Effects of Radiation Model on Soot Modeling in Laminar Coflow Diffusion Flames at Elevated Pressure

ABSTRACT

Detailed numerical simulations of C₂H₄/Air coflow laminar sooting flames at atmospheric and elevated pressures are performed with fully coupled flow, gas-phase reactions, soot dynamics, and nongray radiative heat transfer. The soot dynamics is modeled using a hybrid method of moments combined with a polycyclic aromatic hydrocarbon (PAH) mechanism. Nongray radiative heat transfer by CO₂, H₂O, and soot is calculated using different methods to study the effect of radiation model on the predictions. The discrete ordinates radiation model (DOM) and P1 radiation model are compared. Three radiative property models with different accuracy and efficiency are included: a) full-spectrum correlated-$k$ distribution (FSCK) model, b) weighted sum of gray gas model with original parameters (WSGG-Smith), and c) WSGG model with optimized parameters for variable mole ratios and elevated pressure (WSGG-SK). The optically thin approximation (OTA) model is also compared to a simple baseline case. The results show that the temperature and soot volume fraction predicted by the DOM combined with the WSGG-SK model are consistent with the FSCK model, with errors less than 2%. When the pressure increases to 8 bar, errors of P1 and OTA models increase significantly, the maximum temperatures predicted by the P1 and OTA models have errors of 36 K and 63 K, and the relative errors of the peak soot volume fraction are 18% and 24%, respectively.

KEYWORDS:

• Laminar diffusion flame
• elevated pressure
• soot modeling
• non-gray radiation

Acknowledgements

The work was sponsored by the King Abdullah University of Science and Technology (KAUST). Computational resources were provided by the KAUST Supercomputing Laboratory (KSL).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/00102202.2023.2246201

Additional information

Funding

The work was supported by the King Abdullah University of Science and Technology.