###############################################################################
# WaterTAP Copyright (c) 2021, The Regents of the University of California,
# through Lawrence Berkeley National Laboratory, Oak Ridge National
# Laboratory, National Renewable Energy Laboratory, and National Energy
# Technology Laboratory (subject to receipt of any required approvals from
# the U.S. Dept. of Energy). All rights reserved.
#
# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license
# information, respectively. These files are also available online at the URL
# "https://github.com/watertap-org/watertap/"
#
###############################################################################
"""
Simple property package for selective oil permeation
"""
from pyomo.environ import Constraint, Var, Param, NonNegativeReals, Suffix
from pyomo.environ import units
# Import IDAES cores
from idaes.core import (
declare_process_block_class,
MaterialFlowBasis,
PhysicalParameterBlock,
StateBlockData,
StateBlock,
MaterialBalanceType,
EnergyBalanceType,
)
from idaes.core.base.components import Component
from idaes.core.base.phases import LiquidPhase
from idaes.core.util.initialization import (
fix_state_vars,
revert_state_vars,
solve_indexed_blocks,
)
from idaes.core.util.misc import add_object_reference
from idaes.core.util.model_statistics import (
degrees_of_freedom,
number_unfixed_variables,
)
from idaes.core.util.exceptions import PropertyPackageError
import idaes.core.util.scaling as iscale
import idaes.logger as idaeslog
from idaes.core.solvers import get_solver
from watertap.core.util.scaling import transform_property_constraints
# Set up logger
_log = idaeslog.getLogger(__name__)
# this first class sets up the property package and creates a central parameter block
[docs]@declare_process_block_class("SopParameterBlock")
class SopParameterData(PhysicalParameterBlock):
CONFIG = PhysicalParameterBlock.CONFIG()
[docs] def build(self):
"""
Callable method for Block construction.
"""
super(SopParameterData, self).build()
self._state_block_class = SopStateBlock
# phases
self.Liq = LiquidPhase()
# components
self.H2O = Component()
self.oil = Component()
# ---default scaling---
self.set_default_scaling("temperature", 1e-2)
self.set_default_scaling("pressure", 1e-6)
self.set_default_scaling("dens_mass_phase", 1e-3, index="Liq")
# parameters
self.visc_d_phase_comp = Param(
self.phase_list,
self.component_list,
mutable=True,
initialize={("Liq", "H2O"): 1e-3, ("Liq", "oil"): 3.56e-3},
units=units.kg * units.m**-1 * units.s**-1,
doc="Dynamic viscosity",
)
self.dens_mass_phase_comp = Param(
self.phase_list,
self.component_list,
mutable=True,
initialize={("Liq", "H2O"): 1e3, ("Liq", "oil"): 780},
units=units.kg * units.m**-3,
doc="Component mass density",
)
# this second class contains methods that are applied to state blocks as a whole,
# rather than individual elements of indexed state blocks. Essentially it just includes
# the initialization routine
class _SopStateBlock(StateBlock):
def initialize(
self,
state_args=None,
state_vars_fixed=False,
hold_state=False,
outlvl=idaeslog.NOTSET,
solver=None,
optarg=None,
):
"""
Initialization routine for property package.
Keyword Arguments:
state_args : Dictionary with initial guesses for the state vars
chosen. Note that if this method is triggered
through the control volume, and if initial guesses
were not provided at the unit model level, the
control volume passes the inlet values as initial
guess.The keys for the state_args dictionary are:
flow_mass_phase_comp : value at which to initialize
phase component flows
pressure : value at which to initialize pressure
temperature : value at which to initialize temperature
state_vars_fixed: Flag to denote if state vars have already been
fixed.
- True - states have already been fixed by the
control volume 1D. Control volume 0D
does not fix the state vars, so will
be False if this state block is used
with 0D blocks.
- False - states have not been fixed. The state
block will deal with fixing/unfixing.
hold_state : flag indicating whether the initialization routine
should unfix any state variables fixed during
initialization (default=False).
- True - states variables are not unfixed, and
a dict of returned containing flags for
which states were fixed during
initialization.
