_aux_variable = c
[]
[n1]
[]
[n2]
[]
[n3]
[]
[n4]
[]
[c_bar]
[]
[n1_bar]
[]
[n2_bar]
[]
[n3_bar]
[]
[n4_bar]
[]
[mu_c]
# map_to_aux_variable = mu
[]
[mu_n1]
[]
[mu_n2]
[]
[mu_n3]
[]
[mu_n4]
[]
[mu_c_bar]
[]
[mu_n1_bar]
[]
[mu_n2_bar]
[]
[mu_n3_bar]
[]
[mu_n4_bar]
[]
[Mbar_mu_c_bar]
[]
# constant tensors
[Lbar] # FFT(M*laplacian)
[]
[MkappaL2bar] # FFT(-M*kappa*laplacian^2)
[]
[kappaLbar] # FFT(L*kappa*laplacian)
[]
# postprocessing
[F]
[]
[Fgrad_c]
[]
[Fgrad_n1]
[]
[Fgrad_n2]
[]
[Fgrad_n3]
[]
[Fgrad_n4]
[]
[bnds]
#map_to_aux_variable = bnds
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Lbar]
type = ReciprocalLaplacianFactor
# Mobility is pulled into the chemical potential below
buffer = Lbar
[]
[MkappaL2bar]
type = ReciprocalLaplacianSquareFactor
factor = -15 # -kappa_c*M
buffer = MkappaL2bar
[]
[kappaLbar]
type = ReciprocalLaplacianFactor
buffer = kappaLbar
factor = 15 # kappa_ni*L
[]
[n1]
type = ParsedCompute
buffer = n1
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 1 0.1 1.5'
[]
[n2]
type = ParsedCompute
buffer = n2
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 2 0.1 1.5'
[]
[n3]
type = ParsedCompute
buffer = n3
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 3 0.1 1.5'
[]
[n4]
type = ParsedCompute
buffer = n4
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 4 0.1 1.5'
[]
[]
[Solve]
[mu_c]
type = ParsedCompute
buffer = mu_c
expression = '${fchem}*M'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = c
inputs = 'c n1 n2 n3 n4'
[]
[mu_n1]
type = ParsedCompute
buffer = mu_n1
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n1
inputs = 'c n1 n2 n3 n4'
[]
[mu_n2]
type = ParsedCompute
buffer = mu_n2
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n2
inputs = 'c n1 n2 n3 n4'
[]
[mu_n3]
type = ParsedCompute
buffer = mu_n3
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n3
inputs = 'c n1 n2 n3 n4'
[]
[mu_n4]
type = ParsedCompute
buffer = mu_n4
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n4
inputs = 'c n1 n2 n3 n4'
[]
[mu_c_bar]
type = ForwardFFT
buffer = mu_c_bar
input = mu_c
[]
[mu_n1_bar]
type = ForwardFFT
buffer = mu_n1_bar
input = mu_n1
[]
[mu_n2_bar]
type = ForwardFFT
buffer = mu_n2_bar
input = mu_n2
[]
[mu_n3_bar]
type = ForwardFFT
buffer = mu_n3_bar
input = mu_n3
[]
[mu_n4_bar]
type = ForwardFFT
buffer = mu_n4_bar
input = mu_n4
[]
[Mbar_mu_c_bar]
type = ParsedCompute
buffer = Mbar_mu_c_bar
expression = 'Lbar*mu_c_bar'
inputs = 'Lbar mu_c_bar'
[]
[c_bar]
type = ForwardFFT
buffer = c_bar
input = c
[]
[n1_bar]
type = ForwardFFT
buffer = n1_bar
input = n1
[]
[n2_bar]
type = ForwardFFT
buffer = n2_bar
input = n2
[]
[n3_bar]
type = ForwardFFT
buffer = n3_bar
input = n3
[]
[n4_bar]
type = ForwardFFT
buffer = n4_bar
input = n4
[]
[]
[Postprocess]
[Fgrad_c]
type = FFTGradientSquare
buffer = Fgrad_c
input = c
factor = 1.5 # kappa/2
[]
[Fgrad_n1]
type = FFTGradientSquare
buffer = Fgrad_n1
input = n1
factor = 1.5 # kappa/2
[]
[Fgrad_n2]
type = FFTGradientSquare
buffer = Fgrad_n2
input = n2
factor = 1.5 # kappa/2
[]
[Fgrad_n3]
type = FFTGradientSquare
buffer = Fgrad_n3
input = n3
factor = 1.5 # kappa/2
[]
[Fgrad_n4]
type = FFTGradientSquare
buffer = Fgrad_n4
input = n4
factor = 1.5 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = '${fchem} + Fgrad_c + Fgrad_n1 + Fgrad_n2 + Fgrad_n3 + Fgrad_n4'
constant_names = ${cnames}
constant_expressions = ${cvalues}
inputs = 'c n1 n2 n3 n4 Fgrad_c Fgrad_n1 Fgrad_n2 Fgrad_n3 Fgrad_n4'
[]
[bnds]
type = ParsedCompute
buffer = bnds
expression = 'n1^2 + n2^2 + n3^2 + n4^2'
inputs = 'n1 n2 n3 n4'
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'c n1 n2 n3 n4'
reciprocal_buffer = 'c_bar n1_bar n2_bar n3_bar n4_bar'
linear_reciprocal = 'MkappaL2bar kappaLbar kappaLbar kappaLbar kappaLbar'
nonlinear_reciprocal = 'Mbar_mu_c_bar mu_n1_bar mu_n2_bar mu_n3_bar mu_n4_bar'
substeps = 2000
predictor_order = 2
corrector_order = 2
corrector_steps = 0
[]
[AuxVariables]
[c]
[]
[bnds]
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
# [stable_dt]
# type = SemiImplicitCriticalTimeStep
# buffer = MkappaL2bar
# []
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1030
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.1
dt = 0.001
[]
dtmax = 10
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c bnds'
output_mode = 'CELL CELL'
[]
[]
(benchmarks/02_oswald_ripening/2a_secant.i)
[Domain]
dim = 2
nx = 120
ny = 120
xmax = 200
ymax = 200
device_names = 'cuda:1'
mesh_mode = DOMAIN
[]
fchem='fa:=rho^2*(c-ca)^2;
fb:=rho^2*(cb-c)^2;
h:=n1^3*(6*n1^2-15*n1+10) +
n2^3*(6*n2^2-15*n2+10) +
n3^3*(6*n3^2-15*n3+10) +
n4^3*(6*n4^2-15*n4+10);
g:=n1^2*(1-n1)^2 +
n2^2*(1-n2)^2 +
n3^2*(1-n3)^2 +
n4^2*(1-n4)^2 +
alpha*(
n1^2*n2^2 + n1^2*n3^2 + n1^2*n4^2 +
n2^2*n1^2 + n2^2*n3^2 + n2^2*n4^2 +
n3^2*n1^2 + n3^2*n2^2 + n3^2*n4^2 +
n4^2*n1^2 + n4^2*n2^2 + n4^2*n3^2);
(fa*(1-h) + fb*h + w*g)'
nic = 'epsilon*(cos((0.01*idx)*x-4)*cos((0.007+0.01*idx)*y)
+cos((0.11+0.01*idx)*x)*cos((0.11+0.01*idx)*y)
+psi*(cos((0.046+0.001*idx)*x+(0.0405+0.001*idx)*y)
*cos((0.031+0.001*idx)*x-(0.004+0.001*idx)*y))^2)^2'
