Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-21T00:44:08.306Z Has data issue: false hasContentIssue false

A PDF method for HCCI combustion modeling : CPU timeoptimization through a restricted initial distribution

Published online by Cambridge University Press:  16 November 2012

Pierre-Lin Pommier
Affiliation:
Universitéde Versailles-Saint-Quentin-en-Yvelines, Laboratoire LISV, 10-12 avenue de l’Europe, 78140 Vélizy, France
Fadila Maroteaux*
Affiliation:
Universitéde Versailles-Saint-Quentin-en-Yvelines, Laboratoire LISV, 10-12 avenue de l’Europe, 78140 Vélizy, France
Michel Sorine
Affiliation:
INRIA Rocquencourt, Domaine de Voluceau, 78153 Le Chesnay Cedex, France
*
a Corresponding author:[email protected]
Get access

Abstract

Probability Density Function (PDF) is often selected to couple chemistry with turbulencefor complex reactive flows since complex reactions can be treated without modelingassumptions. This paper describes an investigation into the use of the particlesapproximation of this transport equation approach applied to Homogeneous ChargeCompression Ignition (HCCI) combustion. The model used here is an IEM (Interaction byExchange with the Mean) model to describe the micromixing. Therefore, the fluid within thecombustion chamber is represented by a number of computational particles. Each particleevolves function of the rate of change due to the chemical reaction term and the mixingterm. The chemical reaction term is calculated using a reduced mechanism of n-heptaneoxidation with 25 species and 25 reactions developed previously. The parametric study witha variation of the number of particles from 50 up to 104 has been investigatedfor three initial distributions. The numerical experiments have shown that the hatdistribution is not appropriate and the normal and lognormal distributions give the sametrends. As expected when the number of particles increases for homogenous mixture (i.e.high turbulence intensity), the in-cylinder pressure evolution tends towards thehomogeneous curve. For both homogeneous and inhomogeneous (i.e. low turbulence intensity)cases, we have found that 200 particles are sufficient to model correctly the system, witha CPU time of a few minutes when a restriction of initial distribution is adopted.

Type
Research Article
Copyright
© AFM, EDP Sciences 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Références

