##############################################################################
# Institute for the Design of Advanced Energy Systems Process Systems
# Engineering Framework (IDAES PSE Framework) Copyright (c) 2018, 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.txt and LICENSE.txt for full copyright and
# license information, respectively. Both files are also available online
# at the URL "https://github.com/IDAES/idaes-pse".
##############################################################################
"""
Basic property package for flue gas
main assumptions:
- ideal gas
- components in flue gas: O2, N2, NO, CO2, H2O, SO2
"""
# Import Pyomo libraries
from pyomo.environ import (Constraint, Param, RangeSet, PositiveReals, Reals,
Set, value, log, exp, sqrt, Var)
from pyomo.opt import SolverFactory, TerminationCondition
# Import IDAES cores
from idaes.core import (declare_process_block_class,
PhysicalParameterBlock,
StateBlockData,
StateBlock)
from idaes.core.util.misc import add_object_reference
from idaes.core.util.model_statistics import degrees_of_freedom
from idaes.core import MaterialBalanceType, EnergyBalanceType,\
MaterialFlowBasis
from idaes.core.util.initialization import fix_state_vars, revert_state_vars
# Import Python libraries
import logging
# Some more inforation about this module
__author__ = "Boiler Subsystem Team J. Ma, M. Zamarripa, T. Burgard"
__version__ = "3"
# Set up logger
logger = logging.getLogger('idaes.unit_model.properties')
[docs]@declare_process_block_class("FlueGasParameterBlock")
class PhysicalParameterData(PhysicalParameterBlock):
"""
Property Parameter Block Class
Contains parameters and indexing sets associated with properties for flue
gas. The ideal gas assumption is applied.
"""
[docs] def build(self):
'''
Callable method for Block construction.
'''
super(PhysicalParameterData, self).build()
self.state_block_class = FlueGasStateBlock
# List of valid phases in property package
self.phase_list = Set(initialize=['Vap'])
# Component list - a Set of component identifiers
self.component_list = Set(initialize=['N2','O2','NO','CO2','H2O','SO2'])
#molecular weight
self.mw = Param(self.component_list,
initialize={'O2': 31.998,
'N2': 28.0134,
'NO': 30.0057,
'CO2': 44.01,
'H2O': 18.01528,
'SO2': 64.0588},
doc='Molecular Weight')
# Thermodynamic reference state
self.pressure_reference = Param(within=PositiveReals,
mutable=True,
default=1.01325e5,
doc='Reference pressure [Pa]')
self.temperature_reference = Param(within=PositiveReals,
mutable=True,
default=298.16,
doc='Reference temperature [K]')
# Critical Properties
self.pressure_critical = Param(self.component_list,
within=PositiveReals,
initialize={'O2':50.45985e5,
'N2':33.943875e5,
'NO':64.85e5,
'CO2':73.8e5,
'H2O':220.64e5,
'SO2':7.883e6},
doc='Critical pressure [Pa]')
self.temperature_critical = Param(self.component_list,
within=PositiveReals,
initialize={'O2':154.58,
'N2':126.19,
'NO':180.0,
'CO2':304.18,
'H2O':647,
'SO2':430.8},
doc='Critical temperature [K]')
# Gas Constant
self.gas_constant = Param(within=PositiveReals,
default=8.314,
doc='Gas Constant [J/mol.K]')
# Constants for specific heat capacity, enthalpy, entropy
# calculations for ideal gas (from NIST
#https://webbook.nist.gov/cgi/cbook.cgi?ID=C7727379&Units=SI&Mask=1#Thermo-Gas)
# 01/08/2020
CpIGTab = {
('A','N2') : 19.50583,
('B','N2') : 19.88705,
('C','N2') : -8.598535,
('D','N2') : 1.369784,
('E','N2') : 0.527601,
('F','N2') : -4.935202,
('G','N2') : 212.39,
('H','N2') : 0,
('A','O2') : 30.03235,
('B','O2') : 8.772972,
('C','O2') : -3.98813,
('D','O2') : 0.788313,
('E','O2') : -0.7416,