cnames = 'rho ca cb alpha w L M'
cvalues= 'sqrt(2) 0.3 0.7 5 1 5 5'
[TensorBuffers]
# variables
[c]
[]
[n1]
[]
[n2]
[]
[n3]
[]
[n4]
[]
[c_bar]
[]
[n1_bar]
[]
[n2_bar]
[]
[n3_bar]
[]
[n4_bar]
[]
[mu_c]
[]
[mu_n1]
[]
[mu_n2]
[]
[mu_n3]
[]
[mu_n4]
[]
[mu_c_bar]
[]
[mu_n1_bar]
[]
[mu_n2_bar]
[]
[mu_n3_bar]
[]
[mu_n4_bar]
[]
[Mbar_mu_c_bar]
[]
# constant tensors
[Lbar] # FFT(M*laplacian)
[]
[MkappaL2bar] # FFT(-M*kappa*laplacian^2)
[]
[kappaLbar] # FFT(L*kappa*laplacian)
[]
# postprocessing
[F]
[]
[Fgrad_c]
[]
[Fgrad_n1]
[]
[Fgrad_n2]
[]
[Fgrad_n3]
[]
[Fgrad_n4]
[]
[bnds]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Lbar]
type = ReciprocalLaplacianFactor
# Mobility is pulled into the chemical potential below
buffer = Lbar
[]
[MkappaL2bar]
type = ReciprocalLaplacianSquareFactor
factor = -15 # -kappa_c*M
buffer = MkappaL2bar
[]
[kappaLbar]
type = ReciprocalLaplacianFactor
buffer = kappaLbar
factor = 15 # kappa_ni*L
[]
[n1]
type = ParsedCompute
buffer = n1
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 1 0.1 1.5'
[]
[n2]
type = ParsedCompute
buffer = n2
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 2 0.1 1.5'
[]
[n3]
type = ParsedCompute
buffer = n3
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 3 0.1 1.5'
[]
[n4]
type = ParsedCompute
buffer = n4
expression = ${nic}
extra_symbols = true
constant_names = 'idx epsilon psi'
constant_expressions = ' 4 0.1 1.5'
[]
[]
[Solve]
[mu_c]
type = ParsedCompute
buffer = mu_c
expression = '${fchem}*M'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = c
inputs = 'c n1 n2 n3 n4'
[]
[mu_n1]
type = ParsedCompute
buffer = mu_n1
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n1
inputs = 'c n1 n2 n3 n4'
[]
[mu_n2]
type = ParsedCompute
buffer = mu_n2
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n2
inputs = 'c n1 n2 n3 n4'
[]
[mu_n3]
type = ParsedCompute
buffer = mu_n3
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n3
inputs = 'c n1 n2 n3 n4'
[]
[mu_n4]
type = ParsedCompute
buffer = mu_n4
expression = '${fchem}*(-L)'
constant_names = ${cnames}
constant_expressions = ${cvalues}
derivatives = n4
inputs = 'c n1 n2 n3 n4'
[]
[mu_c_bar]
type = ForwardFFT
buffer = mu_c_bar
input = mu_c
[]
[mu_n1_bar]
type = ForwardFFT
buffer = mu_n1_bar
input = mu_n1
[]
[mu_n2_bar]
type = ForwardFFT
buffer = mu_n2_bar
input = mu_n2
[]
[mu_n3_bar]
type = ForwardFFT
buffer = mu_n3_bar
input = mu_n3
[]
[mu_n4_bar]
type = ForwardFFT
buffer = mu_n4_bar
input = mu_n4
[]
[Mbar_mu_c_bar]
type = ParsedCompute
buffer = Mbar_mu_c_bar
expression = 'Lbar*mu_c_bar'
inputs = 'Lbar mu_c_bar'
[]
[c_bar]
type = ForwardFFT
buffer = c_bar
input = c
[]
[n1_bar]
type = ForwardFFT
buffer = n1_bar
input = n1
[]
[n2_bar]
type = ForwardFFT
buffer = n2_bar
input = n2
[]
[n3_bar]
type = ForwardFFT
buffer = n3_bar
input = n3
[]
[n4_bar]
type = ForwardFFT
buffer = n4_bar
input = n4
[]
[]
[Postprocess]
[Fgrad_c]
type = FFTGradientSquare
buffer = Fgrad_c
input = c
factor = 1.5 # kappa/2
[]
[Fgrad_n1]
type = FFTGradientSquare
buffer = Fgrad_n1
input = n1
factor = 1.5 # kappa/2
[]
[Fgrad_n2]
type = FFTGradientSquare
buffer = Fgrad_n2
input = n2
factor = 1.5 # kappa/2
[]
[Fgrad_n3]
type = FFTGradientSquare
buffer = Fgrad_n3
input = n3
factor = 1.5 # kappa/2
[]
[Fgrad_n4]
type = FFTGradientSquare
buffer = Fgrad_n4
input = n4
factor = 1.5 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = '${fchem} + Fgrad_c + Fgrad_n1 + Fgrad_n2 + Fgrad_n3 + Fgrad_n4'
constant_names = ${cnames}
constant_expressions = ${cvalues}
inputs = 'c n1 n2 n3 n4 Fgrad_c Fgrad_n1 Fgrad_n2 Fgrad_n3 Fgrad_n4'
[]
[bnds]
type = ParsedCompute
buffer = bnds
expression = 'n1^2 + n2^2 + n3^2 + n4^2'
inputs = 'n1 n2 n3 n4'
[]
[]
[]
[TensorSolver]
type = SecantSolver
substeps = 1
max_iterations = 1000
# damping = 0.75
relative_tolerance = 1e-6
absolute_tolerance = 1e-6
buffer = 'c n1 n2 n3 n4'
dt_epsilon = 1e-7
reciprocal_buffer = 'c_bar n1_bar n2_bar n3_bar n4_bar'
linear_reciprocal = 'MkappaL2bar kappaLbar kappaLbar kappaLbar kappaLbar'
nonlinear_reciprocal = 'Mbar_mu_c_bar mu_n1_bar mu_n2_bar mu_n3_bar mu_n4_bar'
# verbose = true
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
# num_steps = 2
end_time = 1e+5
[TimeStepper]
type = TensorSolveIterationAdaptiveDT
dt = 0.1
max_iterations = 500
min_iterations = 300
growth_factor = 1.1
cutback_factor = 0.9
[]
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
[TensorOutputs]
[c]
type = XDMFTensorOutput
buffer = 'c bnds'
output_mode = 'NODE NODE'
enable_hdf5 = true
[]
[]
(test/tests/gradient/gradient.i)
[Domain]
dim = 3
nx = 40
ny = 40
nz = 40
xmax = ${fparse pi*2}
ymax = ${fparse pi*4}
zmax = ${fparse pi*6}
mesh_mode = DUMMY
[]
[TensorBuffers]
[s]
[]
[gradx_s]
[]
[grady_s]
[]
[gradz_s]
[]
[cx]
[]
[cy]
[]
[cz]
[]
[diff]
[]
[]
[TensorComputes]
[Initialize]
[sin]
type = ParsedCompute
buffer = s
extra_symbols = true
expression = 'sin(x)+sin(y)+sin(z)'
[]
[cosx]
type = ParsedCompute
buffer = cx
extra_symbols = true
expression = 'cos(x)'
[]
[cosy]
type = ParsedCompute
buffer = cy
extra_symbols = true
expression = 'cos(y)'
[]
[cosz]
