KineticGas is our implementation of Revised Enskog Theory for Mie fluids (RET-Mie) and hard sphere mixtures (RET-HS).

Transport coefficients such as diffusion coefficients, thermal diffusion coefficients, viscosities and thermal conductivities in dilute and dense gas mixtures and supercritical mixtures can be predicted with good accuracy using Revised Enskog Theory for Mie fluids.

These transport coefficients can be highly difficult or costly to obtain from simulations or experiments, especially for multicomponent mixtures. The KineticGas package includes Mie potential parameters regressed to equilibrium data with SAFT-VR Mie, which have been shown to give accurate predictions for transport coefficients from the dilute gas region up to densities well exceeding the critical density.

Our implementation utilizes exact summational expressions for the Enskog square bracket integrals to allow efficient prediction of transport properties in multicomponent mixtures up to arbitrary Enskog approximation order, limited only by numerical precision.

The KineticGas package is implemented in C++ with a python wrapper, using ThermoPack for PVT-calculations and computation of thermodynamic factors. The implementation is highly modular, to efficiently support the implementation of other interaction potentials than those currently included in the package. Read more about it here.

Flexible Python wrapper

Easily predict and plot transport coefficients using the RET-Mie and other modern and classic Kinetic Gas theories.

Available for download on github and PIP

A limited feature open-source version of KineticGas is available on github.

Written in C++

Can handle heavy numerical computations associated with process and computational fluid dynamics (CFD) simulations.