Physics-guided laminar flame speed correlation for methane-hydrogen-air mixtures with varying dilution

TL;DR

This paper presents a physics-guided laminar flame speed correlation for methane-hydrogen-air mixtures, enabling accurate, efficient, and physically consistent predictions across various combustion systems and conditions.

Contribution

A novel, physics-based flame speed correlation that accurately predicts LFS for methane-hydrogen mixtures, validated against extensive simulations and experimental data.

Findings

Model achieves accuracy comparable to machine learning methods.

Correlation remains physically consistent, differentiable, and extrapolates well.

Validated with experimental data and high-fidelity simulations.

Abstract

Fuel-flexible, low-carbon combustion systems need to accommodate methane/hydrogen mixtures with air and exhaust-gas dilution. To develop these, we require accurate and efficient correlations for laminar flame speed (LFS). In this work, we introduce a physics-guided LFS correlation that applies to burners, gas engines, and turbines. Our model uses a core-kinetic approach based on flame temperatures, an algebraic function for the equivalence ratio, and a mass-flux-based blending law. This allows for accurate predictions with any methane/hydrogen blend. We set the model parameters using one-dimensional flame simulations with C3Mech v4.0.1, chosen for its high prediction accuracy for a wide range of experimental data, including new results from our spherical combustion chamber. The new correlation provides accuracy comparable to a machine learning approach (Gaussian process regression), yet remains physically consistent, differentiable, and extrapolates well. This makes it suitable for computational fluid dynamics and control of fuel-flexible combustion systems.