#################################################################################
# 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) 2018-2024 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.
#################################################################################
"""
Standard IDAES Gibbs reactor model.
"""
# Import Pyomo libraries
from pyomo.environ import Constraint, Param, Reals, Reference, Set, units, value, Var
from pyomo.common.config import ConfigBlock, ConfigValue, In, ListOf, Bool
# Import IDAES cores
from idaes.core import (
ControlVolume0DBlock,
declare_process_block_class,
EnergyBalanceType,
MomentumBalanceType,
UnitModelBlockData,
useDefault,
)
from idaes.core.util.config import is_physical_parameter_block
from idaes.core.util.exceptions import ConfigurationError
from idaes.core.scaling import CustomScalerBase
from idaes.core.util.constants import Constants
__author__ = "Jinliang Ma, Andrew Lee"
[docs]
class GibbsReactorScaler(CustomScalerBase):
"""
Scaler for Gibbs Reactor units.
Due to the nature of Gibbs Reactors, scaling is highly dependent on the outlet
concentrations which cannot be predicted a priori, thus we rely on users to
provide the best initial guesses they can for the outlet concentrations.
"""
UNIT_SCALING_FACTORS = {
# "QuantityName: (reference units, scaling factor)
"Delta Pressure": (units.Pa, 1e-3),
"Heat": (units.J / units.s, 1e-6),
}
[docs]
def variable_scaling_routine(
self, model, overwrite: bool = False, submodel_scalers: dict = None
):
"""
Variable scaling routine for Gibbs reactors.
Due to the nature of Gibbs Reactors, scaling is highly dependent on the outlet
concentrations which cannot be predicted a priori, thus we rely on users to
provide the best initial guesses they can for the outlet concentrations.
Args:
model: instance of GibbsReactor to be scaled
overwrite: whether to overwrite existing scaling factors
submodel_scalers: dict of Scalers to use for sub-models, keyed by submodel local name
Returns:
None
"""
if submodel_scalers is None:
submodel_scalers = {}
# Step 1: Property scaling
# Step 1a: propagate any existing scaling from inlet to outlet
# This is likely a very poor approximation for concentrations, but we expect users
# to provide better scaling factors manually (as there is no way for us to know).
# This will do a first pass fill in however if the user does not provide any information.
self.propagate_state_scaling(
target_state=model.control_volume.properties_out,
source_state=model.control_volume.properties_in,
overwrite=overwrite,
)
# Step 1b: Call Scalers for state blocks
# Inlet properties
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_in,
submodel_scalers=submodel_scalers,
method="variable_scaling_routine",
overwrite=overwrite,
)
# Outlet properties
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_out,
submodel_scalers=submodel_scalers,
method="variable_scaling_routine",
overwrite=overwrite,
)
# Step 2: Scaling Gibbs reactor variables
# Control volume variables - support only heat and deltaP
if hasattr(model.control_volume, "heat"):
for v in model.control_volume.heat.values():
self.scale_variable_by_units(v, overwrite=overwrite)
if hasattr(model.control_volume, "deltaP"):
for v in model.control_volume.deltaP.values():
self.scale_variable_by_units(v, overwrite=overwrite)
# Lagrangian multipliers
# Best guess scaling for these is R*T, need to convert units
p_units = (
model.control_volume.config.property_package.get_metadata().get_derived_units
)
for (t, _), v in model.lagrange_mult.items():
tsf = self.get_scaling_factor(
model.control_volume.properties_out[t].temperature
)
if tsf is not None:
nominal_t = 1 / tsf
else:
nominal_t = 500
lsf = value(
1
/ units.convert(
Constants.gas_constant * nominal_t * p_units("temperature"),
to_units=p_units("energy_mole"),
)
)
self.set_variable_scaling_factor(v, lsf, overwrite=overwrite)
[docs]
def constraint_scaling_routine(
self, model, overwrite: bool = False, submodel_scalers: dict = None
):
"""
Routine to apply scaling factors to constraints in model.
Constraints will be scaled based on nominal Jacobian norms, and thus will
be heavily dependent on variable scaling.
