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Certain Aspects of Conditional Moment Closure for Spray Flame Modelling

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Abstract

Large-eddy simulations (LES) have been coupled with a conditional moment closure (CMC) method for the improved modelling of small scale turbulence-chemistry interactions in turbulent spray flames. Partial pre-evaporation of the liquid fuel prior to exiting the injection nozzle requires a modified treatment for the boundary conditions in mixture fraction space and mixture fraction subgrid distribution and conditionally averaged subgrid dissipation need to be known. Different modelling approaches for the subgrid distribution of mixture fraction have been assessed, but the modelling of subgrid scalar dissipation that is responsible for the subgrid fuel transport from the droplet surface towards the cell filtered mean has not been forthcoming. Instead, we introduce a new conditioning method based on two sets of conditional moments conditioned on two differently defined mixture fractions: the first mixture fraction is a fully conserved scalar, the second mixture fraction is based on the fluid mass originating from the liquid fuel stream and is strictly not conserved due to the evaporation process. The two-conditional moment approach is validated by comparison with measurements from a turbulent ethanol spray flame and predicted temperature and velocity profiles could significantly be improved when compared to conventional LES-CMC modelling.

Keywords

  • Mixture Fraction
  • Droplet Surface
  • Scalar Dissipation
  • Spray Flame
  • Scalar Dissipation Rate

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-319-10810-0_23
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Correspondence to A. Kronenburg .

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Ukai, S., Kronenburg, A., Stein, O.T. (2015). Certain Aspects of Conditional Moment Closure for Spray Flame Modelling. In: Nagel, W., Kröner, D., Resch, M. (eds) High Performance Computing in Science and Engineering ‘14. Springer, Cham. https://doi.org/10.1007/978-3-319-10810-0_23

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