Thermo Save

Thermodynamics and Phase Equilibrium component of Chemical Engineering Design Library (ChEDL)

Project README

====== Thermo

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.. contents::

What is Thermo?

Thermo is open-source software for engineers, scientists, technicians and anyone trying to understand the universe in more detail. It facilitates the retrieval of constants of chemicals, the calculation of temperature and pressure dependent chemical properties (both thermodynamic and transport), and the calculation of the same for chemical mixtures (including phase equilibria) using various models.

Thermo runs on all operating systems which support Python, is quick to install, and is free of charge. Thermo is designed to be easy to use while still providing powerful functionality. If you need to know something about a chemical or mixture, give Thermo a try.

Installation

Get the latest version of Thermo from https://pypi.python.org/pypi/thermo/

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

$ pip install thermo

Alternatively, if you are using conda <https://conda.io/en/latest/>_ as your package management, you can simply install Thermo in your environment from conda-forge <https://conda-forge.org/>_ channel with:

$ conda install -c conda-forge thermo

To get the git version, run:

$ git clone git://github.com/CalebBell/thermo.git

Documentation

Thermo's documentation is available on the web:

http://thermo.readthedocs.io/

Getting Started - Rigorous Interface

Create a pure-component flash object for the compound "decane", using the Peng-Robinson equation of state. Perform a flash calculation at 300 K and 1 bar, and obtain a variety of properties from the resulting object:

.. code-block:: python

>>> from thermo import ChemicalConstantsPackage, PRMIX, CEOSLiquid, CEOSGas, FlashPureVLS
>>> # Load the constant properties and correlation properties
>>> constants, correlations = ChemicalConstantsPackage.from_IDs(['decane'])
>>> # Configure the liquid and gas phase objects
>>> eos_kwargs = dict(Tcs=constants.Tcs, Pcs=constants.Pcs, omegas=constants.omegas)
>>> liquid = CEOSLiquid(PRMIX, HeatCapacityGases=correlations.HeatCapacityGases, eos_kwargs=eos_kwargs)
>>> gas = CEOSGas(PRMIX, HeatCapacityGases=correlations.HeatCapacityGases, eos_kwargs=eos_kwargs)
>>> # Create a flash object with possible phases of 1 gas and 1 liquid
>>> flasher = FlashPureVLS(constants, correlations, gas=gas, liquids=[liquid], solids=[])
>>> # Flash at 300 K and 1 bar
>>> res = flasher.flash(T=300, P=1e5)
>>> # molar enthalpy and entropy [J/mol and J/(mol*K) respectively] and the mass enthalpy and entropy [J/kg and J/(kg*K)]
>>> res.H(), res.S(), res.H_mass(), res.S_mass()
(-48458.137745529726, -112.67831317511894, -340578.897757812, -791.9383098029132)
>>> # molar Cp and Cv [J/(mol*K)] and the mass Cp and Cv [J/(kg*K)]
>>> res.Cp(), res.Cv(), res.Cp_mass(), res.Cv_mass()
(295.17313861592686, 269.62465319082014, 2074.568831461133, 1895.0061117553582)
>>> # Molar volume [m^3/mol], molar density [mol/m^3] and mass density [kg/m^3]
>>> res.V(), res.rho(), res.rho_mass()
(0.00020989856076374984, 4764.206082982839, 677.8592453530177)
>>> # isobatic expansion coefficient [1/K], isothermal compressibility [1/Pa], Joule Thomson coefficient [K/Pa]
>>> res.isobaric_expansion(), res.kappa(), res.Joule_Thomson()
(0.0006977350520992281, 1.1999043797490713e-09, -5.622547043844744e-07)
>>> # Speed of sound in molar [m*kg^0.5/(s*mol^0.5)] and mass [m/s] units
>>> res.speed_of_sound(), res.speed_of_sound_mass()
(437.61281158744987, 1160.1537167375043)

The following example shows the retrieval of chemical properties for a two-phase system with methane, ethane, and nitrogen, using a few sample kijs:

.. code-block:: python

>>> from thermo import ChemicalConstantsPackage, CEOSGas, CEOSLiquid, PRMIX, FlashVL
>>> from thermo.interaction_parameters import IPDB
>>> constants, properties = ChemicalConstantsPackage.from_IDs(['methane', 'ethane', 'nitrogen'])
>>> kijs = IPDB.get_ip_asymmetric_matrix('ChemSep PR', constants.CASs, 'kij')
>>> kijs
[[0.0, -0.0059, 0.0289], [-0.0059, 0.0, 0.0533], [0.0289, 0.0533, 0.0]]
>>> eos_kwargs = {'Pcs': constants.Pcs, 'Tcs': constants.Tcs, 'omegas': constants.omegas, 'kijs': kijs}
>>> gas = CEOSGas(PRMIX, eos_kwargs=eos_kwargs, HeatCapacityGases=properties.HeatCapacityGases)
>>> liquid = CEOSLiquid(PRMIX, eos_kwargs=eos_kwargs, HeatCapacityGases=properties.HeatCapacityGases)
>>> flasher = FlashVL(constants, properties, liquid=liquid, gas=gas)
>>> zs = [0.965, 0.018, 0.017]
>>> PT = flasher.flash(T=110.0, P=1e5, zs=zs)
>>> PT.VF, PT.gas.zs, PT.liquid0.zs
(0.10365, [0.881788, 2.6758e-05, 0.11818], [0.97462, 0.02007, 0.005298])
>>> flasher.flash(P=1e5, VF=1, zs=zs).T
133.6
>>> flasher.flash(T=133, VF=0, zs=zs).P
518367.4
>>> flasher.flash(P=PT.P, H=PT.H(), zs=zs).T
110.0
>>> flasher.flash(P=PT.P, S=PT.S(), zs=zs).T
110.0
>>> flasher.flash(T=PT.T, H=PT.H(), zs=zs).T
110.0
>>> flasher.flash(T=PT.T, S=PT.S(), zs=zs).T
110.0

There is also a N-phase flash algorithm available, FlashVLN. There are no solid models implemented in this interface at this time.

Getting Started - Simple Interface

The library is designed around base SI units only for development convenience. All chemicals default to 298.15 K and 101325 Pa on creation, unless specified. All constant-properties are loaded on the creation of a Chemical instance.

.. code-block:: python

>>> from thermo.chemical import Chemical
>>> tol = Chemical('toluene')
>>> tol.Tm, tol.Tb, tol.Tc
(179.2, 383.75, 591.75)
>>> tol.rho, tol.Cp, tol.k, tol.mu
(862.238, 1706.07, 0.13034, 0.0005522)

For pure species, the phase is easily identified, allowing for properties to be obtained without needing to specify the phase. However, the properties are also available in the hypothetical gas phase (when under the boiling point) and in the hypothetical liquid phase (when above the boiling point) as these properties are needed to evaluate mixture properties. Specify the phase of a property to be retrieved by appending 'l' or 'g' or 's' to the property.

.. code-block:: python

>>> from thermo.chemical import Chemical
>>> tol = Chemical('toluene')
>>> tol.rhog, tol.Cpg, tol.kg, tol.mug
(4.0320096, 1126.553, 0.010736, 6.97332e-06)

Creating a chemical object involves identifying the appropriate chemical by name through a database, and retrieving all constant and temperature and pressure dependent coefficients from Pandas DataFrames - a ~1 ms process. To obtain properties at different conditions quickly, the method calculate has been implemented.

.. code-block:: python

>>> tol.calculate(T=310, P=101325)
>>> tol.rho, tol.Cp, tol.k, tol.mu
(851.1582219886011, 1743.280497511088, 0.12705495902514785, 0.00048161578053599225)
>>> tol.calculate(310, 2E6)
>>> tol.rho, tol.Cp, tol.k, tol.mu
(852.7643604407997, 1743.280497511088, 0.12773606382684732, 0.0004894942399156052)

Each property is implemented through an independent object-oriented method, based on the classes TDependentProperty and TPDependentProperty to allow for shared methods of plotting, integrating, differentiating, solving, interpolating, sanity checking, and error handling. For example, to solve for the temperature at which the vapor pressure of toluene is 2 bar. For each property, as many methods of calculating or estimating it are included as possible. All methods can be visualized independently:

.. code-block:: python

>>> Chemical('toluene').VaporPressure.solve_property(2E5)
409.5909115602903
>>> Chemical('toluene').SurfaceTension.plot_T_dependent_property()

Mixtures are supported and many mixing rules have been implemented. However, there is no error handling. Inputs as mole fractions (zs), mass fractions (ws), or volume fractions (Vfls or Vfgs) are supported. Some shortcuts are supported to predefined mixtures.

.. code-block:: python

>>> from thermo.chemical import Mixture
>>> vodka = Mixture(['water', 'ethanol'], Vfls=[.6, .4], T=300, P=1E5)
>>> vodka.Prl,vodka.Prg
(35.13075699606542, 0.9822705235442692)
>>> air = Mixture('air', T=400, P=1e5)
>>> air.Cp
1013.7956176577836

Warning: The phase equilibria of Chemical and Mixture are not presently as rigorous as the other interface. The property model is not particularly consistent and uses a variety of ideal and Peng-Robinson methods together.

Latest source code

The latest development version of Thermo's sources can be obtained at

https://github.com/CalebBell/thermo

Bug reports

To report bugs, please use the Thermo's Bug Tracker at:

https://github.com/CalebBell/thermo/issues

License information

See LICENSE.txt for information on the terms & conditions for usage of this software, and a DISCLAIMER OF ALL WARRANTIES.

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

Citation

To cite Thermo in publications use::

Caleb Bell and Contributors (2016-2023). Thermo: Chemical properties component of Chemical Engineering Design Library (ChEDL)
https://github.com/CalebBell/thermo.
Open Source Agenda is not affiliated with "Thermo" Project. README Source: CalebBell/thermo