type = ParsedCompute
buffer = cz
extra_symbols = true
expression = 'cos(z)'
[]
[gradx_sin]
type = FFTGradient
buffer = gradx_s
input = s
direction = x
[]
[grady_sin]
type = FFTGradient
buffer = grady_s
input = s
direction = y
[]
[gradz_sin]
type = FFTGradient
buffer = gradz_s
input = s
direction = z
[]
[diff]
type = ParsedCompute
buffer = diff
inputs = 'gradx_s grady_s gradz_s cx cy cz'
expression = 'abs(gradx_s - cx)+abs(grady_s - cy)+abs(gradz_s - cz)'
[]
[]
[]
[Postprocessors]
[diff]
type = TensorIntegralPostprocessor
buffer = diff
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1
[]
[Outputs]
csv = true
[]
(benchmarks/01_spinodal_decomposition/1a.i)
[Domain]
dim = 2
nx = 200
ny = 200
xmax = 200
ymax = 200
device_names = 'cuda'
mesh_mode = DOMAIN
[]
[TensorBuffers]
[c]
map_to_aux_variable = c
[]
[cbar]
[]
[mu]
# map_to_aux_variable = mu
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
# postprocessing
[F]
[]
[Fgrad]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 5 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -10 # -kappa*M
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = 'rho_s*(c-c_alpha)^2*(c_beta-c)^2'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
derivatives = c
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[Postprocess]
[Fgrad]
type = FFTGradientSquare
buffer = Fgrad
input = c
factor = 1 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = 'rho_s * (c-c_alpha)^2 * (c_beta-c)^2 + Fgrad'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
inputs = 'c Fgrad'
[]
[]
[]
[UserObjects]
[terminator]
type = Terminator
expression = change<1e-4
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = c
history_size = 1
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[]
[AuxVariables]
# [mu]
# family = MONOMIAL
# order = CONSTANT
# []
[c]
# family = MONOMIAL
# order = CONSTANT
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[change]
type = TensorIntegralChangePostprocessor
buffer = c
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 1000
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.1
dt = 1
[]
dtmax = 300
[]
[Outputs]
exodus = true
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/tensor_compute/group.i)
[Domain]
dim = 3
nx = 128
ny = 128
nz = 128
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
zmax = ${fparse pi*4}
mesh_mode = DUMMY
[]
[TensorBuffers]
# phase field
[c]
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# mechanics
[disp_x]
[]
[disp_y]
[]
[disp_z]
[]
[mumechbar]
[]
[mumech]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c disp_x disp_y disp_z mu mumech'
output_mode = 'Node Node Node Node Cell Cell'
enable_hdf5 = true
[]
[]
[TensorComputes]
[Initialize]
[c]
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
[]
[disp_x]
type = RandomTensor
buffer = disp_x
min = 0
max = 0
[]
[disp_y]
type = RandomTensor
buffer = disp_y
min = 0
max = 0
[]
[disp_z]
type = RandomTensor
buffer = disp_z
min = 0
max = 0
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -0.001 # kappa
buffer = kappabarbar
[]
[]
[Solve]
[mu]
# chemical potential (real space)
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2' # + c*sin(x/2)*0.005'
extra_symbols = true
derivatives = c
inputs = c
[]
[mubar]
# chemical potential (reciprocal space)
type = ForwardFFT
buffer = mubar
input = mu
[]
[mumechbar]
# mechanical chemical potential (reciprocal space)
type = FFTElasticChemicalPotential
buffer = mumechbar
cbar = cbar
displacements = 'disp_x disp_y disp_z'
lambda = 100
mu = 50
e0 = 0.02
[]
[mumech]
# chemical potential (reciprocal space)
type = InverseFFT
buffer = mumech
input = mumechbar
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*(mubar+mumechbar)'
inputs = 'Mbar mubar mumechbar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[qsmech]
type = FFTQuasistaticElasticity
displacements = 'disp_x disp_y disp_z'
cbar = cbar
lambda = 100
mu = 50
e0 = 0.02
[]
[group]
type = ComputeGroup
computes = 'cbar mumech mu mubar'
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = c
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_x]
type = TensorExtremeValuePostprocessor
buffer = disp_x
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_x]
type = TensorExtremeValuePostprocessor
buffer = disp_x
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_y]
type = TensorExtremeValuePostprocessor
buffer = disp_y
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_y]
type = TensorExtremeValuePostprocessor
buffer = disp_y
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[min_disp_z]
type = TensorExtremeValuePostprocessor
buffer = disp_z
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_disp_z]
type = TensorExtremeValuePostprocessor
buffer = disp_z
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[cavg]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
print_debug_output = true
[]
[Executioner]
type = Transient
num_steps = 100
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.8
dt = 0.1
[]
dtmax = 1000
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/real_space/deep_ghost_periodic.i)
