## [literature data][1]
## [1]: http://dx.doi.org/10.1002/(SICI)1097-4628(19961017)62:3<567::AID-APP14>3.0.CO;2-W
par3 = [3.32e-8, 42.9e3, 2.32, 1.4, X_gel]
## based on [literature data](http://dx.doi.org/10.1002/aic.690280213), but
## gel point changed to 0.5 (Baser and Khakhar)
par4 = [4.1e-8, 38.3e3, 4.0, -2.0, X_gel]
## [literature data](http://doi.wiley.com/10.1002/aic.12002)
par5 = [3.1e0, 2.24e3, 3.5, -2.0, X_gel]
## [literature data](http://doi.wiley.com/10.1002/pen.760311605)
par6 = [1.6e-7, 44.9e3, 1.29, 1.86, X_gel]
## based on BASF data for 100 s^-1 shear rate, you must use 0.5 for gel point
par7 = [2.49707805e-13, 6.88758966e+04, 1.03553549e+01, -1.46554648e+01, 0.5]
## based on BASF data for 1 s^-1 shear rate, you must use 0.5 for gel point
par8 = [7.03759789e-17, 8.91382466e+04, 1.32209736e+01, -1.82153953e+01, 0.5]
## Surrogate model for polymer viscosity
#
# Forward mapping model is used.
m_polymerViscosity = ForwardMappingModel(
_id='polymerViscosity',
surrogateFunction=f_polymerViscosity,
substituteModels=[],
parameters=par,
)
'min': -9e99,
'max': +9e99,
'argPos': 1
},
},
indices={
'A': species,
},
)
## Surrogate model for thermal conductivity of blowing agent
#
# Forward mapping model is used.
m_CO2_thermal_conductivity = ForwardMappingModel(
_id='gas_thermal_conductivity[A=CO2]',
surrogateFunction=f_gas_thermal_conductivity,
substituteModels=[],
parameters=[0.0807e-3, -6.96e-3],
)
## Surrogate model for thermal conductivity of blowing agent
#
# Forward mapping model is used.
m_Air_thermal_conductivity = ForwardMappingModel(
_id='gas_thermal_conductivity[A=Air]',
surrogateFunction=f_gas_thermal_conductivity,
substituteModels=[],
parameters=[0.0720e-3, 4.23e-3],
)
## Surrogate model for thermal conductivity of blowing agent
#
Modena is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
details.
You should have received a copy of the GNU General Public License along
with Modena. If not, see <http://www.gnu.org/licenses/>.
@endcond'''
"""
@ingroup mod_kinetics
@namespace Kinetics.Kinetics
@todo Document
@author Andreas Daiss
@copyright 2014-2016, MoDeNa Project. GNU Public License.
@ingroup app_foaming
"""
import os
from modena import ForwardMappingModel
from PrediciKinetics import PrediciKinetics
k = PrediciKinetics(
_id='RF-1-public',
fileName=os.path.dirname(os.path.abspath(__file__)) + '/RF-1-public.c',
)
m = ForwardMappingModel(_id='RF-1-public',
surrogateFunction=k,
substituteModels=[],
importFrom='Kinetics.PrediciKinetics')
const double* inputs,
double *outputs
)
{
{% block variables %}{% endblock %}
const double R = parameters[0];
outputs[0] = p0/R/T0;
}
''',
# These are global bounds for the function
inputs={
'p0': { 'min': 0, 'max': 9e99 },
'T0': { 'min': 0, 'max': 9e99 },
},
outputs={
'rho0': { 'min': 9e99, 'max': -9e99, 'argPos': 0 },
},
parameters={
'R': { 'min': 0.0, 'max': 9e99, 'argPos': 0 }
},
)
m = ForwardMappingModel(
_id= 'idealGas',
surrogateFunction= f,
substituteModels= [ ],
parameters= [ 287.0 ],
)
parameters={
'R': { 'min': 0.0, 'max': 9e99, 'argPos': 0 }
},
)
m1 = ForwardMappingModel(
_id= 'idealGas',