Args:
model: model to be scaled
overwrite: whether to overwrite existing scaling factors
submodel_scalers: dict of Scalers to use for sub-models, keyed by submodel local name
Returns:
None
"""
# Step 1: Call Scalers for state blocks
# Inlet properties
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_in,
submodel_scalers=submodel_scalers,
method="constraint_scaling_routine",
overwrite=overwrite,
)
# Outlet properties
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_out,
submodel_scalers=submodel_scalers,
method="constraint_scaling_routine",
overwrite=overwrite,
)
# Step 2: Scale all the control volume constraints
for cd in model.control_volume.component_data_objects(
ctype=Constraint, descend_into=False
):
self.scale_constraint_by_nominal_value(
cd, scheme="inverse_sum", overwrite=overwrite
)
# Step 3: Scale local constraints
# Scale Gibbs minimization constraints
for cd in model.gibbs_minimization.values():
self.scale_constraint_by_nominal_value(
cd, scheme="inverse_sum", overwrite=overwrite
)
# Scale inert species balance if they are present
if hasattr(model, "inert_species_balance"):
for cd in model.inert_species_balance.values():
self.scale_constraint_by_nominal_value(
cd, scheme="inverse_sum", overwrite=overwrite
)
[docs]
@declare_process_block_class("GibbsReactor")
class GibbsReactorData(UnitModelBlockData):
"""
Standard Gibbs Reactor Unit Model Class
This model assume all possible reactions reach equilibrium such that the
system partial molar Gibbs free energy is minimized.
Since some species mole flow rate might be very small,
the natural log of the species molar flow rate is used.
Instead of specifying the system Gibbs free energy as an objective
function, the equations for zero partial derivatives of the grand function
with Lagrangian multiple terms with respect to product species mole flow
rates and the multiples are specified as constraints.
"""
CONFIG = ConfigBlock()
CONFIG.declare(
"dynamic",
ConfigValue(
domain=In([False]),
default=False,
description="Dynamic model flag - must be False",
doc="""Gibbs reactors do not support dynamic models, thus this must be
False.""",
),
)
CONFIG.declare(
"has_holdup",
ConfigValue(
default=False,
domain=In([False]),
description="Holdup construction flag",
doc="""Gibbs reactors do not have defined volume, thus this must be
False.""",
),
)
CONFIG.declare(
"energy_balance_type",
ConfigValue(
default=EnergyBalanceType.useDefault,
domain=In(EnergyBalanceType),
description="Energy balance construction flag",
doc="""Indicates what type of energy balance should be constructed,
**default** - EnergyBalanceType.useDefault.
**Valid values:** {
**EnergyBalanceType.useDefault - refer to property package for default
balance type
**EnergyBalanceType.none** - exclude energy balances,
**EnergyBalanceType.enthalpyTotal** - single enthalpy balance for material,
**EnergyBalanceType.enthalpyPhase** - enthalpy balances for each phase,
**EnergyBalanceType.energyTotal** - single energy balance for material,
**EnergyBalanceType.energyPhase** - energy balances for each phase.}""",
),
)
CONFIG.declare(
"momentum_balance_type",
ConfigValue(
default=MomentumBalanceType.pressureTotal,
domain=In(MomentumBalanceType),
description="Momentum balance construction flag",
doc="""Indicates what type of momentum balance should be constructed,
**default** - MomentumBalanceType.pressureTotal.
**Valid values:** {
**MomentumBalanceType.none** - exclude momentum balances,
**MomentumBalanceType.pressureTotal** - single pressure balance for material,
**MomentumBalanceType.pressurePhase** - pressure balances for each phase,
**MomentumBalanceType.momentumTotal** - single momentum balance for material,
**MomentumBalanceType.momentumPhase** - momentum balances for each phase.}""",
),
)
CONFIG.declare(
"has_heat_transfer",
ConfigValue(
default=False,
domain=Bool,
description="Heat transfer term construction flag",
doc="""Indicates whether terms for heat transfer should be constructed,
**default** - False.
**Valid values:** {
**True** - include heat transfer terms,
**False** - exclude heat transfer terms.}""",
),
)
CONFIG.declare(
"has_pressure_change",
ConfigValue(
default=False,
domain=Bool,
description="Pressure change term construction flag",
doc="""Indicates whether terms for pressure change should be
constructed,
**default** - False.
**Valid values:** {
**True** - include pressure change terms,
**False** - exclude pressure change terms.}""",
),
)
CONFIG.declare(
"property_package",
ConfigValue(
default=useDefault,
domain=is_physical_parameter_block,
description="Property package to use for control volume",
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.}""",
),
)
CONFIG.declare(
"inert_species",
ConfigValue(
default=[],
domain=ListOf(str),
description="List of inert species",
doc="List of species which do not take part in reactions.",
),
)
default_scaler = GibbsReactorScaler
[docs]
def build(self):
"""
Begin building model (pre-DAE transformation).
