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Numerical investigation of soot formation and oxidation processes under large two-stroke marine diesel engine-like conditions using integrated CFD-chemical kinetics

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  • Pang, Kar Mun
  • Karvounis, Nikolas
  • Walther, Jens Honore
  • Schramm, Jesper

Abstract

In this reported work, multi-dimensional computational fluid dynamics studies of diesel combustion and soot formation processes in a constant volume combustion chamber and a marine diesel engine are carried out. The key interest here is firstly to validate the coupling of a newly developed skeletal n-heptane mechanism and a revised multi-step soot model using laser extinction measurements of diesel soot obtained at different ambient pressure levels in an optical accessible, constant volume chamber experiment. It is revealed that ignition delay times and liftoff lengths generated using the new skeletal model are close to those produced by the larger and more comprehensive chemical mechanisms, apart from those at the low pressure condition. The current study also demonstrates that the variation of averaged soot volume fraction with respect to the change of combustion chamber pressure captured using the revised soot model agrees reasonably well with the measurements in terms of peak values. The numerical model is subsequently applied to investigate the flame development, soot/nitrogen monoxide formation and heat transfer in a two-stroke, low-speed uniflow-scavenged marine diesel engine operating at full load condition, where optical measurements are not available. Comparisons to the experimental data show that the simulated pressure rise starts 1.0 crank angle degree in advance and the calculated peak pressure is 1.7% lower. The associated flame liftoff length is negligible, yielding higher local equivalence ratio and soot volume fraction values as compared to those under similar test condition in the constant volume chamber. With the use of the revised model, the total heat transfer to the walls calculated when soot radiative heat loss is taken into account is approximately 30% higher compared to that when only convective heat loss is considered. The averaged nitrogen monoxide concentration is 7.7% lower when both convective and soot radiative heat losses are accounted for but the net soot mass production is less sensitive to soot radiation. A sensitivity study reveals that neither increasing nor decreasing the soot absorption coefficient by 30% from the baseline setup is influential to nitrogen monoxide formation, soot mass production and heat transfer. The findings here aid to gain insights and provide a better understanding of the combustion and soot processes in large, uniflow-scavenged marine engines. The numerical model developed in this work can also be applied to explore different phenomena in this combustion system.

Suggested Citation

  • Pang, Kar Mun & Karvounis, Nikolas & Walther, Jens Honore & Schramm, Jesper, 2016. "Numerical investigation of soot formation and oxidation processes under large two-stroke marine diesel engine-like conditions using integrated CFD-chemical kinetics," Applied Energy, Elsevier, vol. 169(C), pages 874-887.
  • Handle: RePEc:eee:appene:v:169:y:2016:i:c:p:874-887
    DOI: 10.1016/j.apenergy.2016.02.081
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    6. Wang, Dawei & Shi, Lei & Zhu, Sipeng & Liu, Bo & Qian, Yuehua & Deng, Kangyao, 2020. "Numerical and thermodynamic study on effects of high and low pressure exhaust gas recirculation on turbocharged marine low-speed engine," Applied Energy, Elsevier, vol. 261(C).
    7. Geertsma, R.D. & Negenborn, R.R. & Visser, K. & Loonstijn, M.A. & Hopman, J.J., 2017. "Pitch control for ships with diesel mechanical and hybrid propulsion: Modelling, validation and performance quantification," Applied Energy, Elsevier, vol. 206(C), pages 1609-1631.
    8. Wu, Shaohua & Yang, Wenming & Xu, Hongpeng & Jiang, Yu, 2019. "Investigation of soot aggregate formation and oxidation in compression ignition engines with a pseudo bi-variate soot model," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. Wu, Shaohua & Akroyd, Jethro & Mosbach, Sebastian & Brownbridge, George & Parry, Owen & Page, Vivian & Yang, Wenming & Kraft, Markus, 2020. "Efficient simulation and auto-calibration of soot particle processes in Diesel engines," Applied Energy, Elsevier, vol. 262(C).
    10. Wu, Shaohua & Zhou, Dezhi & Yang, Wenming, 2019. "Implementation of an efficient method of moments for treatment of soot formation and oxidation processes in three-dimensional engine simulations," Applied Energy, Elsevier, vol. 254(C).
    11. Ling-Chin, Janie & Roskilly, Anthony P., 2016. "Investigating the implications of a new-build hybrid power system for Roll-on/Roll-off cargo ships from a sustainability perspective – A life cycle assessment case study," Applied Energy, Elsevier, vol. 181(C), pages 416-434.
    12. Thomas Lauer & Jens Frühhaber, 2020. "Towards a Predictive Simulation of Turbulent Combustion?—An Assessment for Large Internal Combustion Engines," Energies, MDPI, vol. 14(1), pages 1-26, December.
    13. Yin, Chungen, 2017. "Prediction of air-fuel and oxy-fuel combustion through a generic gas radiation property model," Applied Energy, Elsevier, vol. 189(C), pages 449-459.
    14. Sun, Xiuxiu & Liang, Xingyu & Shu, Gequn & lin, Jiansheng & Wei, Haiqiao & Zhou, Peilin, 2018. "Development of a surrogate fuel mechanism for application in two-stroke marine diesel engine," Energy, Elsevier, vol. 153(C), pages 56-64.
    15. Pang, Kar Mun & Karvounis, Nikolas & Walther, Jens Honore & Schramm, Jesper & Glarborg, Peter & Mayer, Stefan, 2017. "Modelling of temporal and spatial evolution of sulphur oxides and sulphuric acid under large, two-stroke marine engine-like conditions using integrated CFD-chemical kinetics," Applied Energy, Elsevier, vol. 193(C), pages 60-73.
    16. Li, Dun & Gao, Jianmin & Zhao, Ziqi & Du, Qian & Dong, Heming & Cui, Zhaoyang, 2022. "Effects of iron on coal pyrolysis-derived soot formation," Energy, Elsevier, vol. 249(C).
    17. Tang, Yuanyuan & Zhang, Jundong & Gan, Huibing & Jia, Baozhu & Xia, Yu, 2017. "Development of a real-time two-stroke marine diesel engine model with in-cylinder pressure prediction capability," Applied Energy, Elsevier, vol. 194(C), pages 55-70.

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