Experimental and numerical study of laminar flame extinction for syngas and syngas-methane blends

ABSTRACT

Extinction strain rates of syngas and syngas–methane blends at atmospheric pressure were investigated in laminar counter-flow diffusion flames as a function of nitrogen dilution through both experiment and two-dimensional axisymmetric full-domain numerical simulations. Three representative compositions of syngas were examined along with two syngas–methane blends for a range of fuel mole fractions. An opposed-jet burner configuration with straight-tube fuel and air nozzles was used in the experiments and an advanced, computational, solution algorithm was used to obtain the corresponding simulation results. Very good agreement was found between predicted and experimentally observed flame structure as well as global strain rate extinction limits for all syngas fuel and syngas–methane blends over the full range of flow rates and fuel mole fractions considered. Additionally, the local strain rate near extinction was shown to correlate with the global strain rate and an explanation of the differences between these two values was provided by the predicted changes in the nozzle exit plane velocity profiles as a function of flow rate. In particular, non-zero gradients in the axial center-line velocity were predicted at the nozzle exit plane for higher flow rates due to the pressure field created by the opposed-jet flows. The syngas extinction limits as a function of fuel composition were examined. While the amount of hydrogen was found to have a dominant effect on the extinction strain limits, methane and carbon monoxide were also found to induce early extinction and increase reactivity, respectively, if present in sufficiently large quantities.

KEY WORDS:

• Biofuels
• Syngas
• Syngas–methane blends
• Flame extinction
• Extinction strain rate
• Counter-flow laminar diffusion flames

Additional information

Funding

This work was supported by grants from the Ontario Research Fund Research Excellence (ORF-RE) Program and the Southern Ontario Smart Computing for Innovation Platform (SOSCIP) of the Province of Ontario. Computational resources for performing simulations reported in the paper were provided by the SOSCIP program as well as the SciNet High Performance Computing Consortium at the University of Toronto and Compute/Calcul Canada through funding from the Canada Foundation for Innovation (CFI) and the Province of Ontario, Canada.