Analytical assessment of models for large eddy simulation of particle laden flow. (English) Zbl 1273.76198
Summary: For large eddy simulation of particle-laden flow, the effect of the unresolved scales on the particles needs to be modelled. The present work contains an analysis of three such models, namely approximate deconvolution method (ADM) as proposed by J. G. M. Kuerten [Phys. Fluids 18, No. 2, Article ID 025108 (2006; doi:10.1063/1.2176589)] and two stochastic models proposed by B. Shotorban and F. Mashayek [ibid. 7, Paper No. 18, (2006; doi:10.1080/14685240600595685)] and O. Simonin, E. Deutsch and J. P. Minier [Appl. Sci. Res. 51, No. 1-2, 275–283 (1993; Zbl 0778.76098)]. The purpose of the analysis is twofold. On the one hand, the results serve for model selection in dependence of the application and on the other hand, the analysis shows possibilities for model improvement. The present work contains for each model an analytical computation of averages (first moments) and root-mean square values (second moments) of particle velocity, particle position and fluid velocity seen by the particles. Results indicate that for large Stokes number, ADM yields higher accuracy than the stochastic models analysed, whereas for small Stokes number the stochastic models give higher accuracy. An analytical estimate for the model error is given in dependence of Stokes number and the energy spectrum of the flow. This information can be used for model selection and for reliability prediction. Furthermore, it is shown that both stochastic models contain a deficient convective term, which should be avoided in future model development. The analysis is backed by numerical results from literature.
MSC:
| 76F65 | Direct numerical and large eddy simulation of turbulence |
| 76M25 | Other numerical methods (fluid mechanics) (MSC2010) |
| 76M35 | Stochastic analysis applied to problems in fluid mechanics |
| 76T15 | Dusty-gas two-phase flows |
Keywords:
large eddy simulation; particle-laden flow; turbulence model; approximate deconvolution method; generalised Langevin modelCitations:
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