gustavochm / esat2021 Goto Github PK

Gustavo Chaparro Maldonado, Andrés Mejía.

Departamento de Ingeniería Química, Universidad De Concepción, Concepción, Chile

Feel free to try the Jupyter Notebooks interactively with MyBinder:

If you have an installation of Python with pip, simply install it with:

$ pip install phasepy

$ pip install SGTPy

To get the git version, run:

$ git clone https://github.com/gustavochm/phasepy

$ git clone https://github.com/gustavochm/SGTPy

Phasepy's documentation is available on the web:

https://phasepy.readthedocs.io/en/latest/

SGTPy's documentation is available on the web (under development):

https://sgtpy.readthedocs.io/en/latest/

Phasepy and SGTPy easily allow you to perform phase equilibria and interfacial properties calculations. Phasepy includes Gibbs excess models and cubic equations of state (EoS) while SGTPy includes SAFT-VR-Mie EoS. For both packages, first, the components are defined with their molecular parameters, then a mixture can be created with them.

>>> import numpy as np
>>> from SGTPy import component, mixture, saftvrmie
>>> ethanol = component('ethanol2C', ms=1.7728, sigma=3.5592 , eps=224.50,
              lambda_r=11.319, lambda_a=6., eAB=3018.05, rcAB=0.3547,
              rdAB=0.4, sites=[1,0,1], cii=5.3141080872882285e-20)
>>> hexane = component('hexane', ms=1.96720036, sigma=4.54762477,
                         eps=377.60127994, lambda_r=18.41193194,
                         cii=3.581510586936205e-19)
>>> mix = mixture(hexane, ethanol)
>>> # fitted to experimental data
>>> kij = 0.011818492037463553
>>> Kij = np.array([[0, kij], [kij, 0]])
>>> mix.kij_saft(Kij)
>>> eos = saftvrmie(mix)

The eos object can be used to compute phase equilibria.

>>> from SGTPy.equilibrium import bubblePy
>>> # computing bubble point
>>> T = 298.15 # K
>>> x = np.array([0.3, 0.7])
>>> # initial guesses for vapor compotision and pressure
>>> y0 = 1.*x
>>> P0 = 8000. # Pa
>>> sol = bubblePy(y0, P0, x, T, eos, full_output=True)

Finally, the equilibria results can be used to model the interfacial behavior of the mixture using SGT.

>>> from SGTPy.sgt import sgt_mix
>>> # reading solution object
>>> y, P = sol.Y, sol.P
>>> vl, vv = sol.v1, sol.v2
>>> #density vector of each phase
>>> rhox = x/vl
>>> rhoy = y/vv
>>> bij = 0.06486106024034907
>>> beta = np.array([[0, bij], [bij, 0]])
>>> eos.beta_sgt(beta)
>>> #solving BVP of SGT with 25 colocation points
>>> solsgt = sgt_mix(rhoy, rhox, T, P, eos, n=25, full_output=True)

For more examples, please have a look at the Jupyter Notebook files located in this repo. Don't forget to try the examples located in phasepy-examples folder and in the SGTPy-examples folder.

Phasepy is part of the article Phasepy: A Python based framework for fluid phase equilibria and interfacial properties computation by Gustavo Chaparro and Andrés Mejía, J Comput Chem. 2020, 41, 29, 2504-2526. https://doi.org/10.1002/jcc.26405.

SGTPy is part of the article SGTPy: A Python open-source code for calculating the interfacial properties of fluids based on the Square Gradient Theory using the SAFT-VR Mie equation of state by Andrés Mejía, Erich A. Müller and Gustavo Chaparro. J. Chem. Inf. Model., 2021, 61, 3, 1244–1250, https://doi.org/10.1021/acs.jcim.0c01324.

Although not required by the phasepy and SGTPy license, if it is convenient for you, please cite phasepy and SGTPy if used in your work. Please also consider contributing any changes you make back, and benefit the community.