S.M. Aceves, D.L. Flowers, C.K. Westbrook, J.R. Smith, W. Pitz, R. Dibble, M. Christensen, B. Johansson, A multi-zone model for prediction of HCCI combustion and emissions, SAE paper 2000-01-0327, 2000
R. Dibble, M. Au, J. Girard, S.M. Aceves, D.L. Flowers, J. Martinez-Frias, J.R. Smith, Current research in HCCI at UC Berkeley and LLNL, SAE paper 2001-01-2511, 2001
S.M. Aceves, J. Martinez-Friaz, D.L. Flowers, J.R. Smith, R.W. Dibble, J.F. Wright, R.P. Hessel, A decoupled model of detailed fluid mechanics followed by detailed chemical kinetics for prediction of iso-octane HCCI combustion, SAE paper 2001-01-3612, 2001
S.C. Kong, N.A. Ayoub, R.D. Reitz, Modeling combustion in compression ignition homogeneous charge, SAE paper 920512, 1992
S.C. Kong, C.D. Marriott, R.D. Reitz, M. Christensen, Modeling and experiments of HCCI engine combustion using detailed chemical kinetics with multidimensional CFD, SAE paper 2001-01-1026, 2001
M. Sjoberg, J.E. Dec, N.P. Cernansky, Potential of thermal stratification and combustion retard for reducing pressure rise rates in HCCI engines, based on multi-zone modeling and experiments, SAE paper 2005-01-0113, 2005
R. Ogink, V. Golovitchev, Gasoline HCCI modeling : an engine cycle simulation code with a multi-zone combustion model, SAE paper 2002-01-1745, 2002
M. Christensen, B. Johansson, Influence of mixture quality on homogeneous charge compression ignition, SAE paper 982454, 1998
S.B. Fiveland, D.N. Assanis, Development of a two-zone combustion model accounting for boundary layer effects, SAE paper 2001-01-1028, 2001
S.M. Aceves, D.L. Flowers, J. Martinez-Frias, J.R. Smith, R. Dibble, M. Au, J. Girard, HCCI combustion : analysis and experiments, SAE paper 2001-01-2077, 2001
J.E. Dec, A computational study of the effects of low fuel loading and EGR on heat release rates and combustion limits in HCCI engines, SAE paper 2002-01-1309, 2002
A. Hultqvist, M. Christensen, B. Johansson, M. Richter, J. Nygren, J. Hult, M. Aldén, The HCCI combustion process in a single cycle-high-speed fuel tracer LIF and chemiluminescence imaging, SAE paper 2002-01-0424, 2002
M. Richter, J. Engstrom, A. Franke, M. Aldén, A. Hultqvist, B. Johansson, The influence of charge inhomogeneity on the HCCI combustion process, SAE paper 2000-01-2868, 2000
J. Villermaux, J.C. Devillon, Représentation de la coalescence et de la redispersion des domaines de ségrégation dans un fluide par un modèle d’interaction phénoménologique, Proceedings of the 2nd International Symposium on Chemical Reaction Engineering, Elsevier, New York, 1972
Pope, S.B., PDF Methods for turbulent reactive flows, Progr. Energ. Combust. Sci. 11 (1985) 119 CrossRefGoogle Scholar
Dopazo, C., E.E. O’Brien, An approach to the autoignition of a turbulent mixture, Acta Astronaut. 1 (1974) 12391266 CrossRefGoogle Scholar
Curl, R.L., Dispersed phase mixing : I. Theory and effects in simple reactors, A.I.Ch.E. J. 9 (1963) 175181 CrossRefGoogle Scholar
Hsu, A.T., Tsai, Y.L.P., Raju, M.S., Probability density function approach for compressible turbulent reacting flows, AIAA 32 (1994) 7 CrossRefGoogle Scholar
Subramaniam, S., Pope, S.B., A mixing model for turbulent reactive flows based on euclidean minimum spanning trees, Comb. Flame 115 (1998) 487514 CrossRefGoogle Scholar
Yang, B., Pope, S.B., An investigation of the accuracy of manifold methods and splitting schemes in the computational implementation of combustion chemistry, Comb. Flame 112 (1998) 1632 CrossRefGoogle Scholar
Maroteaux, F., Noel, L., Development of a reduced n-heptane oxidation mechanism for HCCI combustion modeling, Comb. Flame 146 (2006) 256267 CrossRefGoogle Scholar
M. Kraft, W. Wagner, An efficient stochastic chemistry approximation for the PDF transport equation, ISSN 0946-8633, 2001
Kraft, M., Maigaard, P., Mauss, F., Christensen, M., Johansson, B., Investigation of combustion emissions in a homogeneous charge compression injection engine : measurements and a new computational model, Proceedings of the Combustion Institute 28 (2000) 11951201 CrossRefGoogle Scholar
Mitarai, S., Riley, J.J., Kosàly, G., Testing of mixing models for Monte Carlo probability density function simulations, Phys. Fluids 17 (2005) 047101 CrossRefGoogle Scholar
Warhaft, Z., Lumley, J., An experimental study of the decay of temperature fluctuations in grid-generated turbulence, J. Fluid Mech. 88 (1978) 659684 CrossRefGoogle Scholar
J. Chang, O. Güralp, Z. Filipi, D. Assanis, T.-W. Kuo, P. Najt, R. Rask, New heat transfert correlation for an hcci engine derived from measurements of instantaneous surface heat flux, SAE 2004-01-2996, 2004
J.B. Heywood, Internal combustion engine fundamentals, McGraw-Hill, New York, 1988
A.C. Hindmarsh, R. Serban CVode v 2.3.0. Center of applied scientific computing lawrence livermore national laboratory, April 2005 http://www.llnl.gov/CASC/sundials/description/description.html.
A. Bhave, M. Balthasar, M. Kraft, F. Mauss, Numerical analysis of natural gas fuelled HCCI engine with exhaust gas recirculation, using a stochastic reactor model, University of Cambridge ISSN 1734-4273, 2003
Maroteaux, F., Noel, L., Ahmed, A., Numerical investigations on methods to control the rate of heat release of HCCI combustion using reduced mechanism of n-heptane with multidimensional CFD code, Combust. Theory Model. 11 (2007) 501525 CrossRefGoogle Scholar