#################################################################################
# WaterTAP Copyright (c) 2020-2026, The Regents of the University of California,
# through Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory,
# National Laboratory of the Rockies, 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/"
#################################################################################
"""
Inherits from a modified CSTR model with injection terms. This model assumes oxygen will be injected.
"""
# Import Pyomo libraries
from pyomo.common.config import In
from pyomo.environ import Constraint
# Import IDAES cores
from idaes.core import (
declare_process_block_class,
)
from idaes.core.scaling import CustomScalerBase, ConstraintScalingScheme
from watertap.unit_models.cstr_injection import (
CSTR_InjectionData,
ElectricityConsumption,
)
__author__ = "Adam Atia"
[docs]class AerationTankScaler(CustomScalerBase):
"""
Default modular scaler for the aeration tank unit model.
This Scaler relies on the associated property and reaction packages,
either through user provided options (submodel_scalers argument) or by default
Scalers assigned to the packages.
"""
DEFAULT_SCALING_FACTORS = {
"volume": 1e-3,
"hydraulic_retention_time": 1e-3,
"KLa": 1e-1,
"mass_transfer_term": 1e2,
}
[docs] def variable_scaling_routine(
self, model, overwrite: bool = False, submodel_scalers: dict = None
):
"""
Routine to apply scaling factors to variables in model.
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
"""
# Call scaling methods for sub-models
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_in,
method="variable_scaling_routine",
submodel_scalers=submodel_scalers,
overwrite=overwrite,
)
self.propagate_state_scaling(
target_state=model.control_volume.properties_out,
source_state=model.control_volume.properties_in,
overwrite=overwrite,
)
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_out,
method="variable_scaling_routine",
submodel_scalers=submodel_scalers,
overwrite=overwrite,
)
self.call_submodel_scaler_method(
submodel=model.control_volume.reactions,
method="variable_scaling_routine",
submodel_scalers=submodel_scalers,
overwrite=overwrite,
)
# Scaling control volume variables
self.scale_variable_by_default(
model.control_volume.volume[0], overwrite=overwrite
)
self.scale_variable_by_default(
model.hydraulic_retention_time[0], overwrite=overwrite
)
self.scale_variable_by_default(model.KLa, overwrite=overwrite)
if model.config.has_aeration:
if "S_O" in model.config.property_package.component_list:
self.scale_variable_by_default(
model.control_volume.mass_transfer_term[0, "Liq", "S_O"],
overwrite=overwrite,
)
elif "S_O2" in model.config.property_package.component_list:
self.scale_variable_by_default(
model.control_volume.mass_transfer_term[0, "Liq", "S_O2"],
overwrite=overwrite,
)
else:
pass
[docs] def constraint_scaling_routine(
self, model, overwrite: bool = False, submodel_scalers: dict = None
):
"""
Routine to apply scaling factors to constraints in model.
Submodel Scalers are called for the property and reaction blocks. All other constraints
are scaled using the inverse maximum scheme.
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
"""
# Call scaling methods for sub-models
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_in,
method="constraint_scaling_routine",
submodel_scalers=submodel_scalers,
overwrite=overwrite,
)
self.call_submodel_scaler_method(
submodel=model.control_volume.properties_out,
method="constraint_scaling_routine",
submodel_scalers=submodel_scalers,
overwrite=overwrite,
)
self.call_submodel_scaler_method(
submodel=model.control_volume.reactions,
method="constraint_scaling_routine",
submodel_scalers=submodel_scalers,
overwrite=overwrite,
)
# Scale unit level constraints
for c in model.component_data_objects(Constraint, descend_into=True):
self.scale_constraint_by_nominal_value(
c,
scheme=ConstraintScalingScheme.inverseMaximum,
overwrite=overwrite,
)
[docs]@declare_process_block_class("AerationTank")
class AerationTankData(CSTR_InjectionData):
"""
CSTR Unit Model with Injection Class
"""
default_scaler = AerationTankScaler
CONFIG = CSTR_InjectionData.CONFIG()
CONFIG.electricity_consumption = ElectricityConsumption.calculated
CONFIG.get("has_aeration")._domain = In([True])
CONFIG.has_aeration = True