# The reference of deep_ghost_faces.i: the field mirrored onto the periodic domain 0 < x < 32,
# where the 5-point biharmonic reads only periodic ghosts. The postprocessors take 0 < x < 16.
u_ic = 'exp(cos(pi*x/16))*sin(2*pi*y/8)'
[Domain]
dim = 2
nx = 32
ny = 8
xmax = 32
ymax = 8
parallel_mode = REAL_SPACE
periodic_directions = 'X Y'
[]
[TensorBuffers]
[u]
[]
[bih]
[]
[bih_strip]
[]
[bih_sq]
[]
[]
[TensorComputes]
[Initialize]
[u_ic]
type = ParsedCompute
buffer = u
extra_symbols = true
expression = ${u_ic}
[]
[]
[Postprocess]
[bih]
type = FiniteDifferenceBiharmonic
buffer = bih
input = u
stencil_width = 5
[]
# 0 outside the strip, which is between the extremes of both test fields there
[bih_strip]
type = ParsedCompute
buffer = bih_strip
extra_symbols = true
expression = 'if(x < 16, bih, 0)'
inputs = bih
[]
[bih_sq]
type = ParsedCompute
buffer = bih_sq
expression = 'bih_strip^2'
inputs = bih_strip
[]
[]
[]
[Postprocessors]
[integral_bih_sq]
type = TensorIntegralPostprocessor
buffer = bih_sq
[]
[max_bih]
type = TensorExtremeValuePostprocessor
buffer = bih_strip
value_type = MAX
[]
[min_bih]
type = TensorExtremeValuePostprocessor
buffer = bih_strip
value_type = MIN
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1
[]
[Outputs]
csv = true
[]
(test/tests/tensor_compute/parallel.i)
[Domain]
device_names = "cuda:1 cuda:0 cpu"
device_weights = "10 10 1"
parallel_mode = FFT_SLAB
dim = 2
nx = 400
ny = 400
xmax = ${fparse pi*2*30}
ymax = ${fparse pi*2*30}
[]
# [Mesh]
# type = GeneratedMesh
# dim =1
# []
[TensorBuffers]
[psi]
# map_to_aux_variable = psi
[]
[psibar]
[]
[psi3]
[]
[psi3bar]
[]
# constant tensors
[linear]
[]
# output
[filter]
# map_to_aux_variable = filter
[]
[filterbar]
[]
[]
[AuxVariables]
[psi]
[]
[filter]
[]
[]
[TensorComputes]
[Initialize]
[psi]
type = RandomTensor
buffer = psi
min = 0
max = 0.07
[]
[linear]
type = SwiftHohenbergLinear
buffer = linear
alpha = 1
r = 0.025
[]
[]
[Solve]
[psi3]
type = ParsedCompute
buffer = psi3
expression = "0.20*psi^2-psi^3"
inputs = psi
[]
[psibar]
type = ForwardFFT
buffer = psibar
input = psi
[]
[psi3bar]
type = ForwardFFT
buffer = psi3bar
input = psi3
[]
[]
[Postprocess]
[low_pass]
type = ParsedCompute
buffer = filterbar
extra_symbols = true
expression = 'psibar * exp(-k2*10)'
inputs = psibar
[]
[filter]
type = InverseFFT
buffer = filter
input = filterbar
[]
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = psi
reciprocal_buffer = psibar
linear_reciprocal = linear
nonlinear_reciprocal = psi3bar
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 300
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.2
dt = 10
[]
dtmax = 1000
[]
[Postprocessors]
[min_psi]
type = TensorExtremeValuePostprocessor
buffer = psi
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_psi]
type = TensorExtremeValuePostprocessor
buffer = psi
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[Psi]
type = TensorIntegralPostprocessor
buffer = psi
[]
[]
# [TensorOutputs]
# [xdmf]
# type = XDMFTensorOutput
# buffer = 'psi'
# output_mode = 'Node'
# enable_hdf5 = true
# []
# []
[Outputs]
exodus = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(examples/swift_hohenberg/rotating_grain.i)
#
# Solve a simple Swift-Hohenberg crystal phase field problem. The initial condition is
# a circular grain that is rotated against the surropunding matrix.
# This example demonstrates the use of the [TensorComputes/Postprocess] system to perform
# compute steps just prior to running the output objects. Here we perform a low-pass filtering
# by forward transfroming the psi amplitude field into frequency space, attenuating frequencies
# by the exponent of their wave number, and transforming back into real space. This filtering
# makes the dislocation structure in the crystal more pronounced in the visualization.
#
w=60
[Domain]
dim = 2
nx = 400
ny = 400
xmax = ${fparse pi*2*w}
ymax = ${fparse pi*2*w}
device_names = 'cuda'
mesh_mode = DOMAIN
[]
[TensorBuffers]
[psi]
map_to_aux_variable = psi
[]
[psibar]
[]
[psi3]
[]
[psi3bar]
[]
# constant tensors
[linear]
[]
# output
[filter]
map_to_aux_variable = filter
[]
[filterbar]
[]
[]
[AuxVariables]
[psi]
[]
[filter]
[]
[]
crystal = '-sin(sin(a)*y/2+cos(a)*x/2)^2*sin(sin(a+1/3*pi)*y/2+cos(a+1/3*pi)*x/2)^2*sin(sin(a-1/3*pi)*y/2+cos(a-1/3*pi)*x/2)^2'
[Functions]
