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Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers
Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers
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Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers
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Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers
Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers

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Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers
Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers
Journal Article

Assessment of RANS-type turbulence models for CFD simulations of horizontal axis wind turbines at moderate Reynolds numbers

2023
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Overview
Nowadays, numerical simulations of wind turbines based on the Reynolds-averaged Navier–Stokes (RANS) formulation are becoming, in terms of computational cost, increasingly more viable tools for geometry optimization and design. Nevertheless, a judicious use of RANS-type methods is still required to guarantee acceptable accuracy at manageable computational cost. Here, we assess the accuracy and cost of several well-known turbulence models (Spalart–Allmaras, k - ε , k - ω SST, along with transitional modelling) with and without a zigzag tape modelling for a representative horizontal axis wind turbine within a range of moderate Reynolds numbers ( Re ≈ 3 × 10 5 to 8 × 10 5 ). This range allowed for the assessment of turbulence models under various complex flow conditions. Significant differences in performance have been found and, for a notable portion of the test cases, the k - ε model was able to deliver good results (similar to k - ω SST results) with a considerably coarser mesh. This suggests that k - ε , although often recognized as less accurate than k - ω SST, might actually be more efficient for wind turbine simulations. Also, although the best results came only with a coupled transition model which required a higher computational cost, this increase in cost is not exceedingly high and might allow for this model’s usage in later design stages. Accordingly, the present study is a valuable source for future wind turbine simulations and design and we hope that it fosters further developments in the field.