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Stochastic modeling of multiple scalar mixing in a three-stream concentric coaxial jet based on one-dimensional turbulence

  • Modeling turbulent mixing is a standing challenge for nonpremixed chemically reacting flows. Key complications arise from the requirement to capture all relevant scales of the flow and the necessity to distinguish between turbulent advective transport and molecular diffusive transport processes. In addition, anisotropic mean shear, variable advection time scales, and the coexistence of turbulent and nonturbulent regions need to be represented. The fundamental issues at stake are addressed by investigating multi-scalar mixing in a three-stream coaxial jet with a map-based stochastic one-dimensional turbulence model. ODT provides full-scale resolution at affordable costs by a radical reduction of complexity compared to high-fidelity Navier–Stokes solvers. The approach is partly justified by an application of the boundary-layer approximation, but neglects fluctuating axial pressure gradients. It is demonstrated that low-order scalar statistics are reasonably but not fully captured. Despite this shortcoming, it is shown that the model isModeling turbulent mixing is a standing challenge for nonpremixed chemically reacting flows. Key complications arise from the requirement to capture all relevant scales of the flow and the necessity to distinguish between turbulent advective transport and molecular diffusive transport processes. In addition, anisotropic mean shear, variable advection time scales, and the coexistence of turbulent and nonturbulent regions need to be represented. The fundamental issues at stake are addressed by investigating multi-scalar mixing in a three-stream coaxial jet with a map-based stochastic one-dimensional turbulence model. ODT provides full-scale resolution at affordable costs by a radical reduction of complexity compared to high-fidelity Navier–Stokes solvers. The approach is partly justified by an application of the boundary-layer approximation, but neglects fluctuating axial pressure gradients. It is demonstrated that low-order scalar statistics are reasonably but not fully captured. Despite this shortcoming, it is shown that the model is able to reproduce experimental state-space statistics of multi-stream multi-scalar mixing. The model therefore offers physics-compatible improvements in multi-stream mixing modeling despite some fundamental limitations that remain from unjustified assumptions.show moreshow less

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Metadaten
Author: Marten KleinORCiD, Christian Zenker, Tommy StarickORCiD, Heiko SchmidtORCiD
DOI:https://doi.org/10.1016/j.ijheatfluidflow.2023.109235
ISSN:0142-727X
Title of the source (English):International Journal of Heat and Fluid Flow
Contributor(s): Katja Hertha
Document Type:Scientific journal article peer-reviewed
Language:English
Year of publication:2023
Tag:map-based stochastic advection modeling; multiple passive scalars; one-dimensional turbulence; turbulent jet; turbulent mixing
Volume/Year:104
First Page:1
Last Page:17
Comment:
This article is part of the "TSFP12 Special Issue".
Article number:109235
Fundername (not EU):Bundesministerium für Bildung und Forschung; Bundesministerium für Wirtschaft und Klimaschutz
Project number (not EU):85056897; 03SF0693A; 03EWS002A
Way of publication:Open Access
Faculty/Chair:Fakultät 3 Maschinenbau, Elektro- und Energiesysteme / FG Numerische Strömungs- und Gasdynamik
Zentrale Einrichtungen / Energie-Innovationszentrum / Scientific Computing Lab
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