Source code for watertap.property_models.activated_sludge.asm1_properties

#################################################################################
# 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), and is copyright (c) 2018-2021
# 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.
#################################################################################
"""
Thermophysical property package to be used in conjunction with ASM1 reactions.
"""

# Import Pyomo libraries
import pyomo.environ as pyo

# Import IDAES cores
from idaes.core import (
    declare_process_block_class,
    MaterialFlowBasis,
    PhysicalParameterBlock,
    StateBlockData,
    StateBlock,
    MaterialBalanceType,
    EnergyBalanceType,
    LiquidPhase,
    Component,
    Solute,
    Solvent,
)
from idaes.core.util.model_statistics import degrees_of_freedom
from idaes.core.util.initialization import fix_state_vars, revert_state_vars
import idaes.logger as idaeslog
import idaes.core.util.scaling as iscale

# Some more information about this module
__author__ = "Andrew Lee"


# Set up logger
_log = idaeslog.getLogger(__name__)


[docs]@declare_process_block_class("ASM1ParameterBlock") class ASM1ParameterData(PhysicalParameterBlock): """ Property Parameter Block Class """
[docs] def build(self): """ Callable method for Block construction. """ super().build() self._state_block_class = ASM1StateBlock # Add Phase objects self.Liq = LiquidPhase() # Add Component objects self.H2O = Solvent() self.S_I = Solute(doc="Soluble inert organic matter, S_I") self.S_S = Solute(doc="Readily biodegradable substrate, S_S") self.X_I = Solute(doc="Particulate inert organic matter, X_I") self.X_S = Solute(doc="Slowly biodegradable substrate, X_S") self.X_BH = Solute(doc="Active heterotrophic biomass, X_B,H") self.X_BA = Solute(doc="Active autotrophic biomass, X_B,A") self.X_P = Solute(doc="Particulate products arising from biomass decay, X_P") self.S_O = Solute(doc="Oxygen, S_O") self.S_NO = Solute(doc="Nitrate and nitrite nitrogen, S_NO") self.S_NH = Solute(doc="NH4+ + NH3 nitrogen, S_NH") self.S_ND = Solute(doc="Soluble biodegradable organic nitrogen, S_ND") self.X_ND = Solute(doc="Particulate biodegradable organic nitrogen, X_ND") self.S_ALK = Component(doc="Alkalinity, S_ALK") # Heat capacity of water self.cp_mass = pyo.Param( mutable=False, initialize=4182, doc="Specific heat capacity of water", units=pyo.units.J / pyo.units.kg / pyo.units.K, ) # Density of water self.dens_mass = pyo.Param( mutable=False, initialize=997, doc="Density of water", units=pyo.units.kg / pyo.units.m**3, ) # Thermodynamic reference state self.pressure_ref = pyo.Param( within=pyo.PositiveReals, mutable=True, default=101325.0, doc="Reference pressure", units=pyo.units.Pa, ) self.temperature_ref = pyo.Param( within=pyo.PositiveReals, mutable=True, default=298.15, doc="Reference temperature", units=pyo.units.K, )
[docs] @classmethod def define_metadata(cls, obj): obj.add_properties( { "flow_vol": {"method": None}, "pressure": {"method": None}, "temperature": {"method": None}, "conc_mass_comp": {"method": None}, "alkalinity": {"method": None}, } ) obj.add_default_units( { "time": pyo.units.s, "length": pyo.units.m, "mass": pyo.units.kg, "amount": pyo.units.kmol, "temperature": pyo.units.K, } )
class _ASM1StateBlock(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=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 provied at the unit model level, the control volume passes the inlet values as initial guess.The keys for the state_args dictionary are: flow_mol_comp : value at which to initialize component flows (default=None) pressure : value at which to initialize pressure (default=None) temperature : value at which to initialize temperature (default=None) outlvl : sets output level of initialization routine state_vars_fixed: Flag to denote if state vars have already been fixed. - True - states have already been fixed and initialization does not need to worry about fixing and unfixing variables. - False - states have not been fixed. The state block will deal with fixing/unfixing. 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). - 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. """ init_log = idaeslog.getInitLogger(blk.name, outlvl, tag="properties") if state_vars_fixed is False: # Fix state variables if not already fixed flags = fix_state_vars(blk, state_args) else: # 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." ) if state_vars_fixed is False: if hold_state is True: return flags else: blk.release_state(flags) init_log.info("Initialization Complete.") def release_state(blk, flags, outlvl=idaeslog.NOTSET): """ Method to relase 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 of logging """ init_log = idaeslog.getInitLogger(blk.name, outlvl, tag="properties") if flags is None: return # Unfix state variables revert_state_vars(blk, flags) init_log.info("State Released.")