- False - state variables are unfixed after
initialization by calling the
release_state method
outlvl : sets output level of initialization routine (default=idaeslog.NOTSET)
solver : Solver object to use during initialization if None is provided
it will use the default solver for IDAES (default = None)
optarg : solver options dictionary object (default=None)
Returns:
If hold_states is True, returns a dict containing flags for
which states were fixed during initialization.
"""
# Get loggers
init_log = idaeslog.getInitLogger(self.name, outlvl, tag="properties")
solve_log = idaeslog.getSolveLogger(self.name, outlvl, tag="properties")
# Set solver and options
opt = get_solver(solver, optarg)
# Fix state variables
flags = fix_state_vars(self, state_args)
# Check when the state vars are fixed already result in dof 0
for k in self.keys():
dof = degrees_of_freedom(self[k])
if dof != 0:
raise PropertyPackageError(
"\nWhile initializing {sb_name}, the degrees of freedom "
"are {dof}, when zero is required. \nInitialization assumes "
"that the state variables should be fixed and that no other "
"variables are fixed. \nIf other properties have a "
"predetermined value, use the calculate_state method "
"before using initialize to determine the values for "
"the state variables and avoid fixing the property variables."
"".format(sb_name=self.name, dof=dof)
)
# ---------------------------------------------------------------------
skip_solve = True # skip solve if only state variables are present
for k in self.keys():
if number_unfixed_variables(self[k]) != 0:
skip_solve = False
if not skip_solve:
# Initialize properties
with idaeslog.solver_log(solve_log, idaeslog.DEBUG) as slc:
results = solve_indexed_blocks(opt, [self], tee=slc.tee)
init_log.info_high(
"Property initialization: {}.".format(idaeslog.condition(results))
)
# ---------------------------------------------------------------------
# If input block, return flags, else release state
if state_vars_fixed is False:
if hold_state is True:
return flags
else:
self.release_state(flags)
def release_state(self, flags, outlvl=idaeslog.NOTSET):
"""
Method to release state variables fixed during initialisation.
Keyword Arguments:
flags : dict containing information of which state variables
were fixed during initialization, and should now be
unfixed. This dict is returned by initialize if
hold_state=True.
outlvl : sets output level of of logging
"""
# Unfix state variables
init_log = idaeslog.getInitLogger(self.name, outlvl, tag="properties")
revert_state_vars(self, flags)
init_log.info_high("{} State Released.".format(self.name))
# this third class, provides the instructions to create state blocks
[docs]@declare_process_block_class("SopStateBlock", block_class=_SopStateBlock)
class SopStateBlockData(StateBlockData):
[docs] def build(self):
"""Callable method for Block construction."""
super(SopStateBlockData, self).build()
self.scaling_factor = Suffix(direction=Suffix.EXPORT)
# first we create the state variables
self.flow_mass_phase_comp = Var(
self.params.phase_list,
self.params.component_list,
initialize={("Liq", "H2O"): 1, ("Liq", "oil"): 0.01},
bounds=(0, None),
domain=NonNegativeReals,
units=units.kg / units.s,
doc="Mass flow rate",
)
self.temperature = Var(
initialize=298.15,
bounds=(0, None),
domain=NonNegativeReals,
units=units.degK,
doc="State temperature",
)
self.pressure = Var(
initialize=101325,
bounds=(0, None),
domain=NonNegativeReals,
units=units.Pa,
doc="State pressure",
)
# -----------------------------------------------------------------------------
# Property Methods
# these property methods build variables and constraints on demand (i.e. only when asked
# for by a user or unit model)
def _visc_d_phase_comp(self):
add_object_reference(self, "visc_d_phase_comp", self.params.visc_d_phase_comp)
def _dens_mass_phase_comp(self):
add_object_reference(