#exactTask= Strategy.InitialDataPoints(),
surrogateFunction= f2,
substituteModels= [ ],
parameters= [ 287.0 ],
inputs={
'p0': { 'min': 0, 'max': 9e99 },
'T0': { 'min': 0, 'max': 9e99 },
},
outputs={
'rho0': {'min': 0, 'max': 9e99 },
},
initialisationStrategy= Strategy.InitialData(
initialData={
'p0' : [1,2,3,4,5],
'T0' : [296,297,298,299,300],
'rho0' : [0.000011771353234, 0.00002346343809758, 0.00003507705259219, 0.00004661298404, 0.0000580720092915],
},
),
)
m2 = BackwardMappingModel(
_id= 'idealGasBackward',
exactTask= Strategy.InitialDataPoints(),
surrogateFunction= f1,
parameterFittingStrategy=parameterFittingStrategy)
m_solubilityCyclopentanePU = BackwardMappingModel(
_id='Solubility[A=CyP,B=2]',
surrogateFunction=f2,
exactTask=SolubilityExactSim(),
substituteModels=[],
initialisationStrategy=Strategy.InitialPoints(initialPoints={
'T': [270, 320, 370, 420],
'xl1': [1.1e-3, 1.0e-3, 1.0e-3, 1.0e-4],
'xl2': [0.9989, 0.999, 0.999, 0.9999],
}, ),
outOfBoundsStrategy=outOfBoundsStrategy,
parameterFittingStrategy=parameterFittingStrategy)
m_solubilityOptPU = ForwardMappingModel(
_id='Solubility[A=Opt,B=2]',
surrogateFunction=f2,
substituteModels=[],
parameters=[10.0, -0.0182038808728673, 0.0],
)
m_solubilitySolPU = ForwardMappingModel(
_id='Solubility[A=Sol,B=2]',
surrogateFunction=f2,
substituteModels=[],
parameters=[10.0, -0.0182038808728673, 0.0],
)
m_solubilityO2PU = BackwardMappingModel(
_id='Solubility[A=O2,B=2]',
surrogateFunction=f2,
exactTask=SolubilityExactSim(),
substituteModels=[],
initialisationStrategy=Strategy.InitialPoints(initialPoints={
'T': [270, 320, 370, 420],
'param0': { 'min': 1e-12, 'max': 1E1, 'argPos': 0 },
'param1': { 'min': -1e-1, 'max': 1e-1, 'argPos': 1 },
'param2': { 'min': -1e-1, 'max': 1e-1, 'argPos': 2 },
'param3': { 'min': -1e-1, 'max': 1e-1, 'argPos': 3 },
}
fR11Baser = CFunction(Ccode=CcodeR11Baser,
inputs=inputsExp,
outputs=outputs,
parameters=parameters4
)
## [R11, Baser](http://dx.doi.org/10.1002/pen.760340804)
parR11Baser = [1e-7, 4.2934, 203.3556, 40.016]
m_solubilityR11Baser = ForwardMappingModel(
_id='SolubilityR11Baser',
surrogateFunction=fR11Baser,
substituteModels=[],
parameters=parR11Baser,
inputs=inputsExp,
outputs=outputs,
)
CcodeCO2Baser='''
#include "modena.h"
#include "math.h"
void surroSolubilityCO2Baser
(
const modena_model_t* model,
const double* inputs,
double *outputs
)
{
{% block variables %}{% endblock %}
# These are global bounds for the function
inputs={
'T': {'min': 273, 'max': 550},
},
outputs={
'polymer_thermal_conductivity': {
'min': 0, 'max': +9e99, 'argPos': 0
},
},
parameters={
'param0': {'min': -9e99, 'max': +9e99, 'argPos': 0},
'param1': {'min': -9e99, 'max': +9e99, 'argPos': 1},
},
)
## Surrogate model for thermal conductivity of polyurethane
#
# Forward mapping model is used.
m_polymer_thermal_conductivity = ForwardMappingModel(
_id='polymer_thermal_conductivity',
surrogateFunction=f_polymer_thermal_conductivity,
substituteModels=[],
parameters=[0.198e-3, 131.08e-3],
inputs={
'T': {'min': 273, 'max': 450},
},
outputs={
'polymer_thermal_conductivity': {'min': 0, 'max': +9e99},
},
)
'max': +9e99,
'argPos': 3
},
},
)
