Source code for watertap.property_models.activated_sludge.asm2d_properties

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# WaterTAP Copyright (c) 2020-2023, 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.
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# 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
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"""
Thermophysical property package to be used in conjunction with ASM2d reactions.

Reference:
[1] Henze, M., Gujer, W., Mino, T., Matsuo, T., Wentzel, M.C., Marais, G.v.R.,
Van Loosdrecht, M.C.M., "Activated Sludge Model No.2D, ASM2D", 1999,
Wat. Sci. Tech. Vol. 39, No. 1, pp. 165-182

"""

# 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

# Some more information about this module
__author__ = "Andrew Lee, Adam Atia, Xinhong Liu"


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


[docs]@declare_process_block_class("ASM2dParameterBlock") class ASM2dParameterData(PhysicalParameterBlock): """ Property Parameter Block Class """
[docs] def build(self): """ Callable method for Block construction. """ super().build() self._state_block_class = ASM2dStateBlock # Add Phase objects self.Liq = LiquidPhase() # Add Component objects self.H2O = Solvent() # Soluble species self.S_A = Solute( doc="Fermentation products, considered to be acetate. [kg COD/m^3]" ) self.S_F = Solute( doc="Fermentable, readily bio-degradable organic substrates. [kg COD/m^3]" ) self.S_I = Solute(doc="Inert soluble organic material. [kg COD/m^3]") self.S_N2 = Solute( doc="Dinitrogen, N2. SN2 is assumed to be the only nitrogenous product of denitrification. [kg N/m^3]" ) self.S_NH4 = Solute(doc="Ammonium plus ammonia nitrogen. [kg N/m^3]") self.S_NO3 = Solute( doc="Nitrate plus nitrite nitrogen (N03' + N02' -N). SN03 is assumed to include nitrate as well as nitrite nitrogen. [kg N/m^3]" ) self.S_O2 = Solute(doc="Dissolved oxygen. [kg O2/m^3]") self.S_PO4 = Solute( doc="Inorganic soluble phosphorus, primarily ortho-phosphates. [kg P/m^3]" ) self.S_ALK = Component(doc="Alkalinity, [mol HCO3- per m^3]") # Particulate species self.X_AUT = Solute(doc="Autotrophic nitrifying organisms. [kg COD/m^3]") self.X_H = Solute(doc="Heterotrophic organisms. [kg COD/m^3]") self.X_I = Solute(doc="Inert particulate organic material. [kg COD/m^3]") self.X_MeOH = Solute(doc="Metal-hydroxides. [kg TSS/m^3]") self.X_MeP = Solute(doc="Metal-phosphate, MeP04. [kg TSS/m^3]") self.X_PAO = Solute(doc="Phosphate-accumulating organisms. [kg COD/m^3]") self.X_PHA = Solute( doc="A cell internal storage product of phosphorus-accumulating organisms, primarily comprising poly-hydroxy-alkanoates (PHA). [kg COD/m^3]" ) self.X_PP = Solute(doc="Poly-phosphate. [kg P/m^3]") self.X_S = Solute(doc="Slowly biodegradable substrates. [kg COD/m^3]") self.X_TSS = Solute(doc="Total suspended solids, TSS. [kg TSS/m^3]") # Create sets for use across ASM models and associated unit models self.non_particulate_component_set = pyo.Set( initialize=[ "S_A", "S_F", "S_I", "S_N2", "S_NH4", "S_NO3", "S_O2", "S_PO4", "S_ALK", "H2O", ] ) self.particulate_component_set = pyo.Set( initialize=[ "X_AUT", "X_H", "X_I", "X_MeOH", "X_MeP", "X_PAO", "X_PHA", "X_PP", "X_S", "X_TSS", ] ) self.tss_component_set = pyo.Set(initialize=["X_TSS"]) # 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}, } ) obj.define_custom_properties( { "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, } )
[docs]class _ASM2dStateBlock(StateBlock): """ This Class contains methods which should be applied to Property Blocks as a whole, rather than individual elements of indexed Property Blocks. """
[docs] 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_vol : value at which to initialize total volumetric flow (default=None) alkalinity: value of alkalinity expressed as molar concentration conc_mass_comp : value at which to initialize component concentrations (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 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. """ init_log = idaeslog.getInitLogger(self.name, outlvl, tag="properties") if state_vars_fixed is False: # Fix state variables if not already fixed flags = fix_state_vars(self, state_args) else: # Check when the state vars are fixed already result in dof 0 for k in self.keys(): if degrees_of_freedom(self[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: self.release_state(flags) init_log.info("Initialization Complete.")
[docs] def release_state(self, 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(self.name, outlvl, tag="properties") if flags is None: return # Unfix state variables revert_state_vars(self, flags) init_log.info("State Released.")
[docs]@declare_process_block_class("ASM2dStateBlock", block_class=_ASM2dStateBlock) class ASM2dStateBlockData(StateBlockData): """ StateBlock for calculating thermophysical proeprties associated with the ASM2d 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=(273.15, 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, )
[docs] def get_material_flow_terms(self, p, j): if j == "H2O": return self.flow_vol * self.params.dens_mass elif j == "S_ALK": # Convert moles of alkalinity to mass assuming all is HCO3- return ( self.flow_vol * self.alkalinity * (61 * pyo.units.kg / pyo.units.kmol) ) else: return self.flow_vol * self.conc_mass_comp[j]
[docs] def get_enthalpy_flow_terms(self, p): return ( self.flow_vol * self.params.dens_mass * self.params.cp_mass * (self.temperature - self.params.temperature_ref) )
[docs] def get_material_density_terms(self, p, j): if j == "H2O": return self.params.dens_mass elif j == "S_ALK": # Convert moles of alkalinity to mass assuming all is HCO3- return self.alkalinity * (61 * pyo.units.kg / pyo.units.kmol) else: return self.conc_mass_comp[j]
[docs] def get_energy_density_terms(self, p): return ( self.params.dens_mass * self.params.cp_mass * (self.temperature - self.params.temperature_ref) )
def default_material_balance_type(self): return MaterialBalanceType.componentPhase def default_energy_balance_type(self): return EnergyBalanceType.enthalpyTotal
[docs] def define_state_vars(self): return { "flow_vol": self.flow_vol, "alkalinity": self.alkalinity, "conc_mass_comp": self.conc_mass_comp, "temperature": self.temperature, "pressure": self.pressure, }
[docs] def define_display_vars(self): return { "Volumetric Flowrate": self.flow_vol, "Molar Alkalinity": self.alkalinity, "Mass Concentration": self.conc_mass_comp, "Temperature": self.temperature, "Pressure": self.pressure, }
[docs] def get_material_flow_basis(self): return MaterialFlowBasis.mass