[grain1]
type = ParsedFunction
expression = 'a := 0; ${crystal}'
[]
[grain2]
type = ParsedFunction
expression = 'a := 0.95; ${crystal}'
[]
[domain]
type = ParsedFunction
expression = 'r := (x-${w}*pi)^2+(y-${w}*pi)^2; if(r<(${w}*2/3*pi)^2, grain2, grain1)'
symbol_names = 'grain1 grain2'
symbol_values = 'grain1 grain2'
[]
[]
[TensorComputes]
[Initialize]
[psi]
type = MooseFunctionTensor
buffer = psi
function = domain
[]
[linear]
type = SwiftHohenbergLinear
buffer = linear
alpha = 1
r = 0.025
[]
[]
[Solve]
[psi3]
type = ParsedCompute
buffer = psi3
expression = "0.20*psi^2-psi^3"
inputs = psi
[]
[psibar]
type = ForwardFFT
buffer = psibar
input = psi
[]
[psi3bar]
type = ForwardFFT
buffer = psi3bar
input = psi3
[]
[]
[Postprocess]
[low_pass]
type = ParsedCompute
buffer = filterbar
extra_symbols = true
expression = 'psibar * exp(-k2*10)'
inputs = psibar
[]
[filter]
type = InverseFFT
buffer = filter
input = filterbar
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = psi
reciprocal_buffer = psibar
linear_reciprocal = linear
nonlinear_reciprocal = psi3bar
substeps = 100
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 120
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.1
dt = 5
[]
dtmax = 500
[]
[Postprocessors]
[min_psi]
type = TensorExtremeValuePostprocessor
buffer = psi
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_psi]
type = TensorExtremeValuePostprocessor
buffer = psi
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[Psi]
type = TensorIntegralPostprocessor
buffer = psi
[]
[]
[Outputs]
exodus = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/parsed_tensor/local_vars_derivative.i)
#
# Test differentiation of local variables in ParsedCompute
#
# We test the expression with a buffer input: r := sqrt(a^2 + 1); r^2
# The derivative with respect to a should be: d/da(r^2) = 2*r * dr/da = 2*r * a/r = 2*a
#
[Domain]
dim = 2
nx = 20
ny = 20
xmax = 2
ymax = 2
mesh_mode = DUMMY
[]
[TensorBuffers]
[a] # Input variable
[]
[df_da] # Auto-differentiated derivative
[]
[df_da_exact] # Hand-coded exact derivative
[]
[error] # Absolute difference
[]
[]
[TensorComputes]
[Solve]
# Initialize input buffer
[init_a]
type = ParsedCompute
buffer = a
expression = 'x + 0.5*y'
extra_symbols = true
[]
# Auto-differentiated derivative: d/da(r^2) where r:=sqrt(a^2+1)
[auto_derivative]
type = ParsedCompute
buffer = df_da
expression = 'r:=sqrt(a^2+1); r^2'
derivatives = 'a'
inputs = 'a'
[]
# Hand-coded exact derivative: d/da(r^2) = 2*a
[exact_derivative]
type = ParsedCompute
buffer = df_da_exact
expression = '2*a'
inputs = 'a'
[]
# Compute absolute error
[compute_error]
type = ParsedCompute
buffer = error
expression = 'abs(df_da - df_da_exact)'
inputs = 'df_da df_da_exact'
[]
[]
[]
[Postprocessors]
[integral_error]
type = TensorIntegralPostprocessor
buffer = error
execute_on = 'INITIAL'
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 0
[]
[Outputs]
csv = true
[]
(examples/cahn_hilliard/cahnhilliard4.i)
[Domain]
dim = 3
nx = 100
ny = 100
nz = 100
xmax = ${fparse pi*4}
ymax = ${fparse pi*4}
zmax = ${fparse pi*4}
device_names = 'cuda'
mesh_mode = DUMMY
debug = true
[]
[TensorBuffers]
[c]
[]
[cbar]
[]
[mu]
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c mu'
output_mode = 'Node Cell'
enable_hdf5 = true
[]
[]
[TensorComputes]
[Initialize]
[c]
type = RandomTensor
buffer = c
min = 0.44
max = 0.56
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 0.2 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -0.001 # kappa
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = '0.1*c^2*(c-1)^2 + c*sin(x/2)*0.005'
extra_symbols = true
derivatives = c
# expression = "0.4*c^3-0.6*c^2+0.2*c"
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = c
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[C]
type = TensorIntegralPostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[cavg]
type = TensorAveragePostprocessor
buffer = c
execute_on = 'TIMESTEP_END'
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 50
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.8
dt = 0.1
[]
dtmax = 500
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(examples/anisotropic_grain_growth/isotropic_five_grain.i)
interface_width = 1.6
side = 80
gbe_max = '${units 0.65 J/m^2}'
L = '${fparse 1.0 * 1.6 / ${interface_width} }'
