Atomization Modeling Using Surface Density And Stochastic Fields

Aqeel Ahmed, Giovanni Tretola, Salvador Navarro-Martinez, Konstantina Vogiatzaki, B. Duret, Julien Reveillon, Francois-Xavier Demoulin

Research output: Contribution to journalArticlepeer-review

Abstract

Correct prediction of the spray in automotive and aerospace engines remains a challenging task. In this work we present a numerical framework to characterize the spray, using both the large scale quantities, like mean liquid volume fractions, as well as small scale structures or liquid droplets. In the limit of high Reynolds and Weber number, the drop size is expected to be much smaller than can be resolved using first principles on a given mesh, thus a subgrid formulation is used to characterize the drop size. Using liquid gas interface surface density we have compared a standard formulation as well as a probability density function-based formulation. Using large eddy simulation we compared against the experimental database hosted by the engine combustion network for a single hole injector. Sauter mean diameter is predicted well using our formulation; at the same time use of the probability density function brings additional information regarding drop size distribution.

Original languageEnglish
Pages (from-to)239-266
Number of pages28
JournalAtomization and Sprays
Volume30
Issue number4
DOIs
Publication statusPublished - 2020

Keywords

  • Atomization
  • Engine combustion network (ecn) spray a
  • Large eddy simulation (les)
  • Probability density functions (pdf)
  • Stochastic fields

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