Abstract
This paper presents a comparison between the numerically determined soot volume fraction (SVF) in a momentum-dominated turbulent diffusion strained jet flames burning ethylene/hydrogen/nitrogen mixture in air with experimental results. The soot inception model used is based on the formation rate of two or three ring poly aromatic hydrocarbon with C6H6 as the soot precursor. Second-moment closure Reynolds stress method turbulent model is used in conjunction with the governing equation of mass, momentum and energy. The turbulent combustion kinetic chemistry interaction is modeled by choosing a chemical equilibrium non-premixed combustion model along with the species inlet diffusion probability density function (PDF). Soot radiation source term like P-1 radiation model is also included along with the turbulent combustion model. The soot turbulence interaction invoked uses single-variable PDF based on the temperature and mixture fraction (Z) for measurement of flame lift-off height, flame length and radiative heat loss. Equilibrium-based Lee soot oxidation model is chosen to estimate the hydroxyl (OH) and O2 species for the oxidation of soot particles. The numerical solutions for each of the experimental configurations are proposed by Mahmoud and co-workers for three different strained flames (4000 s−1, 7300 s−1, and 12,900 s−1). In each discretized finite volume cell, using a quadratic upstream interpolation for convective kinematics algorithm in spatial coordinate and time-bounded second-order accurate in temporal coordinate solution is obtained. All the above turbulence combustion interaction models are iterated with unit Courant–Friedrichs–Lewy condition. It is noted that the mixture fraction (Z) PDF used is very sensitive to the chosen turbulence combustion soot interaction models. Also, it is observed that the simulated outputs are in good agreement with the measured experimental data in terms of SVF, temperature both axially and radially. SVF increases with a decrease in the flame strain rate and shows the reverse trend in radially integrated soot volume reaction. In agreement with experiments, soot productivity shows a linear relationship in momentum-dominated flame with an increase in the strain rates for soot productivity, maximum mean SVF, exit Froude number, exit C2H4 flow rate.
Similar content being viewed by others
References
Karatas AE, Gülder ÖL. Soot formation in high-pressure Laminar diffusion flames. Prog Energy Combust Sci. 2012;38(2):818–45.
Jung H, Guo B, Anastasio C, Kennedy IM. Quantitative measurements of the generation of hydroxyl radicals by soot particles in surrogate lung fluid. Atmos Environ. 2006;40(6):1043–52.
Kärcher B, Möhler O, DeMott PJ, Pechtl S, Yu F. Insights into the role of soot aerosols in cirrus clouds formation. Atmos Chem Phys. 2007;7:4203–27.
Guillaume L, Ignacio H, Damien P, Eleonore R, Bénédicte C. Soot prediction by large-eddy simulation of complex geometry combustion chambers, CERFACS, CFD Team, 42 Avenue G. Coriolis, 31057 Toulouse Cedex 01, France.
Frenklach M, Clary DW, Gardiner WC, et al. Detailed kinetic modeling of soot formation in shock-tube pyrolysis of acetylene. Symp Combust. 1985;20:887–901.
Harris SJ, Weiner AM, Blint RJ. Formation of small aromatic molecules in a sooting ethylene flame. Combust Flame. 1988;72:91–109.
Brookes S, Moss J. Predictions of soot and thermal radiation properties in confined turbulent jet diffusion flames. Combust Flame. 1999;116:486–503.
Kronenburg A, Bilger R, Kent J. Modeling soot formation in turbulent methane–air-jet diffusion flames. Combust Flame. 2000;121:24–40.
Kennedy IM, Yam C, Rapp DC, Santoro RJ. Modeling and measurements of soot and species in a laminar diffusion flame. Combust Flame. 1996;107:368–82.
Kent JH, Wagner GH. Who do diffusion flames emit smoke. Combust Sci Technol. 1984;41:245–69.
Lee W, Na YD. Soot study in laminar diffusion flames at elevated pressure using two-color pyrometry and Abel inversion. JSME Int J B. 2000;43:550–5.