[docs]@declare_process_block_class("ASM1StateBlock", block_class=_ASM1StateBlock) class ASM1StateBlockData(StateBlockData): """ StateBlock for calculating thermophysical proeprties associated with the ASM1 reaction system. """
[docs] def build(self): """ Callable method for Block construction """ super().build() # Create state variables self.flow_vol = pyo.Var( initialize=1.0, domain=pyo.NonNegativeReals, doc="Total volumentric flowrate", units=pyo.units.m**3 / pyo.units.s, ) self.pressure = pyo.Var( domain=pyo.NonNegativeReals, initialize=101325.0, bounds=(1e3, 1e6), doc="Pressure", units=pyo.units.Pa, ) self.temperature = pyo.Var( domain=pyo.NonNegativeReals, initialize=298.15, bounds=(293.15, 323.15), doc="Temperature", units=pyo.units.K, ) self.conc_mass_comp = pyo.Var( self.params.solute_set, domain=pyo.NonNegativeReals, initialize=0.1, doc="Component mass concentrations", units=pyo.units.kg / pyo.units.m**3, ) self.alkalinity = pyo.Var( domain=pyo.NonNegativeReals, initialize=1, doc="Alkalinity in molar concentration", units=pyo.units.kmol / pyo.units.m**3, ) # Material and energy flow and density expressions def material_flow_expression(self, j): if j == "H2O": return self.flow_vol * self.params.dens_mass elif j == "S_ALK": # Convert moles of alkalinity to mass of C assuming all is HCO3- return ( self.flow_vol * self.alkalinity * (12 * pyo.units.kg / pyo.units.kmol) ) else: return self.flow_vol * self.conc_mass_comp[j] self.material_flow_expression = pyo.Expression( self.component_list, rule=material_flow_expression, doc="Material flow terms", ) def enthalpy_flow_expression(self): return ( self.flow_vol * self.params.dens_mass * self.params.cp_mass * (self.temperature - self.params.temperature_ref) ) self.enthalpy_flow_expression = pyo.Expression( rule=enthalpy_flow_expression, doc="Enthalpy flow term" ) def material_density_expression(self, j): if j == "H2O": return self.params.dens_mass elif j == "S_ALK": # Convert moles of alkalinity to mass of C assuming all is HCO3- return self.alkalinity * (12 * pyo.units.kg / pyo.units.kmol) else: return self.conc_mass_comp[j] self.material_density_expression = pyo.Expression( self.component_list, rule=material_density_expression, doc="Material density terms", ) def energy_density_expression(self): return ( self.params.dens_mass * self.params.cp_mass * (self.temperature - self.params.temperature_ref) ) self.energy_density_expression = pyo.Expression( rule=energy_density_expression, doc="Energy density term" )
[docs] def get_material_flow_terms(self, p, j): return self.material_flow_expression[j]
[docs] def get_enthalpy_flow_terms(self, p): return self.enthalpy_flow_expression
[docs] def get_material_density_terms(self, p, j): return self.material_density_expression[j]
[docs] def get_energy_density_terms(self, p): return self.energy_density_expression
def default_material_balance_type(self): return MaterialBalanceType.componentPhase def default_energy_balance_type(self): return EnergyBalanceType.enthalpyTotal
[docs] def define_state_vars(b): return { "flow_vol": b.flow_vol, "alkalinity": b.alkalinity, "conc_mass_comp": b.conc_mass_comp, "temperature": b.temperature, "pressure": b.pressure, }
[docs] def define_display_vars(b): return { "Volumetric Flowrate": b.flow_vol, "Molar Alkalinity": b.alkalinity, "Mass Concentration": b.conc_mass_comp, "Temperature": b.temperature, "Pressure": b.pressure, }
[docs] def get_material_flow_basis(b): return MaterialFlowBasis.mass
def calculate_scaling_factors(self): # Get default scale factors and do calculations from base classes super().calculate_scaling_factors() # No constraints in this model as yet, just need to set scaling factors # for expressions sf_F = iscale.get_scaling_factor(self.flow_vol, default=1e2, warning=True) sf_T = iscale.get_scaling_factor(self.temperature, default=1e-2, warning=True) # Mass flow and density terms for j in self.component_list: if j == "H2O": sf_C = pyo.value(1 / self.params.dens_mass) elif j == "S_ALK": sf_C = 1e-1 * iscale.get_scaling_factor( self.alkalinity, default=1, warning=True ) else: sf_C = iscale.get_scaling_factor( self.conc_mass_comp[j], default=1e2, warning=True ) iscale.set_scaling_factor(self.material_flow_expression[j], sf_F * sf_C) iscale.set_scaling_factor(self.material_density_expression[j], sf_C) # Enthalpy and energy terms sf_rho_cp = pyo.value(1 / (self.params.dens_mass * self.params.cp_mass)) iscale.set_scaling_factor( self.enthalpy_flow_expression, sf_F * sf_rho_cp * sf_T ) iscale.set_scaling_factor(self.energy_density_expression, sf_rho_cp * sf_T)