Startseite Numerical simulation of the effects of NH3 and H2 on the combustion characteristics of laminar premixed ethylene/air flames
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Numerical simulation of the effects of NH3 and H2 on the combustion characteristics of laminar premixed ethylene/air flames

  • Jinfang Yao , Wenlong Dong , Yuhang Yang , Dongyang Wang und Huaqiang Chu ORCID logo EMAIL logo
Veröffentlicht/Copyright: 12. Februar 2025
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Abstract

Hydrogen (H2) and ammonia (NH3) are highly promising carbon-free fuels and can mitigate the greenhouse effect threat. The laminar combustion characteristics of ethylene (C2H4) doped with H2 and NH3 were numerically calculated at large doping proportion (0–50 %), initial temperatures (Tu = 300–400 K), and initial pressures (Pu = 0.1–1.0 MPa) by using the Chemkin/Premix Code. The equivalence ratio (Φ) ranged from 0.75 to 1.5. Laminar burning velocities (LBVs), adiabatic flame temperatures (AFTs), net heat release rates (NHRRs), temperature sensitivity analysis (TSA), mole fractions of radicals of H, O, OH and intermediates of C2H2, NO, NO2, the rate of production (ROP) and the reaction pathways were studied in this research. The results showed that H2 promoted the increase of C2H4/air LBVs, AFTs and NHRRs, while NH3 had the contrary effects. R1 (H + O2 <=> H + OH) had the largest positive sensitivity coefficient more than 0.3. Through the analysis of TSA and ROP, R146 (C2H3 + H <=> C2H2 + H2) was the main reaction to product C2H2, and C2H2 could be effectively inhibited after doping NH3. Additionally, the mole fraction of NO decreased as H2 increased but increased with the increase of NH3. The peak NO2 located much closer to the nozzle inlet after doping H2 and NH3, and R392 (NO + HO2 <=> NO2 + OH) was the main reaction linked NO and NO2. The reaction pathway showed the effect of NH3 on reducing CO2 was stronger than that of H2.


Corresponding author: Huaqiang Chu, School of Energy and Environment, Anhui University of Technology, Ma’anshan 243002, Anhui, P.R. China, E-mail:

Award Identifier / Grant number: 52176095

Acknowledgments

The authors would like to acknowledge the editors and referees who made important comments that helped us to improve this paper.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Jinfang Yao: Writing - original draft, validation; Wenlong Dong: writing - original draft; Yuhang Yang: data curation; Dongyang Wang: data curation, writing - review & editing; Huaqiang Chu: conceptualization, project administration, supervision.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: All authors state no conflict of interest.

  6. Research funding: This work was supported by National Natural Science Foundation of China (No. 52176095), Anhui Provincial Natural Science Foundation (No. 2008085J25), Natural Science Research Project of Colleges and Universities in Anhui Province (No. KJ2020ZD29).

  7. Data availability: Not applicable.

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Received: 2024-09-03
Accepted: 2025-01-24
Published Online: 2025-02-12

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