6.6 KiB
Gaspype
The python package provides an performant library for thermodynamic calculations like equilibrium reactions for several hundred gas species and their mixtures - written in Python/Numpy.
Species are treated as ideal gases. Therefore the application is limited to moderate pressures or high temperature applications.
Its designed with goal to be portable to Numpy-style GPU frameworks like JAX and PyTorch.
Key features
- Tensor operations to prevent bottlenecks by the python interpreter
- Immutable types
- Elegant pythonic interface
- Great readable and compact syntax when using this package
- Good usability in Jupyter Notebook
- High performance for multidimensional fluid arrays
Installation
Installation with pip:
pip install gaspype
Installation with conda:
conda install conda-forge::gaspype
Getting started
Gaspype provides two main classes: fluid and elements.
Fluid
A fluid class describes a mixture of molecular species and their individual molar amounts.
import gaspype as gp
fl = gp.fluid({'H2O': 1, 'H2': 2})
fl
Total 3.000e+00 mol
H2O 33.33 %
H2 66.67 %
Its' functions provides thermodynamic, mass balance and ideal gas properties of the mixture.
cp = fl.get_cp(t=800+273.15)
mass = fl.get_mass()
gas_volume = fl.get_v(t=800+273.15, p=1e5)
The arguments can be provided as numpy-arrays:
import numpy as np
t_range = np.linspace(600, 800, 5) + 273.15
fl.get_density(t=t_range, p=1e5)
array([0.10122906, 0.09574625, 0.09082685, 0.08638827, 0.08236328])
A fluid object can have multiple compositions. A multidimensional fluid object can be created for example by multiplication with a numpy array:
fl2 = gp.fluid({'H2O': 1, 'N2': 2}) + \
np.linspace(0, 10, 4) * gp.fluid({'H2': 1})
fl2
Total mol:
array([ 3. , 6.33333333, 9.66666667, 13. ])
Species:
H2 H2O N2
Molar fractions:
array([[0. , 0.33333333, 0.66666667],
[0.52631579, 0.15789474, 0.31578947],
[0.68965517, 0.10344828, 0.20689655],
[0.76923077, 0.07692308, 0.15384615]])
A fluid object can be converted to a pandas dataframe:
import pandas as pd
pd.DataFrame(list(fl2))
| H2O | N2 | H2 | |
|---|---|---|---|
| 0 | 1.0 | 2.0 | 0.000000 |
| 1 | 1.0 | 2.0 | 3.333333 |
| 2 | 1.0 | 2.0 | 6.666667 |
| 3 | 1.0 | 2.0 | 10.000000 |
The broadcasting behavior is not limited to 1D-arrays:
fl3 = gp.fluid({'H2O': 1}) + \
np.linspace(0, 10, 4) * gp.fluid({'H2': 1}) + \
np.expand_dims(np.linspace(1, 3, 3), axis=1) * gp.fluid({'N2': 1})
fl3
Total mol:
array([[ 2. , 5.33333333, 8.66666667, 12. ],
[ 3. , 6.33333333, 9.66666667, 13. ],
[ 4. , 7.33333333, 10.66666667, 14. ]])
Species:
H2 H2O N2
Molar fractions:
array([[[0. , 0.5 , 0.5 ],
[0.625 , 0.1875 , 0.1875 ],
[0.76923077, 0.11538462, 0.11538462],
[0.83333333, 0.08333333, 0.08333333]],
[[0. , 0.33333333, 0.66666667],
[0.52631579, 0.15789474, 0.31578947],
[0.68965517, 0.10344828, 0.20689655],
[0.76923077, 0.07692308, 0.15384615]],
[[0. , 0.25 , 0.75 ],
[0.45454545, 0.13636364, 0.40909091],
[0.625 , 0.09375 , 0.28125 ],
[0.71428571, 0.07142857, 0.21428571]]])
Elements
In some cases not the molecular but the atomic composition is of interest. The elements class can be used for atom based balances and works similar:
el = gp.elements({'N': 1, 'Cl': 2})
el.get_mass()
np.float64(0.08490700000000001)
A elements object can be as well instantiated from a fluid object. Arithmetic operations between elements and fluid result in an elements object:
el2 = gp.elements(fl) + el - 0.3 * fl
el2
Cl 2.000e+00 mol
H 4.200e+00 mol
N 1.000e+00 mol
O 7.000e-01 mol
Going from an atomic composition to an molecular composition is a little bit less straight forward, since there is no universal approach. One way is to calculate the thermodynamic equilibrium for a mixture:
fs = gp.fluid_system('CH4, H2, CO, CO2, O2')
el3 = gp.elements({'C': 1, 'H': 2, 'O':1}, fs)
fl3 = gp.equilibrium(el3, t=800)
fl3
Total 1.204e+00 mol
CH4 33.07 %
H2 16.93 %
CO 16.93 %
CO2 33.07 %
O2 0.00 %
The equilibrium function can be called with a fluid or elements object as first argument. fluid and elements referencing a fluid_system object witch can be be set as shown above during the object instantiation. If not provided, a new one will be created automatically. Providing a fluid_system gives more control over which molecular species are included in derived fluid objects. Furthermore arithmetic operations between objects with the same fluid_system are potentially faster:
fl3 + gp.fluid({'CH4': 1}, fs)
Total 2.204e+00 mol
CH4 63.44 %
H2 9.24 %
CO 9.24 %
CO2 18.07 %
O2 0.00 %
Especially if the fluid_system of one of the operants has not a subset of molecular species of the other fluid_system a new fluid_system will be created for the operation which might degrade performance:
fl3 + gp.fluid({'NH3': 1})
Total 2.204e+00 mol
CH4 18.07 %
CO 9.24 %
CO2 18.07 %
H2 9.24 %
NH3 45.38 %
O2 0.00 %
Developer Guide
Contributions are welcome, please open an issue or submit a pull request on GitHub.
To get started with developing the gaspype package, follow these steps.
First, clone the repository to your local machine using Git:
git clone https://github.com/DLR-Institute-of-Future-Fuels/gaspype.git
cd gaspype
It's recommended to setup an venv:
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
Install the package and dev-dependencies while keeping the package files in the current directory:
pip install -e .[dev]
Ensure that everything is set up correctly by running the tests:
pytest
License
This project is licensed under the MIT License - see the LICENSE file for details.