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Stochastic Equations for Complex Systems pp 143–174Cite as

Monte Carlo Simulations of Turbulent Non-premixed Combustion using a Velocity Conditioned Mixing Model

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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. A physically 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.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Wyoming, Laramie, USA

    Michael Stoellinger

  2. Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Denis Efimov

  3. Process & Energy, Delft University of Technology, Delft, The Netherlands

    Dirk Roekaerts

Authors
  1. Michael Stoellinger
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  2. Denis Efimov
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  3. Dirk Roekaerts
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Corresponding author

Correspondence to Michael Stoellinger .

Editor information

Editors and Affiliations

  1. University of Wyoming, Laramie, Wyoming, USA

    Stefan Heinz

  2. University of Wyoming, Laramie, Wyoming, USA

    Hakima Bessaih

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Stoellinger, M., Efimov, D., Roekaerts, D. (2015). Monte Carlo Simulations of Turbulent Non-premixed Combustion using a Velocity Conditioned Mixing Model. In: Heinz, S., Bessaih, H. (eds) Stochastic Equations for Complex Systems. Mathematical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-18206-3_7

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  • DOI: https://doi.org/10.1007/978-3-319-18206-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18205-6

  • Online ISBN: 978-3-319-18206-3

  • eBook Packages: EngineeringEngineering (R0)

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