('F','O2') : -11.3247,
('G','O2') : 236.1663,
('H','O2') : 0,
('A','CO2') : 24.99735,
('B','CO2') : 55.18696,
('C','CO2') : -33.69137,
('D','CO2') : 7.948387,
('E','CO2') : -0.136638,
('F','CO2') : -403.6075,
('G','CO2') : 228.2431,
('H','CO2') : -393.5224,
('A','H2O') : 30.092,
('B','H2O') : 6.832514,
('C','H2O') : 6.793435,
('D','H2O') : -2.53448,
('E','H2O') : 0.082139,
('F','H2O') : -250.881,
('G','H2O') : 223.3967,
('H','H2O') : -241.8264,
('A','NO') : 23.83491,
('B','NO') : 12.58878,
('C','NO') : -1.139011,
('D','NO') : -1.497459,
('E','NO') : 0.214194,
('F','NO') : 83.35783,
('G','NO') : 237.1219,
('H','NO') : 90.29114,
('A','SO2') : 21.43049,
('B','SO2') : 74.35094,
('C','SO2') : -57.75217,
('D','SO2') : 16.35534,
('E','SO2') : 0.086731,
('F','SO2') : -305.7688,
('G','SO2') : 254.8872,
('H','SO2') : -296.8422
}
# CpIG units: J/(gmol-K)
self.CpIG = Param(['A','B','C','D','E','F','G','H'],
self.component_list,initialize=CpIGTab,
doc='Constants for spec. heat capacity for ideal gas J/(gmol-K)')
# Vapor pressure coefficients, current use N2 data for
# NO since the data for NO are not available
# NIST Webbook
#https://webbook.nist.gov/cgi/cbook.cgi?ID=C7727379&Units=SI&Mask=4#Thermo-Phase
# 01/08/2020
iv_pvap = {
('N2','A'): 3.7362,
('N2','B'): 264.651,
('N2','C'): -6.788,
('O2','A'): 3.9523,
('O2','B'): 340.024,
('O2','C'): -4.144,
('H2O','A'): 3.55959,
('H2O','B'): 643.748,
('H2O','C'): -198.043,
('CO2','A'): 6.81228,
('CO2','B'): 1301.679,
('CO2','C'): -3.494,
('NO','A'): 3.7362,
('NO','B'): 264.651,
('NO','C'): -6.788,
('SO2','A'): 4.37798,
('SO2','B'): 966.575,
('SO2','C'): -42.071}
self.vapor_pressure_coeff = Param(self.component_list, ['A','B','C'], \
initialize=iv_pvap, mutable=True,
doc="Antoine coefficients for vapor pressure"
"P in bar, T in K")
class _FlueGasStateBlock(StateBlock):
"""
This Class contains methods which should be applied to Property Blocks as a
whole, rather than individual elements of indexed Property Blocks.
"""
def initialize(blk, state_args={"flow_component": {"N2": 1.0,
"CO2": 1.0,
"NO": 1.0,
"O2": 1.0,
"H2O": 1.0,
"SO2": 1.0},
"pressure":1e5,
"temperature":495.0},
hold_state=False,
state_vars_fixed=False,
outlvl=0,
solver='ipopt',
optarg={'tol': 1e-8}):
'''
Initialisation routine for property package.
Key values for the state_args dict:
flow_component : value at which to initialize component flows
(default=27.5e3 mol/s)
pressure : value at which to initialize pressure (default=2.97e7 Pa)
temperature : value at which to initialize temperature
(default=866.5 K)
outlvl : sets output level of initialisation routine
* 0 = no output (default)
* 1 = return solver state for each step in routine
* 2 = include solver output infomation (tee=True)
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.
optarg : solver options dictionary object (default=None)
solver : str indicating whcih solver to use during
initialization (default = 'ipopt')
hold_state : flag indicating whether the initialization routine
should unfix any state variables fixed during
initialization (default=False).
- True - states varaibles 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
relase_state method
Returns:
If hold_states is True, returns a dict containing flags for
which states were fixed during initialization.
'''
if state_vars_fixed is False:
flags = fix_state_vars(blk, state_args)
# Check when the state vars are fixed already result in dof 0
for k in blk.keys():
if degrees_of_freedom(blk[k]) != 0:
raise Exception("State vars fixed but degrees of freedom "
"for state block is not zero during "
"initialization.")
