Static and Dynamic Analysis of a NACA 0021 Airfoil Section at Low Reynolds Numbers Based on Experiments and Computational Fluid Dynamics

Abstract

The wind industry needs airfoil data for ranges of angle of attack (AoA) much wider than those of aviation applications, since large portions of the blades may operate in stalled conditions for a significant part of their lives. Vertical axis wind turbines (VAWTs) are even more affected by this need, since data sets across the full incidence range of 180 deg are necessary for a correct performance prediction at different tip-speed ratios. However, the relevant technical literature lacks data in deep and poststall regions for nearly every airfoil. Within this context, the present study shows experimental and numerical results for the well-known NACA 0021 airfoil, which is often used for Darrieus VAWT design. Experimental data were obtained through dedicated wind tunnel measurements of a NACA 0021 airfoil with surface pressure taps, which provided further insight into the pressure coefficient distribution across a wide range of AoAs. The measurements were conducted at two different Reynolds numbers (Re = 140 k and Re = 180 k): each experiment was performed multiple times to ensure repeatability. Dynamic AoA changes were also investigated at multiple reduced frequencies. Moreover, dedicated unsteady numerical simulations were carried out on the same airfoil shape to reproduce both the static polars of the airfoil and some relevant dynamic AoA variation cycles tested in the experiments. The solved flow field was then exploited both to get further insight into the flow mechanisms highlighted by the wind tunnel tests and to provide correction factors to discard the influence of the experimental apparatus, making experiments representative of open-field behavior. The present study is then thought to provide the scientific community with high quality, low-Reynolds airfoil data, which may enable in the near future a more effective design of Darrieus VAWTs.

Numerical Analysis on the Effectiveness of Gurney Flaps as Power Augmentation Devices for Airfoils Subject to a Continuous Variation of the Angle of Attack by Use of Full and Surrogate Models

“…In order to assess the effectiveness of the numerical techniques prior to proceed with the extended sensitivity analysis on the GF effects on the airfoil in Darrieus-like motion, an experimental benchmark was identified. In particular, the test case presented by researchers from the Technical University (TU) of Berlin in [16] was used. Dedicated experimental studies were conducted inside the laminar wind tunnel of the Hermann Föttinger Institute.…”

“…The choice of the bullet-shaped domain was due to the possibility of imposing only an inlet (at which values of the velocity vector, turbulence intensity, and turbulent viscosity ratio were assumed) and an outlet boundary (at which the value of the gauge pressure was assumed, and for all other quantities zero normal derivative was assumed), with benefits in terms of calculation stability. The same approach was followed successfully in [16]. The works by Balduzzi et al [20] were taken as the main references in order to select the most suitable numerical settings for the solver.…”

“…Energies 2020, 04, x FOR PEER REVIEW 7 of 24 successfully in [16]. The works by Balduzzi et al [20] were taken as the main references in order to select the most suitable numerical settings for the solver.…”

Cartographing dynamic stall with machine learning

“…A full description of dynamic stall would be extraneous here but excellent reviews can be found in McAlister et al (1978), McCroskey (1982), McCroskey (1981, Leishman (2002) and Carr (1987). More modern experimental works can be found in Granlund et al (2014), Mulleners and Raffel (2013), , ), Müller-Vahl et al (2017, Strangfeld et al (2015), Balduzzi et al (2019), and Holst et al (2019). For the discussion here, it is sufficient to note that as the strength and phase of the leading vortex varies, so will the aeroelastic stability.…”

Cartographing dynamic stall with machine learning

“…The vortex then travels downstream causing a spike in low pressure across the airfoil which presents as a strong spike in lift and a strong dump in the moment. A full description of dynamic stall would be extraneous here but excellent reviews can be found in McAlister et al (1978); McCroskey (1982McCroskey ( , 1981; Leishman (2002); Carr (1987) and more modern experimental works can be found in Granlund et al (2014); Mulleners and Raffel (2013); ; ; Muller-Vahl et al (2017); Müller-Vahl et al (2015); Stangfeld et al (2015); Balduzzi et al (2019); Holst et al (2019)). For the discussion here, it is sufficient to note that the strength and phase of the leading vortex varies, so will the aeroelastic stability.…”