Review and Development of Natural Gas/Hydrogen Fuel Flexible Reduced Chemical Mechanism for High-Order Modeling of Gas Turbines Part II: NOx Chemistry

Abstract Hydrogen is emerging as a key player in reducing carbon emissions, either through pure hydrogen combustion or as an additive to hydrocarbon fuels. While hydrogen offers significant benefits in terms of combustion efficiency, it also presents challenges, such as a higher propensity for flashback and increased NOx emissions. The use of micromixer technology effectively mitigates these concerns in gas turbine applications. However, this technology poses challenges for computational fluid dynamics (CFD) modeling due to the need for accurate representation of both premixed and non-premixed combustion conditions. Accurate chemical modeling is essential for predicting NOx emissions, particularly in such partially premixed combustion systems. This study compares eight chemical mechanisms against experimental NOx emission data. The findings reveal that many mechanisms are typically optimized for either premixed or non-premixed conditions, but not both. Peak NO mole fractions are shown to vary amongst the chemical mechanisms from 15 to 53 ppm for non-premixed flames and 15 to 32 ppm for stoichiometric premixed flames with peak NO concentrations being sensitive to variations in burner distance and fuel-air ratio for the respective combustion regime. CRECK, SD SD, and Han NO were top-performing mechanisms identified by comparing these mechanisms to experimental data from published methane and hydrogen premixed and non-premixed flame studies. Furthermore, the study highlights that hydrogen’s unique diffusion characteristics significantly impact the accuracy of NOx emission predictions, depending on the mechanism employed, the fuel type and the combustion regime. Future work will focus on refining the understanding of the best mechanism performance by categorizing NOx emission contributions across the five main pathways: thermal, prompt, N2O, NNH, and reburning. This will enable more precise modeling and optimization of NOx emissions in hydrogen-fueled combustion systems.