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Numerical investigation of turbulence models with emphasis on turbulent intensity at low Reynolds number flows

  • Musavir Bashir (School of Aerospace Engineering, Universiti Sains Malaysia, Engineering Campus) ;
  • Parvathy Rajendran (School of Aerospace Engineering, Universiti Sains Malaysia, Engineering Campus) ;
  • Ambareen Khan (School of Aerospace Engineering, Universiti Sains Malaysia, Engineering Campus) ;
  • Vijayanandh Raja (Department of Aeronautical Engineering, Kumaraguru College of Technology) ;
  • Sher Afghan Khan (Department of Mechanical Engineering, Faculty of Engineering, International Islamic University)
  • Received : 2022.06.22
  • Accepted : 2023.08.07
  • Published : 2023.07.25
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Abstract

The primary goal of this research is to investigate flow separation phenomena using various turbulence models. Also investigated are the effects of free-stream turbulence intensity on the flow over a NACA 0018 airfoil. The flow field around a NACA 0018 airfoil has been numerically simulated using RANS at Reynolds numbers ranging from 100,000 to 200,000 and angles of attack (AoA) ranging from 0° to 18° with various inflow conditions. A parametric study is conducted over a range of chord Reynolds numbers for free-stream turbulence intensities from 0.1 % to 0.5 % to understand the effects of each parameter on the suction side laminar separation bubble. The results showed that increasing the free-stream turbulence intensity reduces the length of the separation bubble formed over the suction side of the airfoil, as well as the flow prediction accuracy of each model. These models were used to compare the modeling accuracy and processing time improvements. The K- SST performs well in this simulation for estimating lift coefficients, with only small deviations at larger angles of attack. However, a stall was not predicted by the transition k-kl-omega. When predicting the location of flow reattachment over the airfoil, the transition k-kl-omega model also made some over-predictions. The Cp plots showed that the model generated results more in line with the experimental findings.

Keywords

Acknowledgement

This research was funded by Universiti Sains Malaysia Bridging GRA Grant (304/PAERO/6316608). The authors confirm that the data supporting the findings of this study are available within the article. The authors declare no conflict of interest.

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