Adv. Appl. Math. Mech., 10 (2018), pp. 978-997.
Published online: 2018-07
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This work is devoted to performing systematic sensitivity analysis of different turbulence models and various incoming wind conditions in predicting the wake flow behind a horizontal-axis wind turbine represented by an actuator disc (AD). The tested turbulence models are the standard $k−є$ model and the Reynolds Stress Model (RSM). Employing each turbulence model, the wind turbine immersed in four inflow conditions, including both uniform and non-uniform ones, is numerically studied. Simulation results are validated against Sexbierum field experimental data. Comparisons show that $k−є$ model is much more sensitive to the employed inflow conditions, with simulated wake velocity and turbulence profiles strongly differ from one condition to another; among them, a uniform TI & Length scale condition delivers the most accurate predictions. By contrast, comparisons identify that RSM is less sensitive to the inflow condition implemented, and the results under all inflow conditions are consistently in fair match with the measurements; the RSM is found to be more robust for capturing wake behavior reliably when using the AD/RANS approach.
}, issn = {2075-1354}, doi = {https://doi.org/10.4208/aamm.OA-2017-0253}, url = {http://global-sci.org/intro/article_detail/aamm/12505.html} }This work is devoted to performing systematic sensitivity analysis of different turbulence models and various incoming wind conditions in predicting the wake flow behind a horizontal-axis wind turbine represented by an actuator disc (AD). The tested turbulence models are the standard $k−є$ model and the Reynolds Stress Model (RSM). Employing each turbulence model, the wind turbine immersed in four inflow conditions, including both uniform and non-uniform ones, is numerically studied. Simulation results are validated against Sexbierum field experimental data. Comparisons show that $k−є$ model is much more sensitive to the employed inflow conditions, with simulated wake velocity and turbulence profiles strongly differ from one condition to another; among them, a uniform TI & Length scale condition delivers the most accurate predictions. By contrast, comparisons identify that RSM is less sensitive to the inflow condition implemented, and the results under all inflow conditions are consistently in fair match with the measurements; the RSM is found to be more robust for capturing wake behavior reliably when using the AD/RANS approach.