# ------------------------------------------------------------------
# Isotropic reference case.
#
# The GB energy is fixed at sigma = 0.65 J/m^2 for all boundaries,
# equal to gbe_max. Consequently gamma_ij = 1.5 for all pairs (the
# symmetric-well value), there are no torque terms, the mobility is
# uniform (L_NL == L), and the mobility-split correction
# (L_NL - L)*kappa*laplacian(gr_i) vanishes identically.
# ------------------------------------------------------------------
# ------------------------------------------------------------------
# Periodic Voronoi-like IC for 5 grains.
#
# Each grain is seeded at a point (xi, yi). We use a smooth *periodic*
# distance metric based on sine functions,
# d_i^2 = (side/pi)^2 * [ sin(pi*(x-xi)/side)^2 + sin(pi*(y-yi)/side)^2 ]
# which reduces to the Euclidean distance near the seed and wraps
# correctly across the periodic boundaries.
#
# The order parameters are then a softmax over the negative distances,
# gr_i = exp(-a*d_i) / sum_j exp(-a*d_j), a = 4/interface_width
# For any two competing grains this reduces exactly to the usual
# 0.5*(1 - tanh(2*(d_i - d_j)/interface_width)) profile, so the
# interfaces come out with the correct width, the partition of unity
# sum_i gr_i = 1 holds identically, and the cell structure is the
# (diffuse) Voronoi tessellation of the seeds under the periodic metric.
# ------------------------------------------------------------------
aexp = '${fparse 4.0 / ${interface_width} }'
lp = '${fparse ${side} / pi }'
kp = '${fparse pi / ${side} }'
# seed points (spread out over the periodic domain)
d0 = 'sqrt((${lp}*sin(${kp}*(x-8)))^2 + (${lp}*sin(${kp}*(y-6)))^2)'
d1 = 'sqrt((${lp}*sin(${kp}*(x-28)))^2 + (${lp}*sin(${kp}*(y-10)))^2)'
d2 = 'sqrt((${lp}*sin(${kp}*(x-20)))^2 + (${lp}*sin(${kp}*(y-24)))^2)'
d3 = 'sqrt((${lp}*sin(${kp}*(x-4)))^2 + (${lp}*sin(${kp}*(y-28)))^2)'
d4 = 'sqrt((${lp}*sin(${kp}*(x-34)))^2 + (${lp}*sin(${kp}*(y-33)))^2)'
g_gamma0 = '${fparse sqrt(2) / 3 }' # g(gamma=1.5)
f0_gamma0 = ${fparse 1/8}
kappa = '${fparse gbe_max * interface_width * sqrt(f0_gamma0) / g_gamma0 }'
mu = '${fparse gbe_max / (g_gamma0 * interface_width * sqrt(f0_gamma0) ) }'
gamma = 1.5
f0 = '((gr0^4/4 - gr0^2/2) + (gr1^4/4 - gr1^2/2) + (gr2^4/4 - gr2^2/2) + (gr3^4/4 - gr3^2/2) + (gr4^4/4 - gr4^2/2) + ${gamma}*(gr0^2*gr1^2 + gr0^2*gr2^2 + gr0^2*gr3^2 + gr0^2*gr4^2 + gr1^2*gr2^2 + gr1^2*gr3^2 + gr1^2*gr4^2 + gr2^2*gr3^2 + gr2^2*gr4^2 + gr3^2*gr4^2) + 0.25)'
[Domain]
dim = 2
nx = 200
ny = 200
xmax = ${side}
ymax = ${side}
mesh_mode = DUMMY
[]
[TensorComputes]
[Initialize]
# unnormalized softmax weights
[c0]
type = ParsedCompute
buffer = c0
expression = 'exp(-${aexp}*${d0})'
extra_symbols = true
[]
[c1]
type = ParsedCompute
buffer = c1
expression = 'exp(-${aexp}*${d1})'
extra_symbols = true
[]
[c2]
type = ParsedCompute
buffer = c2
expression = 'exp(-${aexp}*${d2})'
extra_symbols = true
[]
[c3]
type = ParsedCompute
buffer = c3
expression = 'exp(-${aexp}*${d3})'
extra_symbols = true
[]
[c4]
type = ParsedCompute
buffer = c4
expression = 'exp(-${aexp}*${d4})'
extra_symbols = true
[]
# normalized order parameters (partition of unity by construction)
[gr0]
type = ParsedCompute
buffer = gr0
expression = 'c0/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr1]
type = ParsedCompute
buffer = gr1
expression = 'c1/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr2]
type = ParsedCompute
buffer = gr2
expression = 'c2/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr3]
type = ParsedCompute
buffer = gr3
expression = 'c3/(c0+c1+c2+c3+c4)'
inputs = 'c0 c1 c2 c3 c4'
[]
[gr4]
type = ParsedCompute
buffer = gr4
expression = '1 - gr0 - gr1 - gr2 - gr3'
inputs = 'gr0 gr1 gr2 gr3'
[]
[L_kappa_laplacian]
type = ReciprocalLaplacianFactor
buffer = 'L_kappa_laplacian'
factor = '${fparse ${L} * ${kappa}}'
[]
[smooth]
type = DeAliasingTensor
method = HOULI
buffer = smooth
[]
[]
[Solve]
[bnds]
type = ParsedCompute
buffer = 'bnds'
inputs = 'gr0 gr1 gr2 gr3 gr4'
expression = 'gr0^2 + gr1^2 + gr2^2 + gr3^2 + gr4^2'
[]
## FFT
[gr0_bar]
type = ForwardFFT
buffer = gr0_bar
input = gr0
[]
[gr1_bar]
type = ForwardFFT
buffer = gr1_bar
input = gr1
[]
[gr2_bar]
type = ForwardFFT
buffer = gr2_bar
input = gr2
[]
[gr3_bar]
type = ForwardFFT
buffer = gr3_bar
input = gr3
[]
[gr4_bar]
type = ForwardFFT
buffer = gr4_bar
input = gr4
[]
## bulk driving forces (constant mobility L, constant gamma = ${gamma})
[gr0_bulk_term]
type = ParsedCompute
buffer = 'gr0_bulk_term'
expression = '-${L}*${mu} * (gr0^3 - gr0 + 2*${gamma}*gr0*(gr1^2 + gr2^2 + gr3^2 + gr4^2))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[gr1_bulk_term]
type = ParsedCompute
buffer = 'gr1_bulk_term'
expression = '-${L}*${mu} * (gr1^3 - gr1 + 2*${gamma}*gr1*(gr0^2 + gr2^2 + gr3^2 + gr4^2))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[gr2_bulk_term]
type = ParsedCompute
buffer = 'gr2_bulk_term'
expression = '-${L}*${mu} * (gr2^3 - gr2 + 2*${gamma}*gr2*(gr0^2 + gr1^2 + gr3^2 + gr4^2))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[gr3_bulk_term]
type = ParsedCompute
buffer = 'gr3_bulk_term'
expression = '-${L}*${mu} * (gr3^3 - gr3 + 2*${gamma}*gr3*(gr0^2 + gr1^2 + gr2^2 + gr4^2))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[gr4_bulk_term]
type = ParsedCompute
buffer = 'gr4_bulk_term'
expression = '-${L}*${mu} * (gr4^3 - gr4 + 2*${gamma}*gr4*(gr0^2 + gr1^2 + gr2^2 + gr3^2))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[NL_gr0]
type = ForwardFFT
buffer = NL_gr0
input = 'gr0_bulk_term'
[]
[NL_gr1]
type = ForwardFFT
buffer = NL_gr1
input = 'gr1_bulk_term'
[]
[NL_gr2]
type = ForwardFFT
buffer = NL_gr2
input = 'gr2_bulk_term'
[]
[NL_gr3]
type = ForwardFFT
buffer = NL_gr3
input = 'gr3_bulk_term'
[]
[NL_gr4]
type = ForwardFFT
buffer = NL_gr4
input = 'gr4_bulk_term'
[]
[NL_gr0_smooth]
type = ParsedCompute
buffer = NL_gr0_smooth
expression = 'smooth*NL_gr0'
inputs = 'smooth NL_gr0'
[]
[NL_gr1_smooth]
type = ParsedCompute
buffer = NL_gr1_smooth
expression = 'smooth*NL_gr1'
inputs = 'smooth NL_gr1'
[]
[NL_gr2_smooth]
type = ParsedCompute
buffer = NL_gr2_smooth
expression = 'smooth*NL_gr2'
inputs = 'smooth NL_gr2'
[]
[NL_gr3_smooth]
type = ParsedCompute
