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Soot Predictions in Higher Order Hydrocarbon Flames: Assessment of Semi-Empirical Models and Method of Moments

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Modeling and Simulation of Turbulent Combustion

Part of the book series: Energy, Environment, and Sustainability ((ENENSU))

Abstract

Soot predictions in turbulent flames possess different challenge due to the multiscale interaction between turbulence, chemistry, and particle dynamics. In addition, the high intermittency associated with these processes complicates the modeling further. Also, the large number of reactions related to soot precursor (acetylene) and polycyclic aromatic hydrocarbons (PAH) impose additional constraints in the modeling. Moreover, the radiative heat transfer adds to the complexity as there exists a strong coupling (two way) between combustion and soot models. In the present study, soot formation in a highly sooty kerosene/air diffusion flame is numerically investigated using both the semi-empirical and detailed soot models, where the steady laminar flamelet model (SLFM) is invoked as turbulence–chemistry interaction model. A detailed kinetics is implemented, which is represented through POLIMI mechanism (Ranzi et al. Int J Chem Kinet, 46(9):512–542, 2014). Soot formation is modeled using two different approaches, i.e., semi-empirical two-equation models and quadrature methods of moments with first three moments are used and both the approaches consider various subprocesses such as nucleation, coagulation, surface growth, and oxidation. The radiation heat transfer is taken into account considering four fictitious gasses in conjunction with the weighted sum of gray gas (WSSGM) approach for modeling absorption coefficient. The experimental data and earlier published predictions from Young et al. (Proc Combust Inst 25(1):609–617, 1994) and Wen et al. (Combust Flame 135(3):323–340, 2003) respectively are used for assessment of different soot models. The centerline and radial soot volume fraction is reproduced satisfactorily by quadrature method of moments approach, while the strong dependence of combustion products is analyzed through soot–radiation interactions.

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Abbreviations

ρ:

Mixture density

T:

Temperature

\( Z \) :

Mixture fraction

t :

Time

χ:

Scalar dissipation rate

χst :

Scalar dissipation rate at \( Z = Z_{st} \)

\( Z_{st} \) :

Stoichiometric mixture fraction

erfc −1 :

Inverse complementary error function

σ t :

Turbulent Prandtl number

\( \phi \) :

Representative scalar

a λ :

Absorption coefficient

G λ :

Incident radiation

λ:

Wavelength

\( i \) :

Radiation intensity

\( a_{s} \) :

Characteristic strain rate

\( m_{i} \) :

Mass of the particle

\( M \) :

Concentration of “\( n \)“ moment

\( N \) :

Particle density function

μ eff :

Effective dynamic viscosity

\( n \) :

Moment order

PAH:

Poly-cyclic aromatic hydrocarbons

PDF:

Probability density function

DNS:

Direct numerical simulation

LES:

Large eddy simulation

SIMPLE:

Semi-implicit method for pressure-linked equations

RANS:

Reynolds-Averaged Navier–Stokes

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Acknowledgements

Financial support for this research is provided through Aeronautical Research and Development Board (ARDB), India. Also, the authors would like to acknowledge the IITK computer center (https://www.iitk.ac.in/cc) for providing the support to perform the computation work, data analysis, and article preparation.

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Authors and Affiliations

  1. Department of Aerospace Engineering, Indian Institute of Technology Kanpur, Kanpur, 208016, India

    Rohit Saini & Ashoke De

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  1. Rohit Saini
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  2. Ashoke De
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Correspondence to Ashoke De .

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Editors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    Santanu De

  2. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    Avinash Kumar Agarwal

  3. Department of Aerospace Engineering, Indian Institute of Science, Bangalore, Karnataka, India

    Swetaprovo Chaudhuri

  4. Department of Mechanical Engineering, Jadavpur University, Kolkata, West Bengal, India

    Swarnendu Sen

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Saini, R., De, A. (2018). Soot Predictions in Higher Order Hydrocarbon Flames: Assessment of Semi-Empirical Models and Method of Moments. In: De, S., Agarwal, A., Chaudhuri, S., Sen, S. (eds) Modeling and Simulation of Turbulent Combustion. Energy, Environment, and Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-10-7410-3_11

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  • DOI: https://doi.org/10.1007/978-981-10-7410-3_11

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