Numerical investigation of n-dodecane ECN spray and combustion characteristics using the one-way coupled Eulerian-Lagrangian approach

Abstract
This work investigated the spray and combustion characteristics of the Engine Combustion Network (ECN) n-dodecane injections using a one-way coupled Eulerian-Lagrangian approach. The actual X-ray measured injector geometries from the Argonne National Laboratory were adopted for Eulerian simulations. The multi-phase flow was modeled using the Volume-of-Fluid (VoF) method with the high-resolution interface capturing scheme to track the fluid-gas interface. The generated parcel data from the Eulerian simulations were mapped and utilized in the Lagrangian simulations to ensure fidelity. The simulation results agree well with the experimental data in terms of the projected density, mass flow rates, spray penetrations, mixture distributions, and ignition delays. The diverging nozzle channel in the Spray C injector resulted in cavitation and air entrainment, which reduced the mass flow rate. Because of the low oxygen concentration, the low-temperature combustion (LTC) reactions made a significant contribution to the heat release process. In comparison, similar jet-flame structures were observed for the Spray A, C, and D cases, consisting of the upstream LTC region, midstream intermediate-temperature combustion region, downstream fuel-rich high-temperature combustion (HTC) region, and downstream premixed HTC region. The higher ambient temperature led to a more advanced combustion phasing but shorter lift-off length. As a result, the mixing time was reduced to result in a higher concentration of acetylene. In addition, upon increasing the injection pressure, no significant difference was observed in the jet flame structure. On the other hand, the higher injection velocity resulted in a higher flame tip and broader HTC region.

Citation
Al-lehaibi, M., Liu, X., & Im, H. G. (2023). Numerical investigation of n-dodecane ECN spray and combustion characteristics using the one-way coupled Eulerian-Lagrangian approach. Fuel, 331, 125759. https://doi.org/10.1016/j.fuel.2022.125759

Acknowledgements
This work was sponsored by Umm Al Qura and King Abdullah University of Science and Technology. The computational simulations utilized the clusters at KAUST Supercomputing Laboratory. The authors thank Convergent Science Inc. for providing the CONVERGE technical support.

Publisher
Elsevier BV

Journal
Fuel

DOI
10.1016/j.fuel.2022.125759

Additional Links
https://linkinghub.elsevier.com/retrieve/pii/S001623612202587X

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