buffer = NL_gr3_smooth
expression = 'smooth*NL_gr3'
inputs = 'smooth NL_gr3'
[]
[NL_gr4_smooth]
type = ParsedCompute
buffer = NL_gr4_smooth
expression = 'smooth*NL_gr4'
inputs = 'smooth NL_gr4'
[]
# Properties for output
[grain_ID]
type = ParsedCompute
buffer = 'grain_ID'
expression = 'if(gr0>=max(gr1,max(gr2,max(gr3,gr4))), 0, if(gr1>=max(gr2,max(gr3,gr4)), 1, if(gr2>=max(gr3,gr4), 2, if(gr3>=gr4, 3, 4))))'
inputs = 'gr0 gr1 gr2 gr3 gr4'
[]
[grad_gr0]
type = GradientVector
buffer = grad_gr0
input = gr0
[]
[grad_gr1]
type = GradientVector
buffer = grad_gr1
input = gr1
[]
[grad_gr2]
type = GradientVector
buffer = grad_gr2
input = gr2
[]
[grad_gr3]
type = GradientVector
buffer = grad_gr3
input = gr3
[]
[grad_gr4]
type = GradientVector
buffer = grad_gr4
input = gr4
[]
[gradient_energy]
type = GradientEnergyDensity
buffer = gradient_energy
gradient_buffers = 'grad_gr0 grad_gr1 grad_gr2 grad_gr3 grad_gr4'
kappa = ${kappa}
[]
[total_energy]
type = ParsedCompute
buffer = 'total_energy'
expression = '${mu} * (${f0}) + gradient_energy'
inputs = 'gr0 gr1 gr2 gr3 gr4 gradient_energy'
[]
[]
[]
[Postprocessors]
[total_gb_energy]
type = TensorIntegralPostprocessor
buffer = total_energy
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'gr0 gr1 gr2 gr3 gr4'
reciprocal_buffer = 'gr0_bar gr1_bar gr2_bar gr3_bar gr4_bar'
linear_reciprocal = 'L_kappa_laplacian L_kappa_laplacian L_kappa_laplacian L_kappa_laplacian L_kappa_laplacian'
nonlinear_reciprocal = 'NL_gr0_smooth NL_gr1_smooth NL_gr2_smooth NL_gr3_smooth NL_gr4_smooth'
substeps = 1000
predictor_order = 1
corrector_order = 1
corrector_steps = 1
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'gr0 gr1 gr2 gr3 gr4 bnds grain_ID'
output_mode = 'NODE NODE NODE NODE NODE NODE CELL'
enable_hdf5 = true
transpose = true
[]
[]
[Executioner]
type = Transient
dt = 5
num_steps = 50
[]
[Outputs]
csv = true
execute_on = 'INITIAL TIMESTEP_END'
[]
(benchmarks/01_spinodal_decomposition/1a_solver.i)
[Domain]
dim = 2
nx = 200
ny = 200
xmax = 200
ymax = 200
device_names = 'cuda'
mesh_mode = DOMAIN
[]
[TensorBuffers]
[c]
map_to_aux_variable = c
[]
[cbar]
[]
[mu]
# map_to_aux_variable = mu
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
# postprocessing
[F]
[]
[Fgrad]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 5 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -10 # -kappa*M
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = 'rho_s*(c-c_alpha)^2*(c_beta-c)^2'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
derivatives = c
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[Postprocess]
[Fgrad]
type = FFTGradientSquare
buffer = Fgrad
input = c
factor = 1 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = 'rho_s * (c-c_alpha)^2 * (c_beta-c)^2 + Fgrad'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
inputs = 'c Fgrad'
[]
[]
[]
[UserObjects]
[terminator]
type = Terminator
expression = change<1e-4
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = c
substeps = 1000
history_size = 1
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[AuxVariables]
# [mu]
# family = MONOMIAL
# order = CONSTANT
# []
[c]
# family = MONOMIAL
# order = CONSTANT
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[change]
type = TensorIntegralChangePostprocessor
buffer = c
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 1000
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.1
dt = 1
[]
dtmax = 300
[]
[Outputs]
exodus = true
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(benchmarks/01_spinodal_decomposition/1a_implicit_fd.i)
#
# PFHub benchmark 1a (spinodal decomposition, square periodic domain) with the
# implicit finite-difference solver. Same problem as 1a.i:
#
# dc/dt = div(M grad(f'(c) - kappa Laplacian(c))), f = rho_s (c - c_alpha)^2 (c_beta - c)^2
#
# Backward Euler, with the biharmonic implicit and the double-well flux
# divergence explicit:
#
# (c - c^n)/dt + M kappa Laplacian(Laplacian(c)) = M Laplacian(f'(c^n))
#
# M = 5, kappa = 2, rho_s = 5, c_alpha = 0.3, c_beta = 0.7.
#
# substeps per time step, as in 1a_solver.i (each substep is one linear solve)
substeps = 1000
[Domain]
dim = 2
nx = 200
ny = 200
xmax = 200
ymax = 200
parallel_mode = REAL_SPACE
periodic_directions = 'X Y'
[]
[TensorBuffers]
[c]
[]
[dcdt]
[]
[bih_c]
[]
[mu]
[]
[rhs]
[]
# postprocessing
[lap_c]
[]
[F]
[]
[]
[TensorComputes]
[Initialize]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[]
[Solve]
# implicit operators
[dcdt]
type = TimeDerivativeOperator
buffer = dcdt
input = c
[]
[bih]
type = FiniteDifferenceBiharmonic
buffer = bih_c
input = c
factor = 10 # M * kappa
[]
# explicit source M Laplacian(f'(c^n))
[explicit]
[mu]
type = ParsedCompute
buffer = mu
expression = 'rho_s*(c-c_alpha)^2*(c_beta-c)^2'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
derivatives = c
inputs = c
[]
[rhs]
type = FiniteDifferenceLaplacian
buffer = rhs
input = mu
factor = 5 # M
[]
[]
[]
[Postprocess]
# On the periodic grid sum |grad c|^2 = -sum c Laplacian(c) for the 3-point
# Laplacian, so the gradient energy (kappa/2)|grad c|^2 integrates to the same
# total as -(kappa/2) c Laplacian(c).
[lap_c]
type = FiniteDifferenceLaplacian
buffer = lap_c
input = c
[]
[F]
type = ParsedCompute
buffer = F
expression = 'rho_s * (c-c_alpha)^2 * (c_beta-c)^2 - kappa / 2 * c * lap_c'
constant_names = 'rho_s c_alpha c_beta kappa'
constant_expressions = '5 0.3 0.7 2'
inputs = 'c lap_c'
[]
[]
[]
[TensorSolver]
type = ImplicitFDSolver
buffer = c
operators = 'dcdt bih'
source = rhs
root_compute = explicit
substeps = ${substeps}
[]
[UserObjects]
[terminator]
type = Terminator
expression = change<1e-4
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[change]
type = TensorIntegralChangePostprocessor
buffer = c
[]
# cumulative wall time of the run (s)
[wall_time]
type = PerfGraphData
section_name = Root
data_type = TOTAL
[]
[]
[Problem]
type = TensorProblem
[]
[Executioner]
type = Transient
num_steps = 1000
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.1
dt = 1
[]
dtmax = 300
[]
[TensorOutputs]
[xdmf]
type = XDMFTensorOutput
buffer = 'c mu'
enable_hdf5 = true
[]
[]
[Outputs]
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]
(test/tests/solvers/diagonal.i)
