Improvement of corner separation prediction using an explicit non-linear rans closure

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Abstract

In this paper, an investigation into the effect of explicit non-linear turbulence modelling on anisotropic turbulence flows is presented. Such anisotropic turbulence flows are typified in the corner separations in turbomachinery. The commonly used Reynolds-Averaged Navier-Stokes (RANS) turbulence closures, in which the Reynolds stress tensor is modelled by the Boussinesq (linear) constitutive relation with the mean strain-rate tensor, often struggle to predict the corner separation with reasonable accuracy. The physical reason for the modelling deficiency is partially attributable to the Boussinesq hypothesis which does not count for the turbulence anisotropy, whilst in a corner separation, the flow is subject to three-dimensional (3D) shear and the effects due to turbulence anisotropy shall not be ignored. Considering this, an explicit non-linear Reynolds stress-strain constitutive relation developed by Menter et al. is adopted as a modification of the Reynolds stress anisotropy. Coupled with the Menter’s hybrid k ω/k ε turbulence model, this nonlinear constitutive relation gives significantly improved predictions of the corner separations in a compressor cascade, at both the design and off-design flow conditions. The study of the mean vorticity field reveals the physical reasons for the prediction improvement, thus highlighting the rationality of the explicit anisotropic correction for the corner separation prediction.

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Sun, W., & Xu, L. (2021). Improvement of corner separation prediction using an explicit non-linear rans closure. Journal of the Global Power and Propulsion Society, 5, 50–65. https://doi.org/10.33737/jgpps/133913

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