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Subgrid-scale stress parameterization for anisotropic turbomachinery flow as deduced from stereoscopic particle image velocimetry measurements

  • Ghasem AkbariEmail author
  • Nader Montazerin
Technical Paper

Abstract

The present study searches for parametric subgrid-scale models for the turbomachinery flow based on single-plane stereoscopic particle image velocimetry measurements. A group of deformation tensors are used as the predictors to parameterize the subgrid-scale stress tensor as the response. Missing terms in the rotation rate tensor are completed with a novel approach which is based on geometrical relations between deformation and subgrid-scale tensors. The optimal relations for parametric subgrid-scale models are shaped after minimizing the square of error between modeled and real SGS stresses. The most superior and inferior one-predictor models are based on strain rate and rotation rate tensors, respectively. The two-predictor models show the most efficient prediction of subgrid-scale stress where the correlation coefficient is up to 43% larger than that of the classical Smagorinsky model. The three- to five-predictor models are inefficient since they give minor enhancement of correlation coefficient with a considerably larger computational cost.

Keywords

Parametric model Subgrid-scale model Stereoscopic particle image velocimetry Turbomachinery flow Strain–rotation tensors 

Notes

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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  1. 1.Department of Mechanical Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin BranchIslamic Azad UniversityQazvinIran
  2. 2.Department of Mechanical EngineeringAmirkabir University of TechnologyTehranIran

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