Combustion Modeling in Heavy Duty Diesel Engines Using Detailed Chemistry and Turbulence-Chemistry Interaction

Paper #:
  • 2015-01-0375

Published:
  • 2015-04-14
DOI:
  • 10.4271/2015-01-0375
Citation:
D'Errico, G., Lucchini, T., Hardy, G., Tap, F. et al., "Combustion Modeling in Heavy Duty Diesel Engines Using Detailed Chemistry and Turbulence-Chemistry Interaction," SAE Technical Paper 2015-01-0375, 2015, https://doi.org/10.4271/2015-01-0375.
Pages:
14
Abstract:
Diesel combustion is a very complex process, involving a reacting, turbulent and multi-phase flow. Furthermore, heavy duty engines operate mainly at medium and high loads, where injection durations are very long and cylinder pressure is high. Within such context, proper CFD tools are necessary to predict mixing controlled combustion, heat transfer and, eventually, flame wall interaction which might result from long injection durations and high injection pressures. In particular, detailed chemistry seems to be necessary to estimate correctly ignition under a wide range of operating conditions and formation of rich combustion products which might lead to soot formation. This work is dedicated to the identification of suitable methodologies to predict combustion in heavy-duty diesel engines using detailed chemistry. To this end, two different approaches were implemented to model flame propagation process into the Lib-ICE code, which both employ detailed chemistry and turbulence chemistry interaction. In the first one, the Diesel spray flame is assumed to be an ensemble of different diffusion flames which are sequentially created during the injection process. Each of them is evolving in the mixture fraction space according to the conditionally averaged value of the scalar dissipation rate. The second one employs tabulated kinetics from perfectly stirred reactor calculations: transport equations are solved for mixture fraction, progress variable and their variances. Their source terms come from spray and the table. From these variables, it is possible to estimate the chemical composition in each computational cell, assuming suitable probability density functions both in mixture fraction and progress variable space for the chemical species. The above described approaches were then validated with two different sets of experimental data. First, constant-volume conditions allowed to make clear distinctions between the models in terms of auto-ignition, flame structure and flame stabilization process. Finally, simulations were carried out for a heavy-duty diesel engine with four different relevant operating loads.Comparisons between computed and experimental data of in-cylinder pressure, heat release rate and wall heat flux allowed to identify the most suitable approaches among the tested ones and to even identify possible future improvements.
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