# Set solver options
if outlvl > 1:
stee = True
else:
stee = False
opt = SolverFactory(solver)
opt.options = optarg
# ---------------------------------------------------------------------
# Solve 1st stage
for k in blk.keys():
if hasattr(blk[k], "vapor_pressure_correlation"):
blk[k].vapor_pressure = \
exp(blk[k].vapor_pressure_coeff[1].value +
blk[k].vapor_pressure_coeff[2].value /
value(blk.temperature) +
blk[k].vapor_pressure_coeff[3].value *
value(blk.temperature) +
blk[k].vapor_pressure_coeff[4].value *
log(value(blk.temperature)) +
blk[k].vapor_pressure_coeff[5].value *
value(blk.temperature)**2)
if hasattr(blk[k],'enthalpy_correlation'):
blk[k].enthalpy_correlation.deactivate()
if hasattr(blk[k], "volumetric_flow_calculation"):
blk[k].volumetric_flow_calculation.deactivate()
if hasattr(blk[k], "entropy_correlation"):
blk[k].entropy_correlation.deactivate()
if hasattr(blk[k], "density_mol_calculation"):
blk[k].density_mol_calculation.deactivate()
results = opt.solve(blk[k], tee=stee)
if outlvl > 0:
if results.solver.termination_condition \
== TerminationCondition.optimal:
logger.info('{} Initialisation Step 1 Complete.'
.format(blk.name))
else:
logger.warning('{} Initialisation Step 1 Failed.'
.format(blk.name))
# ---------------------------------------------------------------------
# Solve 2nd stage
for k in blk.keys():
if hasattr(blk[k],'enthalpy_correlation'):
blk[k].enthalpy_correlation.activate()
if hasattr(blk[k], "volumetric_flow_calculation"):
blk[k].volumetric_flow_calculation.activate()
if hasattr(blk[k], "entropy_correlation"):
blk[k].entropy_correlation.activate()
if hasattr(blk[k], "density_mol_calculation"):
blk[k].density_mol_calculation.activate()
results = opt.solve(blk[k], tee=stee)
if outlvl > 0:
if results.solver.termination_condition \
== TerminationCondition.optimal:
logger.info('{} Initialisation Step 2 Complete.'
.format(blk.name))
else:
logger.warning('{} Initialisation Step 2 Failed.'
.format(blk.name))
# ---------------------------------------------------------------------
# If input block, return flags, else release state
if outlvl > 0:
if outlvl > 0:
logger.info('{} Initialisation Complete.'.format(blk.name))
if state_vars_fixed is False:
if hold_state is True:
return flags
else:
blk.release_state(flags)
def release_state(blk, flags, outlvl=0):
'''
Method to relase 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
revert_state_vars(blk, flags)
if outlvl > 0:
if outlvl > 0:
logger.info('{} State Released.'.format(blk.name))
[docs]@declare_process_block_class("FlueGasStateBlock",
block_class=_FlueGasStateBlock)
class FlueGasStateBlockData(StateBlockData):
"""
This is an example of a property package for calculating the thermophysical
properties of flue gas using the ideal gas assumption.
"""
[docs] def build(self):
"""
Callable method for Block construction
"""
super(FlueGasStateBlockData, self).build()
self._make_state_vars()
self._make_constraints()
def _make_state_vars(self):
"""
This section makes the necessary state variable objects
"""
self.flow_component = Var(self._params.component_list,
domain=Reals,
initialize=1.0,
bounds=(0, 1e6),
doc='Component molar flowrate [mol/s]')
self.pressure = Var(domain=Reals,
initialize=1.01325e5,
bounds=(1, 5e7),
doc='State pressure [Pa]')
self.temperature = Var(domain=Reals,
initialize=500,
bounds=(200, 1500),
doc='State temperature [K]')
def _make_constraints(self):
'''
Create property constraints
'''
self.mole_frac = Var(self._params.component_list, initialize=1,
doc='mole fraction of component i')
def rule_mole_frac(b,c):
return b.mole_frac[c]*sum(b.flow_component[j]