#
# Simple Cahn-Hilliard solve on a 2D grid.
#
[Domain]
dim = 2
nx = 150
ny = 150
xmax = '${fparse pi*2}'
ymax = '${fparse pi*2}'
mesh_mode = DUMMY
[]
[GlobalParams]
constant_names = 'A B'
constant_expressions = '1 3.5'
[]
[TensorComputes]
[Initialize]
[u]
type = ParsedCompute
buffer = u
extra_symbols = true
expression = 'sin(x)*sin(y)'
expand = REAL
[]
[v]
type = ConstantTensor
buffer = v
real = 0
[]
# precompute fixed factors for the solve
[Du]
type = ReciprocalLaplacianFactor
factor = 1e-2
buffer = Du
[]
[Dv]
type = ReciprocalLaplacianFactor
factor = 1e-3
buffer = Dv
[]
[]
[Solve]
[u_bar]
type = ForwardFFT
buffer = u_bar
input = u
[]
[v_bar]
type = ForwardFFT
buffer = v_bar
input = v
[]
[source_u]
type = ParsedCompute
buffer = source_u
expression = 'A - (B+1)*u +u^2*v'
inputs = 'u v'
[]
[source_u_bar]
type = ForwardFFT
buffer = source_u_bar
input = source_u
[]
[source_v]
type = ParsedCompute
buffer = source_v
expression = 'B*u - u^2*v'
inputs = 'u v'
[]
[source_v_bar]
type = ForwardFFT
buffer = source_v_bar
input = source_v
[]
[]
[]
[TensorSolver]
type = AdamsBashforthMoulton
buffer = 'u v'
reciprocal_buffer = 'u_bar v_bar'
linear_reciprocal = 'Du Dv'
nonlinear_reciprocal = 'source_u_bar source_v_bar'
substeps = ${ss}
corrector_steps = ${cs}
predictor_order = ${order}
corrector_order = ${order}
[]
[Problem]
type = TensorProblem
[]
[Postprocessors]
[u_min]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MIN
[]
[u_max]
type = TensorExtremeValuePostprocessor
buffer = u
value_type = MAX
[]
[v_min]
type = TensorExtremeValuePostprocessor
buffer = v
value_type = MIN
[]
[v_max]
type = TensorExtremeValuePostprocessor
buffer = v
value_type = MAX
[]
[U]
type = TensorIntegralPostprocessor
buffer = u
[]
[V]
type = TensorIntegralPostprocessor
buffer = v
[]
[]
[Executioner]
type = Transient
num_steps = 25
dt = 0.5
[]
[Outputs]
file_base = diagonal_${ss}_${cs}_${order}
csv = true
[]
(benchmarks/01_spinodal_decomposition/1b.i)
[Domain]
dim = 2
nx = 200
ny = 200
xmin = -10
ymin = -10
xmax = 210
ymax = 210
device_names = 'cuda'
mesh_mode = DOMAIN
[]
[TensorBuffers]
[domain]
map_to_aux_variable = domain
[]
[c]
map_to_aux_variable = c
[]
[cbar]
[]
[mu]
# map_to_aux_variable = mu
[]
[mubar]
[]
[Mbarmubar]
[]
# constant tensors
[Mbar]
[]
[kappabarbar]
[]
# postprocessing
[F]
[]
[Fgrad]
[]
[]
[TensorComputes]
[Initialize]
[domain]
type = ParsedCompute
buffer = domain
extra_symbols = true
expression = 'w:=3;dx:=max(tanh(-x/w),tanh((x-200)/w)); dy:=max(tanh(-y/w),tanh((y-200)/w));1-0.999999999*max(dx,dy)'
[]
[c]
type = ParsedCompute
buffer = c
extra_symbols = true
expression = 'c0+epsilon*(cos(0.105*x)*cos(0.11*y)+(cos(0.13*x)*cos(0.087*y))^2+cos(0.025*x-0.15*y)*cos(0.07*x-0.02*y))'
constant_names = 'c0 epsilon'
constant_expressions = '0.5 0.01'
[]
[Mbar]
type = ReciprocalLaplacianFactor
factor = 5 # Mobility
buffer = Mbar
[]
[kappabarbar]
type = ReciprocalLaplacianSquareFactor
factor = -10 # -kappa*M
buffer = kappabarbar
[]
[]
[Solve]
[mu]
type = ParsedCompute
buffer = mu
expression = 'rho_s*(c-c_alpha)^2*(c_beta-c)^2'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
derivatives = c
inputs = c
[]
[mubar]
type = ForwardFFT
buffer = mubar
input = mu
[]
[Mbarmubar]
type = ParsedCompute
buffer = Mbarmubar
expression = 'Mbar*mubar'
inputs = 'Mbar mubar'
[]
[cbar]
type = ForwardFFT
buffer = cbar
input = c
[]
[]
[Postprocess]
[Fgrad]
type = FFTGradientSquare
buffer = Fgrad
input = c
factor = 1 # kappa/2
[]
[F]
type = ParsedCompute
buffer = F
expression = 'rho_s * (c-c_alpha)^2 * (c_beta-c)^2 + Fgrad'
constant_names = 'rho_s c_alpha c_beta'
constant_expressions = '5 0.3 0.7'
inputs = 'c Fgrad'
[]
[]
[]
[UserObjects]
[terminator]
type = Terminator
expression = change<1e-4
[]
[]
[TensorTimeIntegrators]
[c]
type = FFTSemiImplicit
buffer = c
history_size = 1
reciprocal_buffer = cbar
linear_reciprocal = kappabarbar
nonlinear_reciprocal = Mbarmubar
[]
[]
[AuxVariables]
# [mu]
# family = MONOMIAL
# order = CONSTANT
# []
[c]
# family = MONOMIAL
# order = CONSTANT
[]
[domain]
[]
[]
[Postprocessors]
[min_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MIN
execute_on = 'TIMESTEP_END'
[]
[max_c]
type = TensorExtremeValuePostprocessor
buffer = c
value_type = MAX
execute_on = 'TIMESTEP_END'
[]
[F]
type = TensorIntegralPostprocessor
buffer = F
[]
[change]
type = TensorIntegralChangePostprocessor
buffer = c
[]
[]
[Problem]
type = TensorProblem
spectral_solve_substeps = 1000
[]
[Executioner]
type = Transient
num_steps = 1 # 1000
[TimeStepper]
type = IterationAdaptiveDT
growth_factor = 1.1
dt = 1
[]
dtmax = 300
[]
[Outputs]
exodus = true
csv = true
perf_graph = true
execute_on = 'TIMESTEP_END'
[]