# -*- coding: utf-8 -*-
# BioSTEAM: The Biorefinery Simulation and Techno-Economic Analysis Modules
# Copyright (C) 2020-2023, Yoel Cortes-Pena <yoelcortes@gmail.com>
#
# This module is under the UIUC open-source license. See
# github.com/BioSTEAMDevelopmentGroup/biosteam/blob/master/LICENSE.txt
# for license details.
"""
"""
from ..base import display_asfunctor, SparseVector
from math import log
__all__ = (
'IdealTMixtureModel', 'IdealTPMixtureModel', 'IdealEntropyModel',
'IdealHvapModel', 'SinglePhaseIdealTMixtureModel', 'SinglePhaseIdealTPMixtureModel',
)
[docs]
class IdealTPMixtureModel:
"""
Create an IdealTPMixtureModel object that calculates mixture properties
based on the molar weighted sum of pure chemical properties.
Parameters
----------
models : Iterable[function(T, P)]
Chemical property functions of temperature and pressure.
var : str
Description of thermodynamic variable returned.
Notes
-----
:class:`Mixture` objects can contain IdealMixtureModel objects to establish
as mixture model for thermodynamic properties.
See also
--------
:class:`Mixture`
:func:`~.mixture_builders.ideal_mixture`
Examples
--------
>>> from thermosteam.mixture import IdealTPMixtureModel
>>> from thermosteam import Chemicals
>>> chemicals = Chemicals(['Water', 'Ethanol'])
>>> models = [i.V for i in chemicals]
>>> mixture_model = IdealTPMixtureModel(models, 'V')
>>> mixture_model
<IdealTPMixtureModel(phase, mol, T, P) -> V [m^3/mol]>
>>> mixture_model('l', [0.2, 0.8], 350, 101325)
5.364...-05
"""
__slots__ = ('var', 'models')
def __init__(self, models, var):
self.models = tuple(models)
self.var = var
def __call__(self, phase, mol, T, P):
if mol.__class__ is not SparseVector: mol = SparseVector(mol)
models = self.models
return sum([j * models[i](phase, T, P) for i, j in mol.dct.items()])
def __repr__(self):
return f"<{display_asfunctor(self)}>"
class IdealEntropyModel:
"""
Create an IdealEntropyModel object that calculates entropy of a mixture
based on the molar weighted sum of pure chemical properties.
Parameters
----------
models : Iterable[function(T, P)]
Chemical property functions of temperature and pressure.
var : str
Description of thermodynamic variable returned.
Notes
-----
:class:`Mixture` objects can contain IdealMixtureModel objects to establish
as mixture model for thermodynamic properties.
See also
--------
:class:`Mixture`
:func:`~.mixture_builders.ideal_mixture`
Examples
--------
>>> from thermosteam.mixture import IdealEntropyModel
>>> from thermosteam import Chemicals
>>> import numpy as np
>>> chemicals = Chemicals(['Water', 'Ethanol'])
>>> models = [i.S for i in chemicals]
>>> mixture_model = IdealEntropyModel(models, 'S')
>>> mixture_model
<IdealEntropyModel(phase, mol, T, P) -> S [J/K/mol]>
>>> mixture_model('l', np.array([0.2, 0.8]), 350, 101325)
160.174
"""
__slots__ = IdealTPMixtureModel.__slots__
__init__ = IdealTPMixtureModel.__init__
__repr__ = IdealTPMixtureModel.__repr__
def __call__(self, phase, mol, T, P):
if mol.__class__ is not SparseVector: mol = SparseVector(mol)
total_mol = mol.sum()
models = self.models
return sum([j * models[i](phase, T, P) + j * log(j / total_mol) for i, j in mol.dct.items()])
[docs]
class IdealTMixtureModel:
"""
Create an IdealTMixtureModel object that calculates mixture properties
based on the molar weighted sum of pure chemical properties.
Parameters
----------
models : Iterable[function(T, P)]
Chemical property functions of temperature and pressure.
var : str
Description of thermodynamic variable returned.
Notes
-----
:class:`Mixture` objects can contain IdealMixtureModel objects to establish
as mixture model for thermodynamic properties.
