Browse > Article

http://dx.doi.org/10.15231/jksc.2017.22.4.043
###

Multi-environment PDF Modeling for MILD Combustion Processes |

Ji, Hyunggeun
(Department of Mechanical Engineering, Hanyang University)
Jeon, Sangtae (Department of Mechanical Engineering, Hanyang University) Kim, Yongmo (Department of Mechanical Engineering, Hanyang University) |

Publication Information

Abstract

In this study, the multi-environment probability density function(MEPDF) approach has been applied to numerically investigate Delft-Jet-in-Hot-Coflow(DJHC) turbulent flames under Moderate or Intense Low-oxygen Dilution (MILD) combustion condition. Computations are made for two different jet velocities(Re = 4100 and 8800). In terms of mean axial velocity, temperature, and turbulent kinetic energy, numerical results are in reasonably good agreements with experimental data even if there exist the noticeable deviations in downstream region. Based on numerical results, the detailed discussions are made for the essential features of the non-visible flame structure and MILD combustion processes.

Keywords

Non-visible flame; MILD combustion; Turbulence-chemistry interaction; Multi-environment PDF approach;

Citations & Related Records

Times Cited By KSCI :
1 (Citation Analysis)

- Reference
- Cited By KSCI

1 | E. Oldenhof, M. J. Tummers, E. H. van Veen, and D. J. E. M. Roekaerts, Role of entrainment in the stabilisation of jet-in-hot-coflow flames, Combust. Flame., 158 (2011) 1553-1563. DOI |

2 | J. W. Labahn, D. Dovizio, and C. B. Devaud, Numerical simulation of the Delft-Jet-in-Hot-Coflow (DJHC) flame using Conditional Source-term Estimation, Proc. Combust. Inst., 35 (2015) 3547-3555. DOI |

3 | S. Zahirović, R. Scharler, P. Kilpinen, I. Obernberger, Validation of flow simulation and gas combustion sub-models for the CFD-based prediction of NOx formation in biomass grate furnaces, Combust. Theory Mod., 15 (2010) 61-87. DOI |

4 | S. R. Shabanian, P. R. Medwell, M. Rahimi, A. Frassoldati, A. Cuoci, Kinetic and fluid dynamic modeling of ethylene jet flames in diluted and heated oxidant stream combustion conditions, Appl. Therm. Eng., 52(2) (2013) 538-554. DOI |

5 | S. B. Pope, PDF methods for turbulent reactive flows, Prog. Energy Combust. Sci., 11 (1985) 119-192. DOI |

6 | H. Wang, and S. B. Pope, Large eddy simulation/probability density function modeling of a turbulent jet flame, Proc. Combust. Inst., 33 (2011) 1319-1330. DOI |

7 | R. O. Fox, Computational models for turbulent reacting flows, Cambridge University Press, Cambridge, 2003. |

8 | Q. Tang, W. Zhao, M. Bockelie, and R.O. Fox, Multi-environment probability density function method for modelling turbulent combustion using realistic chemical kinetics, Combust. Theory. Mod., 11 (2007) 889-907. DOI |

9 | L. Valino, A field Monte Carlo formulation for calculating the probability density function of a single scalar in a turbulent flow, Flow Turbul. Combust., 60 (1998) 157-172. DOI |

10 | W. P. Jones, and V. N. Prasad, Large Eddy simulation of the sandia flame series (D, E and F) using the Eulerian stochastic field method, Combust. Flame., 157 (2010) 1621-1636. DOI |

11 | S. T. Jeon, and Y. M. Kim, Numerical Investigations of turbulent flames under MILD condition, The 51th KOSCO Symposium, Dec. 10th-11th 2015, 267-268. |

12 | J. W. Lee, and Y. M. Kim, DQMOM based PDF transport modeling for turbulent lifted nitrogen-diluted hydrogen jet flame with autoignition, Int. J. Hydrogen Energy, 37 (2012) 18498-18508. DOI |

13 | A. De, and A. Dongre, Assessment of turbulence-chemistry interaction models in MILD combustion regime. Flow Turbulence Combust., 94(2) (2015) 439-478. DOI |

14 | C. T. Bowman, R. K. Hanson, D. F. Davidson, W. C. Gardiner, Jr., V. Lissianski, G. P. Smith, D. M. Golden, M. Frenklach, and M. Goldenberg, http://combustion.berkeley.edu/gri-mech/new21/version21/text21.html |

15 | Akroyd J., Smith A. J., McGlashan L. R., and Kraft M. (2010) "Numerical investigation of DQ MoM-IEM as a turbulent reaction closure," Chem. Eng. Sci., vol. 65, pp.1915-1924. DOI |

16 | H. S. Koo, P. Donde, and V. Raman, A Quadrature-based LES/Transported Probability Density Function Approach for Modeling Supersonic Combustion, Proc. Combust. Ins. 33 (2011) 2203-2210. DOI |

17 | A. Mardani, S. Tabejamaat, and M. Ghamari, Numerical study of influence of molecular diffusion in the mild combustion regime. Combust. Theory Mod., 14 (2010) 747-774. DOI |

18 | B. J. Isaac, A. Parente, C. Galletti, J. N. Thornock, P. J. Smith, and L. Tognotti, A novel methodology for chemical time scale evaluation with detailed chemical reaction kinetics. Energy Fuels, 27 (2013) 2255-2265. DOI |

19 | M. Mörtberg, W. Blasiak, and A. K. Gupta, Experimental investigation of flow phenomena of a single fuel jet in cross-flow during highly preheated air combustion conditions. J. Eng. Gas Turbines Power, 129(2) (2007) 556-564. DOI |

20 | H. Tsuji, A. K. Gupta, T. Hasewaga, M. Katsuki, K. Kishimoto, and M. Morita, High temperature air combustion: from energy conservation to pollution reduction; CRC Press, 2002. |

21 | P. Sabia, M. Joannon, S. Fierro, A. Tregrossi, and A. Cavaliere, Hydrogen-enriched methane mild combustion in a well stirred reactor. Exp. Therm. Fluid Sci., 31 (2007) 469-475. DOI |

22 | P. H. Lee and S. S. Hwang, Experimental Study for Oxygen Methane MILD Combustion in a Laboratory Scale Furnace, J. Korean Soc. Combust., 21(4) (2016) 6-15. DOI |

23 | A. De, E. Oldenhof and P. Sathiah, Numerical Simulation of Delft-Jet-in-Hot-Coflow (DJHC) Flames Using the Eddy Dissipation Concept Model for Turbulence-Chemistry Interction, Flow Turbulence Combust., 87(4) (2011) 537-567. DOI |

24 | A. Dongre, A. De, and R. Yadav, Numerical investigation of MILD combustion using multi-environment Eulerian probability density function modeling, Int. J. of spray and combust. dynamics, 6(4) (2014) 357-386. DOI |

25 | E. Oldenhof, M. J. Tummers, E. H. van Veen, and D. J. E. M. Roekaerts, Ignition kernel formation and lift-off behaviour jet-in-hot-coflow flames, Combust. Flame., 157 (2010) 1167-1178. DOI |