Tutorial on WDK-VENUS: A Streamlined and Modular Workflow for High-Temperature Dynamics and Kinetics of Atom–Diatom Collisions

High-precision dynamic simulations of hypersonic flows are crucial for high-temperature aerodynamics, particularly in addressing nonequilibrium effects in turbulent flows. The quasi-classical trajectory (QCT) method, based on microscopic molecular collisions, is a key approach to tackle this challenge. By generating state-to-state (StS) integral cross sections (ICSs), QCT simulations enable detailed modeling of high-temperature thermochemical nonequilibrium flows. However, existing dynamic programs do not have an automated workflow that converts trajectory data into reaction rate coefficients. This work introduces WDK-VENUS, a modular QCT workflow for dynamics and kinetics of atom-diatom (A + BC) collisions built upon the VENUS program. The VENUS program is amended to enable handling high rovibrational states. An automated and efficient <i>b</i> _max test module is introduced. Additionally, an external Python code is provided with four modules: sampling, Gaussian process regression (GPR), model validation, and equilibrium/nonequilibrium rate coefficient calculation. The main function of this workflow is to use GPR machine learning methods to fit models, export large amounts of high-precision ICSs, and calculate equilibrium/nonequilibrium rate coefficients with less human intervention. The modular design of WDK-VENUS simplifies QCT calculations, supports batch processing, and integrates Python analysis tools. This workflow is expected to facilitate broader applications in interdisciplinary fields.