for j in b._params.component_list) == b.flow_component[c]
self.mole_frac_con = Constraint(self._params.component_list, rule=rule_mole_frac)
'''
Add flow_mol
'''
self.flow_mol = Var(initialize=1, doc='total molar flow')
def rule_flow_mol(b):
return b.flow_mol == sum(b.flow_component[j] for j in b._params.component_list)
self.rule_flow_mol = Constraint(rule=rule_flow_mol)
'''
Add flow_mass
'''
self.flow_mass = Var(initialize=1, doc='total mass flow')
def rule_flow_mass(b):
return b.flow_mass == sum(b.flow_component[j] * b._params.mw[j]
* 0.001 for j in b._params.component_list)
self.rule_flow_mass = Constraint(rule=rule_flow_mass)
def _heat_cap_calc(self):
# heat capacity J/mol-K
self.heat_cap = Var(initialize= 1000, doc='heat capacity [J/mol-K]')
def rule_Cp(b):
return b.heat_cap*sum(b.flow_component[j]
for j in b._params.component_list) == sum((b._params.CpIG['A',j]
+ b._params.CpIG['B',j]*(b.temperature/1000)
+ b._params.CpIG['C',j]*(b.temperature/1000)**2
+ b._params.CpIG['D',j]*(b.temperature/1000)**3
+ b._params.CpIG['E',j]/(b.temperature/1000)**2)*b.flow_component[j]
for j in b._params.component_list)
try:
self.heat_cap_correlation = Constraint(rule=rule_Cp)
except AttributeError:
self.del_component(self.heat_cap)
self.del_component(self.heat_cap_correlation)
def _enthalpy_calc(self):
self.enthalpy = Var(self._params.phase_list, doc='Specific Enthalpy [J/mol]')
# Specific Enthalpy
def enthalpy_correlation(b, p):
scale_factor = 1e-3
return scale_factor*b.enthalpy[p]*sum(b.flow_component[j]
for j in b._params.component_list) == scale_factor*(
sum((b._params.CpIG['A',j]*(b.temperature/1000) +\
b._params.CpIG['B',j]*(b.temperature/1000)**2/2 +\
b._params.CpIG['C',j]*(b.temperature/1000)**3/3 +\
b._params.CpIG['D',j]*(b.temperature/1000)**4/4 -\
b._params.CpIG['E',j]/(b.temperature/1000) +\
b._params.CpIG['F',j])*b.flow_component[j]*1000
for j in b._params.component_list))
try:
self.enthalpy_correlation = Constraint(self._params.phase_list,
rule=enthalpy_correlation)
except AttributeError:
self.del_component(self.enthalpy)
self.del_component(self.enthalpy_correlation)
def _entropy_calc(self):
self.entropy = Var(doc='Specific Entropy [J/mol/K]')
# Specific Entropy
def entropy_correlation(b):
return b.entropy*sum(b.flow_component[j]
for j in b._params.component_list) == \
sum((b._params.CpIG['A',j]*log((b.temperature/1000)) +
b._params.CpIG['B',j]*(b.temperature/1000) +
b._params.CpIG['C',j]*(b.temperature/1000)**2/2 +
b._params.CpIG['D',j]*(b.temperature/1000)**3/3 -
b._params.CpIG['E',j]/(2*(b.temperature/1000)**2) +
b._params.CpIG['G',j] - b._params.gas_constant*log(b.mole_frac[j]))
*b.flow_component[j] for j in b._params.component_list)
try:
self.entropy_correlation = Constraint(rule=entropy_correlation)
except AttributeError:
self.del_component(self.entropy)
self.del_component(self.entropy_correlation)
def _reduced_press_temp(self):
self.pressure_reduced = Var(initialize=1.0, doc='Reduced Pressure')
self.temperature_reduced = Var(initialize=1.0,
doc='Reduced Temperature')
# Reduced Temperature and Pressure
def reduced_pressure_calculation(b):
scale_factor = 1e-3
return scale_factor*b.pressure_reduced*sum(b._params.pressure_critical[j]*
b.flow_component[j] for j in b._params.component_list) == \
scale_factor*b.pressure*sum(b.flow_component[j]
for j in b._params.component_list)
def reduced_temperature_calculation(b):
return b.temperature_reduced*sum(b.temperature_critical[j]*
b.flow_component[j] for j in b._params.component_list) == \
b.temperature*sum(b.flow_component[j]
for j in b._params.component_list)
try:
self.reduced_pressure_calculation = \