## Surrogate model for density_reaction_mixture
#
# Forward mapping model is used.
m = ForwardMappingModel(
_id='density_reaction_mixture',
surrogateFunction=f,
substituteModels=[],
parameters=[-0.0006, 1287.8, -0.000048, 992.8],
inputs={
'T': {
'min': 273,
'max': 450
},
'XOH': {
'min': 0,
'max': 1
},
},
outputs={
'density_reaction_mixtureSM': {
'min': 0,
'max': 8000.0
},
},
)
'min': -9e99,
'max': +9e99,
'argPos': 0
},
'C2': {
'min': -9e99,
'max': +9e99,
'argPos': 1
},
},
)
# -------------------------- Surrogate Models ------------------------------- #
m_forward = ForwardMappingModel(
_id='FoamElasticModulus',
surrogateFunction=f_ludwigshafen,
substituteModels=[],
parameters=[0, 1], # TODO: Use real values from Ludwigshafen presentation
)
m_backward = BackwardMappingModel(
_id='FoamElasticModulus_TEST',
surrogateFunction=f_backward,
exactTask=MechanicalPropertiesExactSim(),
substituteModels=[],
initialisationStrategy=Strategy.InitialData(
initialData={
'rho': [
30.2, 60, 120, 240, 30.2, 60, 120, 240, 30.2, 30.2, 30.2, 30.2,
30.2, 30.2, 30.2
],
'strut_content': [
},
},
parameters={
'param0': {
'min': -9e99,
'max': +9e99,
'argPos': 0
},
'param1': {
'min': -9e99,
'max': +9e99,
'argPos': 1
},
'param2': {
'min': -9e99,
'max': +9e99,
'argPos': 2
},
},
)
## Surrogate model for density_reaction_mixture
#
# Forward mapping model is used.
m = ForwardMappingModel(
_id='strutContent',
surrogateFunction=f,
substituteModels=[],
parameters=[0.06115509, -0.72513392, 1.],
)
'min': -9e99,
'max': +9e99,
'argPos': 0
},
'param1': {
'min': 0.0,
'max': +9e99,
'argPos': 1
},
'param2': {
'min': -9e99,
'max': +9e99,
'argPos': 2
},
'param3': {
'min': 0.0,
'max': +9e99,
'argPos': 3
},
},
)
## Surrogate model for density_reaction_mixture
#
# Forward mapping model is used.
m = ForwardMappingModel(
_id='density_reaction_mixture',
surrogateFunction=f,
substituteModels=[],
parameters=[-0.0006, 1287.8, -0.000048, 992.8],
)
## based on [literature data](http://dx.doi.org/10.1002/aic.690280213), but
## gel point changed to 0.5 (Baser and Khakhar)
par4 = [4.1e-8, 38.3e3, 4.0, -2.0, 0.5]
## Surrogate model for polymer viscosity
#
# Forward mapping model is used.
m_polymerViscosity = ForwardMappingModel(
_id='polymerViscosity',
surrogateFunction=f_polymerViscosity,
substituteModels=[],
parameters=par4,
inputs={
'T': {
'min': 200,
'max': 450
},
'X': {
'min': 0,
'max': 1
},
},
outputs={
'mu': {
'min': 0,
'max': +9e99
},
},
)
},
},
parameters={
'param0': {
'min': -9e99,
'max': +9e99,
'argPos': 0
},
'param1': {
'min': -9e99,
'max': +9e99,
'argPos': 1
},
'param2': {
'min': -9e99,
'max': +9e99,
'argPos': 2
},
},
)
## Surrogate model for thermal conductivity of mixture of blowing agents
#
# Forward mapping model is used.
m_gasMixtureConductivity = ForwardMappingModel(
_id='gasMixtureConductivity',
surrogateFunction=f_gasMixtureConductivity,
substituteModels=gasConductivity.substituteModels,
parameters=[1, 1, 1],
)
'diffusivity': {'min': 0, 'max': +9e99, 'argPos': 0},
},
parameters={
'param0[A]': {'min': 0.0, 'max': +9e99, 'argPos': 0},
'param1[A]': {'min': 0.0, 'max': +9e99, 'argPos': 1},
},
indices={
'A': species,
},
)
## Surrogate model for diffusivity
#
# Forward mapping model is used.
m_CO2_diffusivity = ForwardMappingModel(
_id='diffusivityPol[A=CO2]',
surrogateFunction=f_diffusivity,
substituteModels=[],
parameters=[0.00123, 6156],
)