Args:
None
Returns:
None
"""
# Call UnitModel.build to setup dynamics
super(GibbsReactorData, self).build()
# Build Control Volume
self.control_volume = ControlVolume0DBlock(
dynamic=self.config.dynamic,
property_package=self.config.property_package,
property_package_args=self.config.property_package_args,
)
self.control_volume.add_state_blocks(has_phase_equilibrium=False)
# Validate list of inert species
for i in self.config.inert_species:
if i not in self.control_volume.properties_in.component_list:
raise ConfigurationError(
"{} invalid component in inert_species argument. {} is "
"not in the property package component list.".format(self.name, i)
)
self.control_volume.add_total_element_balances()
self.control_volume.add_energy_balances(
balance_type=self.config.energy_balance_type,
has_heat_transfer=self.config.has_heat_transfer,
)
self.control_volume.add_momentum_balances(
balance_type=self.config.momentum_balance_type,
has_pressure_change=self.config.has_pressure_change,
)
# Add Ports
self.add_inlet_port()
self.add_outlet_port()
# Add performance equations
# Add Lagrangian multiplier variables
# Only need multipliers for species which participate in reactions
l_set = []
for e in self.control_volume.config.property_package.element_list:
skip = True
for j in self.control_volume.properties_in.component_list:
if j in self.config.inert_species:
continue
elif self.control_volume.properties_out.params.element_comp[j][e] != 0:
skip = False
if not skip:
l_set.append(e)
self.lagrange_set = Set(initialize=l_set)
e_units = self.control_volume.config.property_package.get_metadata().get_derived_units(
"energy_mole"
)
self.lagrange_mult = Var(
self.flowsheet().time,
self.lagrange_set,
domain=Reals,
initialize=100,
doc="Lagrangian multipliers",
units=e_units,
)
# TODO : Remove this once scaling is properly implemented
self.gibbs_scaling = Param(default=1, mutable=True)
# Use Lagrangian multiple method to derive equations for Out_Fi
# Use RT*lagrange as the Lagrangian multiple such that lagrange is in
# a similar order of magnitude as log(Yi)
@self.Constraint(
self.flowsheet().time,
self.control_volume.properties_in.phase_component_set,
doc="Gibbs energy minimisation constraint",
)
def gibbs_minimization(b, t, p, j):
# Use natural log of species mole flow to avoid Pyomo solver
# warnings of reaching infeasible point
if j in self.config.inert_species:
return Constraint.Skip
return 0 == b.gibbs_scaling * (
b.control_volume.properties_out[t].gibbs_mol_phase_comp[p, j]
+ sum(
b.lagrange_mult[t, e]
* b.control_volume.properties_out[t].params.element_comp[j][e]
for e in self.lagrange_set
)
)
if len(self.config.inert_species) > 0:
@self.Constraint(
self.flowsheet().time,
self.control_volume.properties_in.phase_list,
self.config.inert_species,
doc="Inert species balances",
)
def inert_species_balance(b, t, p, j):
# Add species balances for inert components
cv = b.control_volume
e_comp = cv.properties_out[t].config.parameters.element_comp
# Check for linear dependence with element balances
# If an inert species is the only source of element e,
# the inert species balance would be linearly dependent on the
# element balance for e.
dependent = True
if len(self.control_volume.properties_in.phase_list) > 1:
# Multiple phases avoid linear dependency
dependent = False
else:
for e in self.control_volume.config.property_package.element_list:
if e_comp[j][e] == 0:
# Element e not in component j, no effect
continue
else:
for i in self.control_volume.properties_in.component_list:
if i == j:
continue
else:
# If comp j shares element e with comp i
# cannot be linearly dependent
if e_comp[i][e] != 0:
dependent = False
if (
not dependent
and (p, j) in self.control_volume.properties_in.phase_component_set
):
return 0 == (
cv.properties_in[t].get_material_flow_terms(p, j)
- cv.properties_out[t].get_material_flow_terms(p, j)
)
else:
return Constraint.Skip
# Set references to balance terms at unit level
if (
self.config.has_heat_transfer is True
and self.config.energy_balance_type != EnergyBalanceType.none
):
self.heat_duty = Reference(self.control_volume.heat[:])
if (
self.config.has_pressure_change is True
and self.config.momentum_balance_type != MomentumBalanceType.none
):
self.deltaP = Reference(self.control_volume.deltaP[:])
def _get_performance_contents(self, time_point=0):
var_dict = {}
if hasattr(self, "heat_duty"):
var_dict["Heat Duty"] = self.heat_duty[time_point]
if hasattr(self, "deltaP"):
var_dict["Pressure Change"] = self.deltaP[time_point]
return {"vars": var_dict}