Constraint(rule=reduced_pressure_calculation)
self.reduced_temperature_calculation = \
Constraint(rule=reduced_temperature_calculation)
except AttributeError:
self.del_component(self.pressure_reduced)
self.del_component(self.temperature_reduced)
self.del_component(self.reduced_pressure_calculation)
self.del_component(self.reduced_temperature_calculation)
def _compress_fact(self):
# Compressibility
self.compress_fact = Var(initialize=1.00,
doc='Vapor Compressibility Factor')
def compress_fact_correlation(b):
return b.compress_fact == 1
try:
self.compress_fact_correlation = Constraint(
rule=compress_fact_correlation)
except AttributeError:
self.del_component(self.compress_fact)
self.del_component(self.compress_fact_correlation)
def _dens_mol_phase(self):
# Density from PV = ZRT
self.dens_mol_phase = Var(self._params.phase_list, doc='Molar Density')
def dens_mol_phase_calculation(b, p):
return b.pressure == (b.dens_mol_phase[p]*b.compress_fact *
b._params.gas_constant*b.temperature)
try:
self.dens_mol_phase_calculation = Constraint(self._params.phase_list,
rule=dens_mol_phase_calculation)
except:
self.del_component(self.dens_mol_phase)
self.del_component(self.dens_mol_phase_calculation)
def _vapor_pressure(self):
# Vapour Pressure
self.vapor_pressure = Var(initialize=101325,
doc="Vapour pressure [Pa]")
def vapor_pressure_correlation(b):
return log(b.vapor_pressure)*sum(b.flow_component[j]
for j in b._params.component_list) == sum((
b._params.vapor_pressure_coeff[j,'A']*b.temperature -
(b._params.vapor_pressure_coeff[j,'B']/(b.temperature +
b._param.vapor_pressure_coeff[j,'C'])))*
b.flow_component[j]
for j in b._params.component_list)
try:
self.vapor_pressure_correlation = \
Constraint(rule=vapor_pressure_correlation)
except AttributeError:
self.del_component(self.vapor_pressure)
self.del_component(self.vapor_pressure_correlation)
def _flow_volume(self):
# Volumetric Flowrate
self.flow_volume = Var(doc='Volumetric Flowrate')
def volumetric_flow_calculation(b):
return b.flow_volume*b.density_mol["Vap"] == \
sum(b.flow_component[j] for j in b._params.component_list)
try:
self.volumetric_flow_calculation = Constraint(
rule=volumetric_flow_calculation)
except AttributeError:
self.del_component(self.flow_volume)
self.del_component(self.volumetric_flow_calculation)
def _therm_cond(self):
self.therm_cond = Var(self._params.component_list, initialize=0.05,
doc='thermal conductivity J/m-K-s')
self.therm_cond_mix = Var(initialize= 0.05,
doc='thermal conductivity '
'of gas mixture J/m-K-s')
self.visc_d = Var(self._params.component_list,
initialize= 2e-5,
doc = 'dynamic viscocity of pure gas species')
self.visc_d_mix = Var(initialize= 2e-5,
doc='viscosity of gas mixture kg/m-s')
self.omega = Var(self._params.component_list,
initialize = 1, doc = 'dim')
self.theta = Var(self._params.component_list, initialize = 1,
doc = 'dimensionless variable = T/ep/Kappa')
self.phi_ij = Var(self._params.component_list,
self._params.component_list,
initialize = 1, doc = 'dimensionless var')
self.sigma = Param(self._params.component_list,
initialize={'O2': 3.458,
'N2': 3.621,
'NO': 3.47,
'CO2': 3.763,
'H2O': 2.605,
'SO2': 4.29},
doc='collision diameter in Angstrom (10e-10 mts)')
self.ep_Kappa = Param(self._params.component_list,
initialize={'O2': 107.4,
'N2': 97.53,
'NO': 119.0,
'CO2': 244.0,
'H2O': 572.4,
'SO2': 252.0},
doc="characteristic energy of interaction between "
"pair of molecules K = Boltzmann "
"constant in Kelvin")
try:
def rule_therm_cond(b,c):
return b.therm_cond[c] == (((b._params.CpIG['A',c]
+ b._params.CpIG['B',c]*(b.temperature/1000)
+ b._params.CpIG['C',c]*(b.temperature/1000)**2
