Turbulent mixing model based on ordered pairing

Norris, Andrew T.; Pope, Stephen B.

doi:10.1016/0010-2180(91)90201-l

Cited by 48 publications

(29 citation statements)

References 16 publications

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“…This trend has been observed in DNS (Eswaran and Pope, 1988;Givi and McMurtry, 1988) and has been corroborated by experimental measurements (Miyawaki et al, 1974;Tavoularis and Corrsin, 1981). This deficiency associated with the C/D closure has been long recognized, and within the past decade significant efforts have been devoted toward developing closures that can overcome this nonphysical behavior (for example, Pope, 1982;Norris and Pope, 1991).…”

Section: Introductionmentioning

confidence: 55%

Modeling of isotropic reacting turbulence by a hybrid mapping‐EDQNM closure

1992

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A hybrid model is developed and implemented for predicting the limiting bound of the reactant conversion rate in an isotropic turbulent flow under the influence of a reaction of the type A+B-Products. This model is based on the amplitude mapping closure of Kraichnan for the molecular mixing of a stochastically distributed scalar, and the eddy-damped quasi-normal Markovian ( EDQNM) spectral closure for the two-point scalar covariance. The results predicted by this model compare well with available experimental data in both gaseous and aqueousplug-flow reactors, but point to the need for more detailed measurements in future experimental studies. With the implementation of the mapping closure, a simple analytical expression is obtained for the decay rate of the unmixedness. This expression is very convenient and is recommended for direct practical applications in the modeling and design of plug-flow reactors.

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Section: Introductionmentioning

confidence: 55%

Modeling of isotropic reacting turbulence by a hybrid mapping‐EDQNM closure

1992

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“…The MC model is local in a strong sense, meaning that only neighboring particles in scalar space interact with each other. This property is advantageous especially for reactive scalars with strongly localized reaction zones [29,20]. Later an algorithmic extension of Pope's MC particle implementation for multiple scalars was devised by Subramaniam and Pope [16].…”

Section: Different Mixing Modelsmentioning

confidence: 98%

Micromixing models for turbulent flows

Meyer

Jenny

2009

Journal of Computational Physics

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“…Detailed discussion regarding the importance of these principles can be found in the the literature [1,2]. Here, we only emphasise the importance of localness for mixing to occur [3]. Generally improvements to the mixing model are limited by the resolution for the flow field and thus discrepancies are more pronounced in the RANS context [4].…”

Section: Introductionmentioning

confidence: 99%

Stochastic multiple mapping conditioning for a piloted, turbulent jet diffusion flame

Vogiatzaki

Kronenburg

Navarro‐Martinez

et al. 2011

Proceedings of the Combustion Institute

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract: A stochastic implementation of the Multiple Mapping Conditioning (MMC) approach has been applied to a turbulent jet diffusion flame (Sandia Flame D). This implementation combines the advantages of the basic concepts of a mapping closure methodology with a probability density approach. A single reference variable has been chosen. Its evolution is described by a Markov process and then mapped to the mixture fraction space. Scalar micro-mixing is modelled by a modified ``interaction by exchange with the mean'' (IEM) mixing model where the particles mix with their -in reference space-conditionally averaged means. The formulation of the closure leads to localness of mixing in mixture fraction space and consequently improved localness in composition space. Results for mixture fraction and reactive species are in good agreement with the experimental data. The MMC methodology allows for the introduction of an additional ``minor dissipation time scale'' that controls the fluctuations around the conditional mean. A sensitivity analysis based on the conditional temperature fluctuations as a function of this time scale does not endorse earlier estimates for its modelling, but only relatively large dissipation time scales of the order of the integral turbulence time scale yield acceptable levels of conditional fluctuations that agree with experiments. With the choice of a suitable dissipation time scale, MMC-IEM thus provides a simple mixing model that is capable of capturing extinction phenomena, and it gives improved predictions over conventional PDF predictions using simple IEM mixing models. turing extinction phenomena, and it gives improved predictions over conventional PDF predictions using simple IEM mixing models. Permanent repository link Stochastic Multiple Mapping

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Turbulent mixing model based on ordered pairing

Cited by 48 publications

References 16 publications

Modeling of isotropic reacting turbulence by a hybrid mapping‐EDQNM closure

Modeling of isotropic reacting turbulence by a hybrid mapping‐EDQNM closure

Micromixing models for turbulent flows

Stochastic multiple mapping conditioning for a piloted, turbulent jet diffusion flame

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