self, "dens_mass_phase_comp", self.params.dens_mass_phase_comp
)
def _mass_frac_phase_comp(self):
self.mass_frac_phase_comp = Var(
self.params.phase_list,
self.params.component_list,
initialize=0.1,
bounds=(0, 1),
domain=NonNegativeReals,
units=units.dimensionless,
doc="Mass fraction",
)
def rule_mass_frac_phase_comp(b, p, j):
return (
b.mass_frac_phase_comp[p, j] * b.flow_mass_phase[p]
== b.flow_mass_phase_comp[p, j]
)
self.eq_mass_frac_phase_comp = Constraint(
self.params.phase_list,
self.params.component_list,
rule=rule_mass_frac_phase_comp,
)
def _flow_vol_phase_comp(self):
self.flow_vol_phase_comp = Var(
self.params.phase_list,
self.params.component_list,
initialize=1e-6,
bounds=(0, None),
domain=NonNegativeReals,
units=units.m**3 / units.s,
doc="Component volumetric flowrate",
)
def rule_flow_vol_phase_comp(b, p, j):
return (
b.flow_vol_phase_comp[p, j] * b.dens_mass_phase_comp[p, j]
== b.flow_mass_phase_comp[p, j]
)
self.eq_flow_vol_phase_comp = Constraint(
self.params.phase_list,
self.params.component_list,
rule=rule_flow_vol_phase_comp,
)
def _flow_vol_phase(self):
self.flow_vol_phase = Var(
self.params.phase_list,
initialize=1e-3,
bounds=(0, None),
domain=NonNegativeReals,
units=units.m**3 / units.s,
doc="Phase volumetric flow rate",
)
def rule_flow_vol_phase(b, p):
return b.flow_vol_phase[p] == sum(
b.flow_vol_phase_comp[p, j] for j in b.params.component_list
)
self.eq_flow_vol_phase = Constraint(
self.params.phase_list, rule=rule_flow_vol_phase
)
def _flow_vol(self):
self.flow_vol = Var(
initialize=1e-3,
bounds=(0, None),
domain=NonNegativeReals,
units=units.m**3 / units.s,
doc="Total volumetric flow rate",
)
def rule_flow_vol(b):
return b.flow_vol == sum(b.flow_vol_phase[p] for p in b.params.phase_list)
self.eq_flow_vol = Constraint(rule=rule_flow_vol)
def _flow_mass_phase(self):
self.flow_mass_phase = Var(
self.params.phase_list,
initialize=1e-3,
bounds=(0, None),
domain=NonNegativeReals,
units=units.kg / units.s,
doc="Mass flow rate",
)
def rule_flow_mass_phase(b, p):
return b.flow_mass_phase[p] == sum(
b.flow_mass_phase_comp[p, j] for j in b.params.component_list
)
self.eq_flow_mass_phase = Constraint(
self.params.phase_list, rule=rule_flow_mass_phase
)
def _dens_mass_phase(self):
self.dens_mass_phase = Var(
self.params.phase_list,
initialize=1e3,
bounds=(0, None),
domain=NonNegativeReals,
units=units.kg * units.m**-3,
doc="Mass density",
)
def rule_dens_mass_phase(b, p):
return b.dens_mass_phase[p] * b.flow_vol_phase[p] == b.flow_mass_phase[p]
self.eq_dens_mass_phase = Constraint(
self.params.phase_list, rule=rule_dens_mass_phase
)
def _vol_frac_phase_comp(self):
self.vol_frac_phase_comp = Var(
self.params.phase_list,
self.params.component_list,
initialize=0.1,
bounds=(0, 1),
domain=NonNegativeReals,
units=units.dimensionless,
doc="Volumetric fraction",
)
def rule_vol_frac_phase_comp(b, p, j):
return (
b.vol_frac_phase_comp[p, j] * b.flow_vol_phase[p]
== b.flow_vol_phase_comp[p, j]
)
self.eq_vol_frac_phase_comp = Constraint(
self.params.phase_list,
self.params.component_list,
rule=rule_vol_frac_phase_comp,
)
def _conc_mass_phase_comp(self):
self.conc_mass_phase_comp = Var(
self.params.phase_list,
self.params.component_list,
initialize=1,
bounds=(0, None),
domain=NonNegativeReals,
units=units.kg / units.m**3,
doc="Mass concentration",
)
def rule_conc_mass_phase_comp(b, p, j):
return (
b.conc_mass_phase_comp[p, j]
== b.mass_frac_phase_comp[p, j] * b.dens_mass_phase[p]
)
self.eq_conc_mass_phase_comp = Constraint(
self.params.phase_list,
self.params.component_list,
rule=rule_conc_mass_phase_comp,
)
# -----------------------------------------------------------------------------
# General Methods
# NOTE: For scaling in the control volume to work properly, these methods must
# return a pyomo Var or Expression
[docs] def get_material_flow_terms(self, p, j):
"""Create material flow terms for control volume."""