+ b._params.CpIG['D',c]*(b.temperature/1000)**3
+ b._params.CpIG['E',c]/(b.temperature/1000)**2)/b._params.mw[c]) \
+ 1.25*(b._params.gas_constant/b._params.mw[c]))*b.visc_d[c]*1000.0
self.therm_cond_con = Constraint(self._params.component_list,
rule=rule_therm_cond)
def rule_theta(b,c):
return b.theta[c] == b.temperature/b.ep_Kappa[c]
self.theta_con = Constraint(self._params.component_list, rule=rule_theta)
def rule_omega(b,c):
return b.omega[c] == 1.5794145 + 0.00635771*b.theta[c] \
- 0.7314*log(b.theta[c]) + 0.2417357*(log(b.theta[c]))**2 \
- 0.0347045*log(b.theta[c])**3
self.omega_con = Constraint(self._params.component_list, rule=rule_omega)
# Pure gas viscocity
def rule_visc_d(b,c):
return b.visc_d[c]*b.sigma[c]**2*b.omega[c] == \
2.6693e-6*sqrt(b._params.mw[c]*b.temperature)
self.visc_d_con = Constraint(self._params.component_list, rule=rule_visc_d)
# section to calculate viscosity of gas mixture
def rule_phi(b,i,j):
return b.phi_ij[i,j] == 1/2.8284 \
* (1 + (b._params.mw[i]/b._params.mw[j]))**(-0.5) \
* (1 + sqrt(b.visc_d[i]/b.visc_d[j])*(b._params.mw[j]/b._params.mw[i])**0.25)**2
self.phi_con = Constraint(self._params.component_list,
self._params.component_list,
rule=rule_phi)
# viscosity of Gas mixture kg/m-s
def rule_visc_d_mix(b):
return b.visc_d_mix == sum((b.mole_frac[i]*b.visc_d[i]) \
/sum(b.mole_frac[j]*b.phi_ij[i,j]
for j in b._params.component_list)
for i in b._params.component_list)
self.vis_d_mix_con = Constraint(rule=rule_visc_d_mix)
#thermal conductivity of gas mixture in kg/m-s
def rule_therm_mix(b):
return b.therm_cond_mix == \
sum((b.mole_frac[i]*b.therm_cond[i]) \
/sum(b.mole_frac[j]*b.phi_ij[i,j] for j in b._params.component_list)
for i in b._params.component_list)
self.therm_mix_con = Constraint(rule=rule_therm_mix)
except AttributeError:
self.del_component(self.therm_cond)
self.del_component(self.therm_cond_mix)
self.del_component(self.visc_d)
self.del_component(self.visc_d_mix)
self.del_component(self.omega)
self.del_component(self.theta)
self.del_component(self.phi_ij)
self.del_component(self.sigma)
self.del_component(self.ep_Kappa)
self.del_component(self.therm_cond_con)
self.del_component(self.theta_con)
self.del_component(self.omega_con)
self.del_component(self.visc_d_con)
self.del_component(self.phi_con)
def default_material_balance_type(self):
return MaterialBalanceType.componentTotal
def default_energy_balance_type(self):
return EnergyBalanceType.enthalpyTotal
[docs] def get_material_flow_terms(self, p, j):
return self.flow_component[j]
[docs] def get_material_flow_basis(self):
return MaterialFlowBasis.molar
[docs] def get_enthalpy_flow_terms(self, p):
return sum(self.flow_component[j]
for j in self._params.component_list)*self.enthalpy[p]
[docs] def get_material_density_terms(self, p, j):
return self.dens_mol_phase[p]
def get_enthalpy_density_terms(self, p):
return self.enthalpy[p]*self.dens_mol_phase[p]
[docs] def define_state_vars(self):
return {"flow_component": self.flow_component,
"temperature": self.temperature,
"pressure": self.pressure}
[docs] def model_check(blk):
"""
Model checks for property block
"""
# Check temperature bounds
if value(blk.temperature) < blk.temperature.lb:
logger.error(
'{} Temperature set below lower bound.'.format(blk.name))
if value(blk.temperature) > blk.temperature.ub:
logger.error(
'{} Temperature set above upper bound.'.format(blk.name))
# Check pressure bounds
if value(blk.pressure) < blk.pressure.lb:
logger.error(
'{} Pressure set below lower bound.'.format(blk.name))
if value(blk.pressure) > blk.pressure.ub:
logger.error(
'{} Pressure set above upper bound.'.format(blk.name))