Monte Carlo simulations of turbulent non-premixed combustion using a velocity conditioned mixing model

Michael Stoellinger, Denis Efimov, Dirk Roekaerts

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

1 Downloads (Pure)

Abstract

Non-premixed turbulent combustion in a laboratory scale flame (Delft III flame) is studied using a statistical description at the one-point one-time joint velocity—scalar composition probability density function (PDF) level. The PDF evolution equation is solved using a stochastic Lagrangian Monte Carlo method.The PDF equation requires a so called micro-mixing model for closure and the performance of two micro-mixing models is investigated. The Interaction by Exchange with the Mean (IEM) micro mixing model is the most commonly adopted model. The IEM model was developed for the scalar PDF method and does not depend on velocity statistics.Aphysically more sound extension of the IEM is the Interaction by Exchange with the Conditional Mean (IECM) which involves mixing of the scalars towards mean values conditional on the velocity. Both models are applied in this work and it is shown that the IECM model does perform significantly better than the simple IEM model.

Original languageEnglish
Title of host publicationStochastic equations for complex systems
Subtitle of host publicationtheoretical and computational topics
EditorsStefan Heinz, Hakima Bessaih
Place of PublicationBerlin
PublisherSpringer
Pages143-174
Number of pages32
ISBN (Print)978-3-319-18205-6
DOIs
Publication statusPublished - 1 Jan 2015

Publication series

NameMathematical Engineering
Volume20
ISSN (Print)2192-4732

Fingerprint Dive into the research topics of 'Monte Carlo simulations of turbulent non-premixed combustion using a velocity conditioned mixing model'. Together they form a unique fingerprint.

  • Cite this

    Stoellinger, M., Efimov, D., & Roekaerts, D. (2015). Monte Carlo simulations of turbulent non-premixed combustion using a velocity conditioned mixing model. In S. Heinz, & H. Bessaih (Eds.), Stochastic equations for complex systems: theoretical and computational topics (pp. 143-174). (Mathematical Engineering; Vol. 20). Springer. https://doi.org/10.1007/978-3-319-18206-3_7