Glassman I, Yaccarino P. The temperature effect in sooting diffusion flames. Proc Combust Inst. 1981;18:1175–83.
Ma G, Wen JZ, Lightstone MF, et al. Optimization of soot modeling in turbulent nonpremixed ethylene/air jet flames. Combust Sci Technol. 2005;177:1567–602.
Mahmoud SM, Nathan GJ, Alwahabi ZT, Sun ZW, Medwell PR, Dally BB. The effect of exit strain rate on soot volume fraction in turbulent non-premixed jet flames. Proc Combust Inst. 2017;36(1):889–97.
Hall RJ, Smooke MD, Colket MB. Predictions of soot dynamics in opposed jet diffusion flames. Phys Chem Asp of Combust. 1997;4:189–229.
Launder BE, Spalding DB. The numerical computation of turbulent flows. Comput Methods Appl Mech Eng. 1974;3:269–89.
Jones WP, Prasetyo Y. Probability density function modeling of premixed turbulent opposed jet flames. In: Symposium (international) on combustion, vol 26. 1996.
O’Brien EE. The probability density function (PDF) approach to reacting turbulent flows. Turbulent reacting flows. Berlin: Springer; 1980. p. 185–218.
Pope SB. PDF methods for turbulent reactive flows. Prog Energy Combust Sci. 1985;11(2):119–92.
Siegel R, Howel JR. Thermal radiation heat transfer. 4th ed. New York: CRC Press; 2002.
Smith TF, Shen ZF, Friedman JN. Evaluation of coefficients for the weighted sum of the gray gases model. J Heat Transf. 1982;104:602–8.
Lee KB, Thring MW, Beer JM. On the rate of combustion of soot in a laminar soot flame. Combust Flame. 1962;6:137–45.
Baulch DL, Bowman CT, Cobos CJ, Cox RA, Just Th, Kerr JA, Pilling MJ, Stocker D, Troe J, Tsang W, Walker RW, Warnatz J. Evaluated kinetic data for combustion modeling. J Phys Chem Ref Data. 1992;21(3):411–734.
Flynn PF, Durrett RP, Hunter GL, Zur Loye AO, Akinyemi OC, Dec JE, Westbrook CK. Diesel combustion: an integrated view combining laser diagnostics, chemical kinetics, and empirical validation. SAE Trans. 1999;108:587–600.
Westenberg AA. Kinetics of NO and CO in lean, premixed hydrocarbon-air flames. Combust Sci Technol. 1971;4(1):59–64.
Oberkampf WL, Trucano TG, Hirsch C. Verification, validation, and predictive capability in computational engineering and physics. Appl Mech Rev. 2004;57(5):345–84.
Kwaśniewski L. On practical problems with verification and validation of computational models. Arch Civ Eng. 2009;55(3):323–46.
Eça L. A verification exercise for two 2-D steady incompressible turbulent flows. In: Proceedings of ECCOMAS 2004, Jyvaskyla. 2004.
Delichatsios MA. The transition from momentum to buoyancy-controlled turbulent jet diffusion flames and flame height relationships. Combust Flame. 1993;92(4):349–64.
Becker HA, Liang D. Visible length of vertical free turbulent diffusion flames. Combust Flame. 1978;32:115–37.
Turns SR, Myhr FH. Oxides of nitrogen emissions from turbulent jet flames: part I—fuel effects and flame radiation. Combust Flame. 1991;87(3–4):319–35.
Acknowledgements
The authors would like to acknowledge the support given by NITT Octagon computer center for providing the resources to perform the computation work, data analysis and article preparation. The authors thank Professor Bassam Dally of School of Mechanical Engineering, University of Adelaide, South Australia, for kindly granting access to the experimental data of C2H4/H2/N2/air diffusion turbulent flames for numerical soot study.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mohamed Ibrahim, N.H., Udayakumar, M. Coupling RSM with soot model for the study of soot formation in a momentum-dominated strained jet flames. J Therm Anal Calorim 141, 2369–2389 (2020). https://doi.org/10.1007/s10973-020-09649-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10973-020-09649-0