ITV-LFS-model: Physics-guided laminar flame speed correlation for methane-hydrogen-air mixtures

Zenodo (CERN European Organization for Nuclear Research)

Abstract

This release updates the repository metadata, citation guidelines, and documentation to coincide with the final peer-reviewed publication of our manuscript in the International Journal of Hydrogen Energy. This repository provides the complete data, parameter sets, and Python framework required to reproduce the modeling and validation results presented in the paper. Key Features Core Physics Framework: Implements the global asymptotic laminar flame speed ($S_L$) correlation and thermodynamic models ($T_b$, $T_i$) for $\text{CH}_4/\text{H}_2/\text{air}$ mixtures with exhaust gas recirculation (EGR). Adaptive Multi-Anchor Blending: Features a dynamic blending algorithm that automatically selects the four optimal parameter anchors (from 0%, 40%, 80%, 95%, and 100% $\text{H}_2$ datasets) to ensure high robustness in hydrogen-dominated regimes. Uncertainty Mapping & OOD Detection: Utilizes 5D nearest-neighbor interpolation on experimental data to map model uncertainty to predictive grids and explicitly filters Out-of-Domain (OOD) queries outside the core robust domain ($\phi \in [0.5, 1.8]$). Automated Workflow & Visualization: Includes run_all.sh for a one-click reproduction pipeline, alongside advanced plotting tools for smooth grid-interpolated heatmaps, log-binned parity density plots, and functional trend comparisons. Licensing This project utilizes a dual-license structure to support open science: Code (PYTHON_MODEL_RUNNER/): MIT License Data & Parameters (MODEL_INPUT/, VAL_DATA/): CC BY 4.0 Citation If you use this model or code in your research, please cite the peer-reviewed journal article. A native CITATION.cff is included in the root directory for seamless reference management, and the updated BibTeX is available in the README.md. Journal DOI: 10.1016/j.ijhydene.2026.156313 Software Archive DOI: 10.5281/zenodo.21164326

Authors 6

1. Raik Hesse Aachen Institute for Combustion Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Combustion Technology, RWTH Aachen University

2. Christian Schwenzer Aachen Institute for Combustion Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Combustion Technology, RWTH Aachen University

3. Roman Glaznev Aachen Institute for Combustion Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Combustion Technology, RWTH Aachen University

4. Florence Cameron Aachen Institute for Combustion Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Combustion Technology, RWTH Aachen University

5. Heinz Pitsch Aachen Institute for Combustion Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Combustion Technology, RWTH Aachen University

6. Joachim Beeckmann Aachen Institute for Combustion Technology

   RWTH Aachen University

   Affiliation as printed

   Institute for Combustion Technology, RWTH Aachen University