Large Eddy Simulation Subfilter Modeling of Combustion-Affected Turbulence in Turbulent Premixed Combustion
ORAL · Invited
Abstract
In turbulent premixed combustion, thermal expansion across the flame is a source of velocity fluctuations and turbulent kinetic energy. The influence of this thermal expansion effect on the turbulence depends on the ratio of the flame thickness to the Kolmogorov length scale, that is, the Karlovitz number. At high Karlovitz number, the thermal expansion effect is overwhelmed by dissipation and does not strongly influence the turbulence. However, at low Karlovitz number, the thermal expansion effect becomes the dominant source of turbulent kinetic energy. With Large Eddy Simulation, at low Karlovitz number, the flame will never be resolved, so the dominant thermal expansion production mechanism must be included in subfilter turbulence models. Direct Numerical Simulation databases of turbulent premixed planar jet flames at low and high Karlovitz number are utilized to assess a series of candidate subfilter turbulence models for both the subfilter stresses and the subfilter scalar fluxes. Three candidate models are considered: the Smagorinksy model, the Clark model, and an algebraic mixed model that explicitly accounts for thermal expansion effects presuming an infinitely thin flame. At high Karlovitz number, all models correctly capture the negligible influence of the flame on the turbulence. However, at low Karlovitz number, only the Clark model and the algebraic mixed model can capture the strong influence of the flame on the turbulence, manifested as generalized counter-gradient transport. This conclusion is independent of filter width, and counter-gradient transport is found to persist across all scales. In a posteriori tests, the algebraic mixed model is found to more accurately capture the influence of the flame on the turbulence since it explicitly includes information about the underlying flame structure. Looking forward, a new framework is proposed for subfilter turbulence modeling utilizing conditionally filtered velocities.
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Presenters
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Michael E. Mueller
Princeton Univ, Princeton University
Authors
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Michael E. Mueller
Princeton Univ, Princeton University
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Jonathan F MacArt
University of Illinois at Urbana-Champaign