Tabulated Chemistry Approach for the Simulation of MILD Combustion: Effects of Scalar Mixing and Chemistry Tabulation

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Abstract

MILD (moderate and intense low-oxygen dilution) combustion is a highly promising technology to deliver clean and efficient thermal energy. However, because of its unconventional reaction nature, the optimization of the MILD combustion in various industrial burners is still challenging, for which the design tool based on accurate and cost-effective numerical simulation is most desirable. To this end, the tabulated chemistry approach (TCA) is thoroughly assessed for the modeling of MILD combustion by simulations of the Adelaide Jet in Hot Coflow (JHC) burner. The sensitivities to the submodel accounting for the scalar micromixing and the canonical flame configurations (i.e., flamelet and PSR-based reactors), being relevant for MILD regime characterization in TCA, are studied. It is found that the scalar mixing enhanced through the dynamic adjustment of model parameter Cs leads to an improved prediction, and the optimal value of Cs = 8 is identified for the current flames. The proper parametrization of the detailed chemical structures in TCA is found to affect the accurate prediction of the MILD flame profiles, especially the mass fraction of minor species (e.g., OH, CO). Furthermore, the endothermic reaction path of O + C2H2 ⇒ CO + CH2 is indicated as the main contributing step to the disparities in the CO predictions. This implies that the multiple reaction regimes in complex MILD burning should be accounted for by the use of either flamelet or PSR structures, depending on the local microscale diffusion/chemistry competitions. Overall, the results highlight the influential role of multiscale mixing and its intercoupling with the finite-rate chemistry, the accurate determination of which is important for MILD combustion modeling.

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Hu, Y., Jiang, Y., & Cheong, K. P. (2023). Tabulated Chemistry Approach for the Simulation of MILD Combustion: Effects of Scalar Mixing and Chemistry Tabulation. ACS Omega, 8(11), 10288–10302. https://doi.org/10.1021/acsomega.2c07850

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