## Surrogate model for diffusivity
#
# Forward mapping model is used.
m_CyP_diffusivity = ForwardMappingModel(
_id='diffusivityPol[A=CyP]',
surrogateFunction=f_diffusivity,
substituteModels=[],
parameters=[1.7e-7, 4236],
)
## Surrogate model for diffusivity
#
# Forward mapping model is used.
m_N2_diffusivity = ForwardMappingModel(
'min': -9e99,
'max': +9e99,
'argPos': 1
},
},
indices={
'A': species,
},
)
## Surrogate model for thermal conductivity of blowing agent
#
# Forward mapping model is used.
m_CO2_thermal_conductivity = ForwardMappingModel(
_id='gas_thermal_conductivity[A=CO2]',
surrogateFunction=f_gas_thermal_conductivity,
substituteModels=[],
parameters=[0.0807e-3, -6.96e-3],
)
## Surrogate model for thermal conductivity of blowing agent
#
# Forward mapping model is used.
m_Air_thermal_conductivity = ForwardMappingModel(
_id='gas_thermal_conductivity[A=Air]',
surrogateFunction=f_gas_thermal_conductivity,
substituteModels=[],
parameters=[0.0720e-3, 4.23e-3],
)
## Surrogate model for thermal conductivity of blowing agent
#
Ccode=weightedAverageCode,
# These are global bounds for the function
inputs={
'T': {'min': 273, 'max': 550},
'x': {'index': gasConductivity.species, 'min': 0, 'max': 1},
'gas_thermal_conductivity': {'index': gasConductivity.species,
'min': 0, 'max': 1},
},
outputs={
'gasMixtureConductivity': {'min': 0, 'max': +9e99, 'argPos': 0},
},
parameters={
'param0': {'min': -9e99, 'max': +9e99, 'argPos': 0},
'param1': {'min': -9e99, 'max': +9e99, 'argPos': 1},
'param2': {'min': -9e99, 'max': +9e99, 'argPos': 2},
},
)
## Surrogate model for thermal conductivity of mixture of blowing agents
#
# Forward mapping model is used.
m_gasMixtureConductivity = ForwardMappingModel(
_id='gasMixtureConductivity',
surrogateFunction=f_gasMixtureConductivity,
substituteModels=[gasConductivity.m_CO2_thermal_conductivity,\
gasConductivity.m_CyP_thermal_conductivity,\
gasConductivity.m_O2_thermal_conductivity,\
gasConductivity.m_N2_thermal_conductivity],
parameters=[1, 1, 1],
)
#include "math.h"
void fullerEtAlDiffusion
(
const modena_model_t* model,
const double* inputs,
double *outputs
)
{
{% block variables %}{% endblock %}
const double WA = parameters[0];
const double VA = parameters[1];
const double WB = parameters[2];
const double VB = parameters[3];
outputs[0] = 1.011e-4*pow(T, 1.75)*pow(1.0/WA + 1.0/WB, 1.0/2.0);
outputs[0] /= p*(pow(pow(VA, 1.0/3.0) + pow(VB, 1.0/3.0), 2.0));
}
''',
)
m = ForwardMappingModel(
_id= 'fullerEtAlDiffusion[A=H2O,B=N2]',
surrogateFunction= f,
substituteModels= [ ],
parameters= [ 16, 9.44, 14, 11.38 ],
)
mu_ap = mu_car * f_t;
// printf("apparent viscosity %f", mu_ap);
outputs[0] = mu_ap;
}
''',
inputs={
'T': {'min': 0, 'max': 9e99 },
'shear': {'min': 0, 'max': 9e99 },
'X': {'min': 0, 'max': 1 },
'm0' : {'min': 0, 'max' : 9e99},
'm1' : {'min': 0, 'max' : 9e99},
'mu' : {'min': 0, 'max' : 9e99},
'ST' : {'min': 0, 'max' : 9e99},
'mu_car' : {'min': 0, 'max' : 9e99},
},
outputs={
'mu_ap': { 'min': 0, 'max': 9e99, 'argPos': 0 },
},
parameters={
'Rgas' : {'min': 8.31, 'max': 8.32, 'argPos': 0},
}
)
m = ForwardMappingModel(
_id='Rheology_Arrhenius',
surrogateFunction=f,
substituteModels=[ Rheology.m ],
parameters=[ 8.314 ],
)