See also
--------
:class:`Mixture`
Examples
--------
>>> from thermosteam.mixture import IdealTMixtureModel
>>> from thermosteam import Chemicals
>>> chemicals = Chemicals(['Water', 'Ethanol'])
>>> models = [i.Cn for i in chemicals]
>>> mixture_model = IdealTMixtureModel(models, 'Cn')
>>> mixture_model
<IdealTMixtureModel(phase, mol, T, P=None) -> Cn [J/mol/K]>
>>> mixture_model('l', [0.2, 0.8], 350)
122.529
"""
__slots__ = IdealTPMixtureModel.__slots__
__init__ = IdealTPMixtureModel.__init__
__repr__ = IdealTPMixtureModel.__repr__
def __call__(self, phase, mol, T, P=None):
if mol.__class__ is not SparseVector: mol = SparseVector(mol)
models = self.models
return sum([j * models[i](phase, T) for i, j in mol.dct.items()])
class SinglePhaseIdealTMixtureModel:
"""
Create an SinglePhaseIdealTMixtureModel object that calculates mixture properties
based on the molar weighted sum of pure chemical properties.
Parameters
----------
models : Iterable[function(T, P)]
Chemical property functions of temperature and pressure.
var : str
Description of thermodynamic variable returned.
Notes
-----
:class:`Mixture` objects can contain IdealMixtureModel objects to establish
as mixture model for thermodynamic properties.
See also
--------
:class:`Mixture`
Examples
--------
>>> from thermosteam.mixture import SinglePhaseIdealTMixtureModel
>>> from thermosteam import Chemicals
>>> chemicals = Chemicals(['Water', 'Ethanol'])
>>> models = [i.Psat for i in chemicals]
>>> mixture_model = SinglePhaseIdealTMixtureModel(models, 'Psat')
>>> mixture_model
<SinglePhaseIdealTMixtureModel(mol, T, P=None) -> Psat [Pa]>
>>> mixture_model([0.2, 0.8], 350)
84499.12
"""
__slots__ = IdealTPMixtureModel.__slots__
__init__ = IdealTPMixtureModel.__init__
__repr__ = IdealTPMixtureModel.__repr__
def __call__(self, mol, T, P=None):
if mol.__class__ is not SparseVector: mol = SparseVector(mol)
models = self.models
return sum([j * models[i](T) for i, j in mol.dct.items()])
class SinglePhaseIdealTPMixtureModel:
"""
Create an IdealTPMixtureModel object that calculates mixture properties
based on the molar weighted sum of pure chemical properties.
Parameters
----------
models : Iterable[function(T, P)]
Chemical property functions of temperature and pressure.
var : str
Description of thermodynamic variable returned.
Notes
-----
:class:`Mixture` objects can contain IdealMixtureModel objects to establish
as mixture model for thermodynamic properties.
See also
--------
:class:`Mixture`
:func:`~.mixture_builders.ideal_mixture`
Examples
--------
>>> from thermosteam.mixture import SinglePhaseIdealTPMixtureModel
>>> from thermosteam import Chemicals
>>> chemicals = Chemicals(['Water', 'Ethanol'])
>>> models = [i.V.l for i in chemicals]
>>> mixture_model = SinglePhaseIdealTPMixtureModel(models, 'V')
>>> mixture_model
<SinglePhaseIdealTPMixtureModel(mol, T, P) -> V [m^3/mol]>
>>> mixture_model([0.2, 0.8], 350, 101325)
5.3640...-05
"""
__slots__ = ('var', 'models')
def __init__(self, models, var):
self.models = tuple(models)
self.var = var
def __call__(self, mol, T, P):
if mol.__class__ is not SparseVector: mol = SparseVector(mol)
models = self.models
return sum([j * models[i](T, P) for i, j in mol.dct.items()])
def __repr__(self):
return f"<{display_asfunctor(self)}>"
class IdealHvapModel:
__slots__ = ('chemicals',)
var = 'Hvap'
def __init__(self, chemicals):
self.chemicals = chemicals
def __call__(self, mol, T, P=None):
if mol.__class__ is not SparseVector: mol = SparseVector(mol)
chemicals = self.chemicals
return sum([
j * k.Hvap(T) for i, j in mol.dct.items()
if not (k:=chemicals[i]).locked_state
])
__repr__ = IdealTPMixtureModel.__repr__
