Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

Predicting wind turbine blade loads using vorticity transport and RANS methodologies

Fletcher, Timothy M. and Brown, Richard and Kim, Da Hye and Kwon, Oh Joon (2009) Predicting wind turbine blade loads using vorticity transport and RANS methodologies. In: European Wind Energy Conference and Exhibition, EWEC 2009, 2009-03-16 - 2009-03-19.

[img]
Preview
PDF (strathprints027431.pdf)
strathprints027431.pdf

Download (1MB) | Preview

Abstract

Two computational methods, one based on the solution of the vorticity transport equation, and a second based on the solution of the Reynolds-Averaged Navier-Stokes equations, have been used to simulate the aerodynamic performance of a horizontal axis wind turbine. Comparisons have been made against data obtained during Phase VI of the NREL Unsteady Aerodynamics Experimental and against existing numerical data for a range of wind conditions. The Reynolds-Averaged Navier-Stokes method demonstrates the potential to predict accurately the flow around the blades and the distribution of aerodynamic loads developed on them. The Vorticity Transport Model possesses a considerable advantage in those situtations where the accurate, but computationally efficient, modelling of the structure of the wake and the associated induced velocity is critical, but where the prediction of blade loads can be achieved with sufficient accuracy using a lifting-line model augmented by incorporating a semi-empirical stall delay model. The largest benefits can be extracted when the two methods are used to complement each other in order to understand better the physical mechanisms governing the aerodynamic performance of wind turbines.