#################################################################################
# The Institute for the Design of Advanced Energy Systems Integrated Platform
# Framework (IDAES IP) was produced under the DOE Institute for the
# Design of Advanced Energy Systems (IDAES).
#
# Copyright (c) 2018-2026 by the software owners: The Regents of the
# University of California, through Lawrence Berkeley National Laboratory,
# National Technology & Engineering Solutions of Sandia, LLC, Carnegie Mellon
# University, West Virginia University Research Corporation, et al.
# All rights reserved. Please see the files COPYRIGHT.md and LICENSE.md
# for full copyright and license information.
#################################################################################
"""
Unit model to adjust size of streams to represent, for example, a stream being split across several identical units,
which are then all modeled as a single IDAES unit
"""
from functools import partial
from pyomo.environ import (
Block,
PositiveReals,
units as pyunits,
Var,
)
from pyomo.network import Port
from pyomo.common.config import ConfigBlock, ConfigValue, In
from idaes.core import (
declare_process_block_class,
UnitModelBlockData,
useDefault,
)
from idaes.core.util.config import (
is_physical_parameter_block,
)
from idaes.core.base.var_like_expression import VarLikeExpression
from idaes.core.util.tables import create_stream_table_dataframe
import idaes.core.util.scaling as iscale
import idaes.logger as idaeslog
from idaes.models.unit_models.feed import FeedInitializer as StreamScalerInitializer
__author__ = "Douglas Allan, Tanner Polley"
# Set up logger
_log = idaeslog.getLogger(__name__)
[docs]
@declare_process_block_class("StreamScaler")
class StreamScalerData(UnitModelBlockData):
"""
Unit model to adjust size of streams to represent, for example, a stream being split across several identical units,
which are then all modeled as a single IDAES unit
"""
default_initializer = StreamScalerInitializer
CONFIG = ConfigBlock()
CONFIG.declare(
"dynamic",
ConfigValue(
domain=In([False]),
default=False,
description="Dynamic model flag - must be False",
doc="""Indicates whether this model will be dynamic or not,
**default** = False. Scaler blocks are always steady-state.""",
),
)
CONFIG.declare(
"has_holdup",
ConfigValue(
default=False,
domain=In([False]),
description="Holdup construction flag - must be False",
doc="Scaler blocks do not contain holdup, thus this must be False.",
),
)
CONFIG.declare(
"property_package",
ConfigValue(
default=useDefault,
domain=is_physical_parameter_block,
description="Property package to use for StreamScaler",
doc="""Property parameter object used to define property
calculations, **default** - useDefault.
**Valid values:** {
**useDefault** - use default package from parent model or flowsheet,
**PropertyParameterObject** - a PropertyParameterBlock object.}""",
),
)
CONFIG.declare(
"property_package_args",
ConfigBlock(
implicit=True,
description="Arguments to use for constructing property packages",
doc="""A ConfigBlock with arguments to be passed to a property
block(s) and used when constructing these,
**default** - None.
**Valid values:** {
see property package for documentation.}""",
),
)
[docs]
def build(self):
"""
General build method for StreamScalerData. This method calls a number
of sub-methods which automate the construction of expected attributes
of unit models.
Inheriting models should call `super().build`.
Args:
None
Returns:
None
"""
# Call super.build()
super(StreamScalerData, self).build()
tmp_dict = dict(**self.config.property_package_args)
tmp_dict["has_phase_equilibrium"] = False
tmp_dict["defined_state"] = True
# Call setup methods from ControlVolumeBlockData
self._get_property_package()
self._get_indexing_sets()
self.properties = self.config.property_package.build_state_block(
self.flowsheet().time, doc="Material properties at inlet", **tmp_dict
)
self.scaled_expressions = Block()
self.multiplier = Var(
initialize=1,
domain=PositiveReals,
units=pyunits.dimensionless,
doc="Factor by which to scale dimensionless streams",
)
self.add_inlet_port(name="inlet", block=self.properties)
self.outlet = Port(doc="Outlet port")
def rule_scale_var(b, *args, var=None):
return self.multiplier * var[args]
def rule_no_scale_var(b, *args, var=None):
return var[args]
for var_name in self.inlet.vars.keys():
var = getattr(self.inlet, var_name)
if "flow" in var_name:
rule = partial(rule_scale_var, var=var)
else:
rule = partial(rule_no_scale_var, var=var)
self.scaled_expressions.add_component(
var_name, VarLikeExpression(var.index_set(), rule=rule)
)
expr = getattr(self.scaled_expressions, var_name)
self.outlet.add(expr, var_name)
[docs]
def initialize_build(
blk, outlvl=idaeslog.NOTSET, optarg=None, solver=None, hold_state=False
):
"""
Initialization routine for StreamScaler.
Keyword Arguments:
outlvl : sets output level of initialization routine
optarg : solver options dictionary object (default=None, use
default solver options)
solver : str indicating which solver to use during
initialization (default = None, use default solver)
hold_state : flag indicating whether the initialization routine
should unfix any state variables fixed during
initialization, **default** - False. **Valid values:**
**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.
Returns:
If hold_states is True, returns a dict containing flags for which
states were fixed during initialization.
"""
# Create solver
# Initialize inlet state blocks
flags = blk.properties.initialize(
outlvl=outlvl,
optarg=optarg,
solver=solver,
hold_state=True,
)
if hold_state is True:
return flags
else:
blk.release_state(flags, outlvl=outlvl)
[docs]
def release_state(blk, flags, outlvl=idaeslog.NOTSET):
"""
Method to release state variables fixed during initialization.
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 logging
Returns:
None
"""
blk.properties.release_state(flags, outlvl=outlvl)
def _get_stream_table_contents(self, time_point=0):
io_dict = {
"Inlet": self.inlet,
# "Outlet": self.outlet,
}
return create_stream_table_dataframe(io_dict, time_point=time_point)
def calculate_scaling_factors(self):
# Scaling factors for the property block are calculated automatically
super().calculate_scaling_factors()
# Need to pass on scaling factors from the property block to the outlet
# VarLikeExpressions so arcs get scaled right
if self.multiplier.value == 0:
default = 1
else:
default = 1 / self.multiplier.value
scale = iscale.get_scaling_factor(
self.multiplier, default=default, warning=False
)
for var_name in self.inlet.vars.keys():
var = getattr(self.inlet, var_name)
outlet_expr = getattr(self.outlet, var_name)
for key, subvar in var.items():
sf = iscale.get_scaling_factor(subvar, default=1, warning=True)
iscale.set_scaling_factor(outlet_expr[key], scale * sf)
