vle-thermo 0.1.1

Vapor-liquid equilibrium (VLE) thermodynamic calculator: 22+ cubic EOS, activity models, flash algorithms

vle-thermo

Vapor-liquid equilibrium (VLE) thermodynamic calculator with a Rust computation engine and a Python interface.

A modern Rust + Python port of two legacy thermodynamic codebases (VB6 ~15,000 lines + Pascal ~2,500 lines). The Rust core (vle-thermo crate) does the computation; this Python package wraps it for interactive use in scripts and Jupyter notebooks.

Install

pip install vle-thermo

Optional extras:

pip install "vle-thermo[plot]"   # adds matplotlib
pip install "vle-thermo[db]"     # adds `thermo` for extended component-database seeding
pip install "vle-thermo[dev]"    # adds pytest, maturin

The distribution name on PyPI is vle-thermo, but the import name is vle (following the common distribution-vs-import split, like Pillow → import PIL or python-dateutil → import dateutil):

import vle

Status

0.1.x — the component database, CLI, and units layer work today. Numerical kernels (flash algorithms, equation-of-state solvers, parameter regression) are under active development. Treat 0.1.x as pre-release; semver promises begin at 1.0.

See the roadmap for what's shipped vs. planned.

What works today

# Initialize the bundled component database (SQLite) and seed with the 15
# compounds from Chapter IV of the source thesis.
vle-db init
vle-db seed --source chapter4

# Browse and inspect
vle-db list
vle-db show methane
vle-db validate chapter4

from vle.db import list_components, get_component

for c in list_components():
    print(c.name, c.tc, c.pc, c.omega)

methane = get_component("methane")

Unit-aware input/output (gauge pressure, °C, °F, psi, barg, mmHg, …):

from vle.units import ureg, Q_

T = Q_(25, "degC")                # 298.15 K internally
P = Q_(3.5, "bar").to("kPa")      # 350 kPa

Features (full roadmap)

• 22+ cubic equations of state — Peng-Robinson, RKS, van der Waals, Schmidt-Wenzel, Patel-Teja, and more
• 5 activity coefficient models — Wilson, van Laar, Margules, Scatchard-Hildebrand, Ideal
• 11 mixing rules — Classical (IVDW, IIVDW), Wong-Sandler, Huron-Vidal, MHV1/MHV2
• 6 saturation pressure correlations — Antoine, Riedel, Müller, RPM
• 6 flash calculation types — bubble/dew point (T/P), isothermal (Rachford-Rice), adiabatic
• Parameter regression — kij (binary interaction) and Aij (activity model)

Use it in Jupyter

A curated set of notebooks reproducing Chapter IV of the source thesis ships alongside the project at https://github.com/miguelju/vle/tree/main/notebooks. To run them in your own environment:

pip install "vle-thermo[plot]" jupyterlab
git clone https://github.com/miguelju/vle.git
cd vle/notebooks
jupyter lab

For a zero-setup option, a ready-to-run Docker image is published at ghcr.io/miguelju/vle-thermo:

docker run --rm -p 8888:8888 ghcr.io/miguelju/vle-thermo:latest

Origin

Based on the thesis "Desarrollo de un Programa Computacional para el Cálculo del Equilibrio Líquido Vapor de Mezclas Multicomponentes bajo el Ambiente Windows" (Jackson & Mendible, Universidad Simón Bolívar, 1999), with additional models from Da Silva & Báez (1989). See the research paper (English translation) for algorithms, parameters, and their academic references.

License

MIT. See LICENSE.