###############################################################################
# WaterTAP Copyright (c) 2021, 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.
#
# 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
# "https://github.com/watertap-org/watertap/"
#
###############################################################################
"""
This module contains a zero-order representation of a fixed bed unit
operation.
"""
from pyomo.environ import units as pyunits, Var
from idaes.core import declare_process_block_class
from watertap.core import build_siso, constant_intensity, ZeroOrderBaseData
# Some more information about this module
__author__ = "Adam Atia"
[docs]@declare_process_block_class("FixedBedZO")
class FixedBedZOData(ZeroOrderBaseData):
"""
Zero-Order model for an Ion exchange unit operation.
"""
CONFIG = ZeroOrderBaseData.CONFIG()
[docs] def build(self):
super().build()
self._tech_type = "fixed_bed"
build_siso(self)
constant_intensity(self)
self.recovery_frac_mass_H2O.fix(1)
# Chemical demands
self.acetic_acid_dose = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Dosing rate of acetic acid",
)
self.phosphoric_acid_dose = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Dosing rate of phosphoric acid",
)
self.ferric_chloride_dose = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Dosing rate of ferric chloride",
)
self._fixed_perf_vars.append(self.acetic_acid_dose)
self._fixed_perf_vars.append(self.phosphoric_acid_dose)
self._fixed_perf_vars.append(self.ferric_chloride_dose)
self.acetic_acid_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Consumption rate of acetic acid",
)
self.phosphoric_acid_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Consumption rate of phosphoric acid",
)
self.ferric_chloride_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Consumption rate of ferric chloride",
)
self._perf_var_dict["Acetic Acid Demand"] = self.acetic_acid_demand
self._perf_var_dict["Phosphoric Acid Demand"] = self.phosphoric_acid_demand
self._perf_var_dict["Ferric Chlorided Demand"] = self.ferric_chloride_demand
@self.Constraint(self.flowsheet().time, doc="Acetic acid demand constraint")
def acetic_acid_demand_equation(b, t):
return b.acetic_acid_demand[t] == pyunits.convert(
b.acetic_acid_dose * b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)
@self.Constraint(self.flowsheet().time, doc="Phosphoric acid demand constraint")
def phosphoric_acid_demand_equation(b, t):
return b.phosphoric_acid_demand[t] == pyunits.convert(
b.phosphoric_acid_dose * b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)
@self.Constraint(self.flowsheet().time, doc="Acetic acid demand constraint")
def ferric_chloride_demand_equation(b, t):
return b.ferric_chloride_demand[t] == pyunits.convert(
b.ferric_chloride_dose * b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)
# Activated Carbon demand
self.activated_carbon_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Replacement rate for activated carbon",
)
self.activated_carbon_parameter_a = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Pre-exponential factor for activated carbon demand",
)
self.activated_carbon_parameter_b = Var(
units=pyunits.dimensionless,
bounds=(None, None),
doc="Exponential factor for activated carbon demand",
)
self._fixed_perf_vars.append(self.activated_carbon_parameter_a)
self._fixed_perf_vars.append(self.activated_carbon_parameter_b)
self._perf_var_dict["Activated Carbon Demand"] = self.activated_carbon_demand
@self.Constraint(
self.flowsheet().time, doc="Activated carbon demand constraint"
)
def activated_carbon_demand_equation(b, t):
return b.activated_carbon_demand[t] == pyunits.convert(
b.activated_carbon_parameter_a
* pyunits.convert(
b.properties_in[t].flow_vol / (pyunits.m**3 / pyunits.hour),
to_units=pyunits.dimensionless,
)
** b.activated_carbon_parameter_b
* b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)
# Sand demand
self.sand_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Replacement rate for sand",
)
self.sand_parameter_a = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Pre-exponential factor for sand demand",
)
self.sand_parameter_b = Var(
units=pyunits.dimensionless,
bounds=(None, None),
doc="Exponential factor for sand demand",
)
self._fixed_perf_vars.append(self.sand_parameter_a)
self._fixed_perf_vars.append(self.sand_parameter_b)
self._perf_var_dict["Sand Demand"] = self.sand_demand
@self.Constraint(self.flowsheet().time, doc="Sand demand constraint")
def sand_demand_equation(b, t):
return b.sand_demand[t] == pyunits.convert(
b.sand_parameter_a
* pyunits.convert(
b.properties_in[t].flow_vol / (pyunits.m**3 / pyunits.hour),
to_units=pyunits.dimensionless,
)
** b.sand_parameter_b
* b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)
# Anthracite demand
self.anthracite_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Replacement rate for anthracite",
)
self.anthracite_parameter_a = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Pre-exponential factor for anthracite demand",
)
self.anthracite_parameter_b = Var(
units=pyunits.dimensionless,
bounds=(None, None),
doc="Exponential factor for anthracite demand",
)
self._fixed_perf_vars.append(self.anthracite_parameter_a)
self._fixed_perf_vars.append(self.anthracite_parameter_b)
self._perf_var_dict["Anthracite Demand"] = self.anthracite_demand
@self.Constraint(self.flowsheet().time, doc="Anthracite demand constraint")
def anthracite_demand_equation(b, t):
return b.anthracite_demand[t] == pyunits.convert(
b.anthracite_parameter_a
* pyunits.convert(
b.properties_in[t].flow_vol / (pyunits.m**3 / pyunits.hour),
to_units=pyunits.dimensionless,
)
** b.anthracite_parameter_b
* b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)
# Cationic polymer demand
self.cationic_polymer_demand = Var(
self.flowsheet().time,
units=pyunits.kg / pyunits.hr,
bounds=(0, None),
doc="Replacement rate for cationic polymer",
)
self.cationic_polymer_parameter_a = Var(
units=pyunits.kg / pyunits.m**3,
bounds=(0, None),
doc="Pre-exponential factor for cationic polymer demand",
)
self.cationic_polymer_parameter_b = Var(
units=pyunits.dimensionless,
bounds=(None, None),
doc="Exponential factor for cationic polymer demand",
)
self._fixed_perf_vars.append(self.cationic_polymer_parameter_a)
self._fixed_perf_vars.append(self.cationic_polymer_parameter_b)
self._perf_var_dict["Cationic Polymer Demand"] = self.cationic_polymer_demand
@self.Constraint(
self.flowsheet().time, doc="Cationic Polymer demand constraint"
)
def cationic_polymer_demand_equation(b, t):
return b.cationic_polymer_demand[t] == pyunits.convert(
b.cationic_polymer_parameter_a
* pyunits.convert(
b.properties_in[t].flow_vol / (pyunits.m**3 / pyunits.hour),
to_units=pyunits.dimensionless,
)
** b.cationic_polymer_parameter_b
* b.properties_in[t].flow_vol,
to_units=pyunits.kg / pyunits.hr,
)