Modelling paradigms for MILD combustion
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Three-dimensional Direct Numerical Simulation (DNS) data of methane-air MILD combustion is analysed to study the behaviour of MILD reaction zones and to identify a suitable modelling paradigm for MILD combustion. The combustion kinetics in the DNS was modelled using a skeletal mechanism including non-unity Lewis number effects. The reaction zones under MILD conditions are highly convoluted and contorted resulting in their frequent interactions. This leads to combustion occurring over a large portion of the computational volume and giving an appearance of distributed combustion. Three paradigms, standard flamelets, mild flame elements (MIFEs) and PSR, along with a presumed PDF model are explored to estimate the mean and filtered reaction rate in MILD combustion. A beta function is used to estimate the presumed PDF shape. The variations of species mass fractions and reaction rate with temperature computed using these models are compared to the DNS results. The PSR-based model is found to be appropriate, since the conditional averages obtained from the DNS agree well with those obtained using the PSR model. The flamelets model with MIFEs gives only a qualitative agreement because it does not include the effects of reaction zone interactions.
KeywordsMILD combustion Flameless combustion Direct numerical simulation (DNS) Perfectly stirred reactor (PSR) Presumed PDF LES RANS Modelling
YM acknowledges the financial support of Nippon Keidanren and Cambridge Overseas Trust. EPSRC support is acknowledged by NS. This work made use of the facilities of HECToR, the UK’s national high-performance computing service, which is provided by UoE HPCx Ltd at the University of Edinburgh, Cray Inc and NAG Ltd, and funded by the Office of Science and Technology through EPSRCs High End Computing Programme.
- 3.Cant, R.S.: SENGA2 User Guide. In: Technical Report CUED/A-THERMO/TR67. Cambridge University Engineering Department, Cambridge (2012)Google Scholar
- 9.COSILAB: The Combustion Simulation Laboratory Version 2.0.8. Rotexo-Softpredict-Cosilab GmbH & Co. KG, Germany (2007)Google Scholar
- 15.Ertesvag, I.S., Magnussen, B.F.: A numerical study of a bluff-body stabilized diffusion flame. part 1. influence of turbulence modeling and boundary conditions. Combust. Sci. Technol. 119(1–6), 171–190 (1996a)Google Scholar
- 16.Ertesvag, I.S., Magnussen, B.F.: A numerical study of a bluff-body stabilized diffusion flame. Part 2. Influence of combustion modeling and finite-rate chemistry. Combust. Sci. Technol. 119(1–6), 191–217 (1996b)Google Scholar
- 21.Jenkins, K.W., Cant, R.S.: DNS of turbulent flame kernels. In: Knight & Sakell (eds.) Proc. Second AFOSR Conf. on DNS and LES. Rutgers University, Kluwer Academic Publishers, New Brunswick, pp. 192–202. (1999)Google Scholar
- 26.Magnussen, B.F.: On the structure of turbulence and a generalized eddy dissipation concept for chemical reaction in turbulent flow. In: 19th American Institute of Aeronautics and Astronautics Aerospace Science Meeting, pp. 1–6 (1981)Google Scholar
- 28.Minamoto, Y.: Physical aspects and modelling of turbulent MILD combustion. PhD thesis, Department of Engineering, University of Cambridge, Cambridge. (2013)Google Scholar
- 30.Minamoto, Y., Swaminathan, N.: Scalar gradient behaviour in MILD combustion. Combust. Flame 161, 1063–1075 (2014). doi: 10.1016/j.combustflame.2013.10.005
- 31.Minamoto, Y., Swaminathan, N., Cant, R. S., Leung, T.: Morphology of reaction zones in mild and premixed combustion. Combust. Flame (2013b) (submitted)Google Scholar
- 40.Rogallo, R.S.: Numerical experiments in homogeneous turbulence. NASA TM, p. 81315 (1981)Google Scholar