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Modelling of diesel spray flames under engine-like conditions using an accelerated Eulerian Stochastic Field method

Pang, Kar Mun; Jangi, Mehdi LU ; Bai, Xue Song LU ; Schramm, Jesper and Walther, Jens Honore (2018) In Combustion and Flame 193. p.363-383
Abstract

This paper aims to simulate diesel spray flames across a wide range of engine-like conditions using the Eulerian Stochastic Field probability density function (ESF-PDF) model. The ESF model is coupled with the Chemistry Coordinate Mapping approach to expedite the calculation. A convergence study is carried out for a number of stochastic fields at five different conditions, covering both conventional diesel combustion and low-temperature combustion regimes. Ignition delay time, flame lift-off length as well as distributions of temperature and various combustion products are used to evaluate the performance of the model. The peak values of these properties generated using thirty-two stochastic fields are found to converge, with a maximum... (More)

This paper aims to simulate diesel spray flames across a wide range of engine-like conditions using the Eulerian Stochastic Field probability density function (ESF-PDF) model. The ESF model is coupled with the Chemistry Coordinate Mapping approach to expedite the calculation. A convergence study is carried out for a number of stochastic fields at five different conditions, covering both conventional diesel combustion and low-temperature combustion regimes. Ignition delay time, flame lift-off length as well as distributions of temperature and various combustion products are used to evaluate the performance of the model. The peak values of these properties generated using thirty-two stochastic fields are found to converge, with a maximum relative difference of 27% as compared to those from a greater number of stochastic fields. The ESF-PDF model with thirty-two stochastic fields performs reasonably well in reproducing the experimental flame development, ignition delay times and lift-off lengths. The ESF-PDF model also predicts a broader hydroxyl radical distribution which resembles the experimental observation, indicating that the turbulence–chemistry interaction is captured by the ESF-PDF model. The validated model is subsequently used to investigate the flame structures under different conditions. Analyses based on flame index and formaldehyde distribution suggest that a triple flame, which consists of a rich premixed flame, a diffusion flame and a lean premixed flame, is established in the earlier stage of the combustion. As the combustion progresses, the lean premixed flame weakens and diminishes with time. Eventually, only a double-flame structure, made up of the diffusion flame and the rich premixed flame, is observed. The analyses for various ambient temperatures show that the triple-flame structure remains for a longer period of time in cases with lower ambient temperatures. The present study shows that the ESF-PDF method is a valuable alternative to Lagrangian particle PDF methods.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Diesel engine, Eulerian Stochastic Field, Probability density function, Spray flame, Turbulent combustion
in
Combustion and Flame
volume
193
pages
21 pages
publisher
Elsevier
external identifiers
  • scopus:85045547630
ISSN
0010-2180
DOI
10.1016/j.combustflame.2018.03.030
language
English
LU publication?
yes
id
5085f46e-9cfd-4cf5-8fda-12c106b0939f
date added to LUP
2018-04-26 08:30:37
date last changed
2019-10-15 06:36:39
@article{5085f46e-9cfd-4cf5-8fda-12c106b0939f,
  abstract     = {<p>This paper aims to simulate diesel spray flames across a wide range of engine-like conditions using the Eulerian Stochastic Field probability density function (ESF-PDF) model. The ESF model is coupled with the Chemistry Coordinate Mapping approach to expedite the calculation. A convergence study is carried out for a number of stochastic fields at five different conditions, covering both conventional diesel combustion and low-temperature combustion regimes. Ignition delay time, flame lift-off length as well as distributions of temperature and various combustion products are used to evaluate the performance of the model. The peak values of these properties generated using thirty-two stochastic fields are found to converge, with a maximum relative difference of 27% as compared to those from a greater number of stochastic fields. The ESF-PDF model with thirty-two stochastic fields performs reasonably well in reproducing the experimental flame development, ignition delay times and lift-off lengths. The ESF-PDF model also predicts a broader hydroxyl radical distribution which resembles the experimental observation, indicating that the turbulence–chemistry interaction is captured by the ESF-PDF model. The validated model is subsequently used to investigate the flame structures under different conditions. Analyses based on flame index and formaldehyde distribution suggest that a triple flame, which consists of a rich premixed flame, a diffusion flame and a lean premixed flame, is established in the earlier stage of the combustion. As the combustion progresses, the lean premixed flame weakens and diminishes with time. Eventually, only a double-flame structure, made up of the diffusion flame and the rich premixed flame, is observed. The analyses for various ambient temperatures show that the triple-flame structure remains for a longer period of time in cases with lower ambient temperatures. The present study shows that the ESF-PDF method is a valuable alternative to Lagrangian particle PDF methods.</p>},
  author       = {Pang, Kar Mun and Jangi, Mehdi and Bai, Xue Song and Schramm, Jesper and Walther, Jens Honore},
  issn         = {0010-2180},
  keyword      = {Diesel engine,Eulerian Stochastic Field,Probability density function,Spray flame,Turbulent combustion},
  language     = {eng},
  month        = {07},
  pages        = {363--383},
  publisher    = {Elsevier},
  series       = {Combustion and Flame},
  title        = {Modelling of diesel spray flames under engine-like conditions using an accelerated Eulerian Stochastic Field method},
  url          = {http://dx.doi.org/10.1016/j.combustflame.2018.03.030},
  volume       = {193},
  year         = {2018},
}