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

Kar Mun Pang*, Mehdi Jangi, Xue-Song Bai, Jesper Schramm, Jens Honore Walther

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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 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.
Original languageEnglish
JournalCombustion and Flame
Volume193
Pages (from-to)363-383
ISSN0010-2180
DOIs
Publication statusPublished - 2018

Keywords

  • Diesel engine
  • Eulerian Stochastic Field
  • Probability density function
  • Spray flame
  • Turbulent combustion

Cite this

@article{905b8e004d2a4347a302b690b42bb1f5,
title = "Modelling of diesel spray flames under engine-like conditions using an accelerated Eulerian Stochastic Field method",
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 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.",
keywords = "Diesel engine, Eulerian Stochastic Field, Probability density function, Spray flame, Turbulent combustion",
author = "Pang, {Kar Mun} and Mehdi Jangi and Xue-Song Bai and Jesper Schramm and Walther, {Jens Honore}",
year = "2018",
doi = "10.1016/j.combustflame.2018.03.030",
language = "English",
volume = "193",
pages = "363--383",
journal = "Combustion and Flame",
issn = "0010-2180",
publisher = "Elsevier",

}

Modelling of diesel spray flames under engine-like conditions using an accelerated Eulerian Stochastic Field method. / Pang, Kar Mun; Jangi, Mehdi ; Bai, Xue-Song ; Schramm, Jesper; Walther, Jens Honore.

In: Combustion and Flame, Vol. 193, 2018, p. 363-383.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Modelling of diesel spray flames under engine-like conditions using an accelerated Eulerian Stochastic Field method

AU - Pang, Kar Mun

AU - Jangi, Mehdi

AU - Bai, Xue-Song

AU - Schramm, Jesper

AU - Walther, Jens Honore

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Diesel engine

KW - Eulerian Stochastic Field

KW - Probability density function

KW - Spray flame

KW - Turbulent combustion

U2 - 10.1016/j.combustflame.2018.03.030

DO - 10.1016/j.combustflame.2018.03.030

M3 - Journal article

VL - 193

SP - 363

EP - 383

JO - Combustion and Flame

JF - Combustion and Flame

SN - 0010-2180

ER -