Gaspype

The Python package provides a 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.

It is designed with goal to be portable to NumPy-style GPU frameworks like JAX and PyTorch.

Key Features

• Pure Python implementation with NumPy vectorization for high performance
• Immutable types and comprehensive type hints for reliability
• Intuitive, Pythonic API for both rapid prototyping and complex multidimensional models
• Ready for Jupyter Notebook and educational use
• Designed for future GPU support (JAX, PyTorch)
• Ships with a comprehensive NASA9-based species database

Installation

Installation with pip: bash pip install gaspype

Installation with conda: bash 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.

python 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.

python 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:

python 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:

python 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: python 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:

python 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:

python 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: python 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 possible as well. One way is to calculate the thermodynamic equilibrium for a mixture:

python 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:

python 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:

python 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:

bash git clone https://github.com/DLR-Institute-of-Future-Fuels/gaspype.git cd gaspype

It's recommended to setup an venv:

bash 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:

bash pip install -e .[dev]

Compile binary property database from text based files:

bash python thermo_data/combine_data.py thermo_data/combined_data.yaml thermo_data/nasa9*.yaml thermo_data/nasa9*.xml python thermo_data/compile_to_bin.py thermo_data/combined_data.yaml src/gaspype/data/therm_data.bin

Ensure that everything is set up correctly by running the tests:

bash pytest

License

This project is licensed under the MIT License - see the LICENSE file for details.