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Subfilter scalar-flux vector orientation in homogeneous isotropic turbulence.
Verma, Siddhartha; Blanquart, G.
Afiliação
  • Verma S; Graduate Aerospace Laboratories, California Institute of Technology, Pasadena, California, USA.
  • Blanquart G; Department of Mechanical Engineering, California Institute of Technology, Pasadena, California, USA.
Article em En | MEDLINE | ID: mdl-25019887
The geometric orientation of the subfilter-scale scalar-flux vector is examined in homogeneous isotropic turbulence. Vector orientation is determined using the eigenframe of the resolved strain-rate tensor. The Schmidt number is kept sufficiently large so as to leave the velocity field, and hence the strain-rate tensor, unaltered by filtering in the viscous-convective subrange. Strong preferential alignment is observed for the case of Gaussian and box filters, whereas the sharp-spectral filter leads to close to a random orientation. The orientation angle obtained with the Gaussian and box filters is largely independent of the filter width and the Schmidt number. It is shown that the alignment direction observed numerically using these two filters is predicted very well by the tensor-diffusivity model. Moreover, preferred alignment of the scalar gradient vector in the eigenframe is shown to mitigate any probable issues of negative diffusivity in the tensor-diffusivity model. Consequentially, the model might not suffer from solution instability when used for large eddy simulations of scalar transport in homogeneous isotropic turbulence. Further a priori tests indicate poor alignment of the Smagorinsky and stretched vortex model predictions with the exact subfilter flux. Finally, strong filter dependence of subfilter scalar-flux orientation suggests that explicit filtering may be preferable to implicit filtering in large eddy simulations.
Assuntos
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Base de dados: MEDLINE Assunto principal: Algoritmos / Modelos Estatísticos / Dinâmica não Linear Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article
Buscar no Google
Base de dados: MEDLINE Assunto principal: Algoritmos / Modelos Estatísticos / Dinâmica não Linear Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2014 Tipo de documento: Article