return self.flow_mass_phase_comp[p, j]
def default_material_balance_type(self):
return MaterialBalanceType.componentTotal
def default_energy_balance_type(self):
return EnergyBalanceType.none
[docs] def get_material_flow_basis(self):
return MaterialFlowBasis.mass
[docs] def define_state_vars(self):
"""Define state vars."""
return {
"flow_mass_phase_comp": self.flow_mass_phase_comp,
"temperature": self.temperature,
"pressure": self.pressure,
}
# -----------------------------------------------------------------------------
# Scaling methods
def calculate_scaling_factors(self):
super().calculate_scaling_factors()
# setting scaling factors for variables
# default scaling factors have already been set with
# idaes.core.property_base.calculate_scaling_factors()
sf_dens_mass_phase = {}
for p in self.params.phase_list:
if self.is_property_constructed("dens_mass_phase"):
sf_dens_mass_phase[p] = iscale.get_scaling_factor(
self.dens_mass_phase[p]
)
else:
sf_dens_mass_phase[p] = self.params.get_default_scaling(
"dens_mass_phase", index=p
)
# these variables should have user input
for p in self.params.phase_list:
if (
iscale.get_scaling_factor(
self.flow_mass_phase_comp[p, "H2O"], warning=True
)
is None
):
iscale.set_scaling_factor(self.flow_mass_phase_comp[p, "H2O"], 1)
if (
iscale.get_scaling_factor(
self.flow_mass_phase_comp[p, "oil"], warning=True
)
is None
):
iscale.set_scaling_factor(self.flow_mass_phase_comp[p, "oil"], 1e1)
sf_flow_mass_phase = {}
for p in self.params.phase_list:
sf_flow_mass_phase[p] = 1 / (
1 / iscale.get_scaling_factor(self.flow_mass_phase_comp[p, "H2O"])
+ 1 / iscale.get_scaling_factor(self.flow_mass_phase_comp[p, "oil"])
)
# these variables do not typically require user input
if self.is_property_constructed("flow_mass_phase"):
for p in self.params.phase_list:
iscale.set_scaling_factor(
self.flow_mass_phase[p], sf_flow_mass_phase[p]
)
if self.is_property_constructed("mass_frac_phase_comp"):
for p in self.params.phase_list:
for j in self.params.component_list:
sf = (
iscale.get_scaling_factor(self.flow_mass_phase_comp[p, j])
/ sf_flow_mass_phase[p]
)
iscale.set_scaling_factor(self.mass_frac_phase_comp[p, j], sf)
if self.is_property_constructed("flow_vol_phase_comp"):
for p in self.params.phase_list:
for j in self.params.component_list:
sf = (
iscale.get_scaling_factor(self.flow_mass_phase_comp[p, j])
/ sf_dens_mass_phase[p]
)
iscale.set_scaling_factor(self.flow_vol_phase_comp[p, j], sf)
if self.is_property_constructed("flow_vol_phase"):
for p in self.params.phase_list:
sf = sf_flow_mass_phase[p] / sf_dens_mass_phase[p]
iscale.set_scaling_factor(self.flow_vol_phase[p], sf)
if self.is_property_constructed("flow_vol"):
sf = sum(
sf_flow_mass_phase[p] / sf_dens_mass_phase[p]
for p in self.params.phase_list
)
iscale.set_scaling_factor(self.flow_vol, sf)
if self.is_property_constructed("vol_frac_phase_comp"):
for p in self.params.phase_list:
for j in self.params.component_list:
sf = iscale.get_scaling_factor(
self.flow_vol_phase_comp[p, j]
) / iscale.get_scaling_factor(self.flow_vol_phase[p])
iscale.set_scaling_factor(self.vol_frac_phase_comp[p, j], sf)
if self.is_property_constructed("conc_mass_phase_comp"):
for p in self.params.phase_list:
for j in self.params.component_list:
sf = (
iscale.get_scaling_factor(self.mass_frac_phase_comp[p, j])
* sf_dens_mass_phase[p]
)
iscale.set_scaling_factor(self.conc_mass_phase_comp[p, j], sf)
# transform property constraints
transform_property_constraints(self)