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Numerical study on fuel-NO formation characteristics of ammonia-added methane fuel in laminar non-premixed flames with oxygen/carbon dioxide oxidizer

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  • Woo, Mino
  • Choi, Byung Chul

Abstract

Ammonia (NH3) is considered as an attractive carbon-free fuel although a technical obstacle involves the formation of large amounts of nitrogen oxides (NOx) due to its N-atom. The study focuses on the fuel-NO formation characteristics in ammonia-added methane flame with an oxygen/carbon dioxide (O2/CO2) oxidizer to elucidate the key elementary reaction steps. Two well-known reaction mechanisms were employed in two-dimensional axisymmetric computational fluid dynamics (CFD) and one-dimensional opposite-diffusion (OPPDIF) flame simulations, and the results were compared with those of experimentally measured NOx emission trends. Hence, a region with a significant difference in nitrogen monoxide (NO) formation characteristics calculated using the two reaction mechanisms was determined via local distributions and statistical analysis of the 2D CFD results. Additionally, the multidimensional effect was observed while comparing the axial profiles of 1D OPPDIF and radial distributions of 2D CFD at various axial positions from the fuel nozzle. Reaction pathways were extracted at the representative positions, and the major NO production and destruction steps were analyzed via the dimensionless conversion rate of NH3 to NO species. The results demonstrated that the fast N-related reactions in the NH – N – NO pathway, N + OH → NO + H in particular, highly influenced the predicted fuel-NO formation trends with increases in the oxygen concentration in the oxidizer.

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  • Woo, Mino & Choi, Byung Chul, 2021. "Numerical study on fuel-NO formation characteristics of ammonia-added methane fuel in laminar non-premixed flames with oxygen/carbon dioxide oxidizer," Energy, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:energy:v:226:y:2021:i:c:s0360544221006149
    DOI: 10.1016/j.energy.2021.120365
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    References listed on IDEAS

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    Cited by:

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    4. Liu, Xing & Wang, Ying & Bai, Yuanqi & Yang, Wenxu, 2023. "Development of reduced and optimized mechanism for ammonia/ hydrogen mixture based on genetic algorithm," Energy, Elsevier, vol. 270(C).

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