We present a new system for the generation of rapid, strong flow perturbations in the aerodynamic wind tunnel at École Centrale de Nantes. The system is called the

The atmospheric boundary layer is naturally turbulent, and these turbulence conditions are highly complex and nonstationary. One characteristic of atmospheric turbulence is that compared to a Gaussian distribution, the probability of extreme events, i.e., gusts, is significantly higher, and this effect is called

Wind turbines operate in this part of the atmospheric boundary layer, and one consequence is that they experience high loads, partially due to the intermittency in the wind (see, e.g.,

The velocity amplitude

For example, the EOG used for a wind turbine of class I.A with diameter

To investigate the aerodynamic reaction of rotor blades to turbulence and gusts, laboratory-scale experimental research is an acknowledged method. Here, the inclusion of turbulence and unsteady flows is important to model the real atmospheric conditions more closely. Over the years, different approaches have been used to include turbulence in wind tunnel experiments, and they can be classified into two categories: passive and active devices.

An example of passive devices are grids. They are often used in the wind tunnel to include turbulence in airfoil and rotor aerodynamics investigations, as done by

To overcome these limitations, setups that actively control the inflow in the wind tunnel can be used.

One example is the generation of transverse gusts by inducing a flow perpendicular to the stream-wise direction, as done for example by

To generate stream-wise gusts in the test section, the flow can be altered globally in the wind tunnel.

Another approach to generate stream-wise gusts is to alter the flow directly at the beginning of the test section with active devices. The methods depend on the aimed gust shape. One possibility is the generation of periodic gusts in the wind tunnel.

Another device that is capable of creating customized flows and also gusts is an active grid. The most common design was proposed by

Overall, there are different systems to generate gusts and specific flows. Many of the above-presented experiments focus on the generation of gusts and flows tailored to investigate isolated aerodynamic effects.

In this study, we will present a new perturbation system with a unique mechanism consisting of a rotating bar. The objective of this new perturbation system, called the “chopper”, is to combine sudden, strong mean flow changes and turbulence, which is targeted separately in other perturbation devices. This setup will help to improve the insight into blade and rotor aerodynamics under turbulent and unsteady conditions. This is important as the global pitch control can not mitigate the loads caused by unsteady aerodynamic effects due to gusts. On the contrary, active flow control (AFC) strategies using sensors and actuators that are placed locally at the blades may be able to do so. Using for example plasma actuators, a fast and local control with up to 10 kHz can be achieved, and up to a few kHz can be achieved in the case of micro-jet actuators (see, e.g.,

The present paper is a proof of concept of this new system, and it focuses on investigating the mean flow behavior, the shape and the characteristic time of the perturbation, and the turbulence generated by the system throughout the test section. The amplitude and the characteristic time of the perturbation will be compared to the IEC EOG. Further customization of the perturbation system will be needed to match realistic gusts like the one discussed for example by

The paper is organized as follows: in Sect.

In the following, the chopper and the experimental setup used to characterize the flow disturbance generated by it are introduced. In Fig.

Experimental setup: the rotating chopper blade (blue) cuts through the inlet of the wind tunnel test section, thus generating a flow disturbance. An induction sensor returns a signal when the chopper blade crosses the horizontal centerline of the test section inlet. Measurements were carried out using an array of five hot-wire probes at the positions marked with red dots within the turquoise measurement planes.

The test section's dimensions are 500 mm

To characterize the chopper, an array equipped with five 1-D hot-wire probes of the type 55P11 with a sensor length of 1.25 mm from Dantec Dynamics was used. A sketch of the probe arrangement can be found in Fig.

The inflow velocity was

Convergence test of the phase average at five different points of time during the gust event for a data set measured at the centerline at

In the next section, the results from these measurements are presented.

In the following, the structure and the downstream evolution of the inverse gust generated by the chopper will be presented. For a first overview, an example of the time series will be shown in combination with the energy spectral density. The separate elements of the gust structure will be explained. Afterwards, the evolution of the gust will be investigated by looking at the average gust flow field, the inverse gust shape, and the turbulence within the gust. The analysis will include mean velocities

Gust produced by the chopper, measured at the centerline 5.425

In Fig.

Figure

Energy spectral density of the measured time series at the centerline 5.425

Example of a triple decomposition of the inverse gust

The investigation of the gust time series and the energy spectral density shows how the recurring inverse gust generated by the chopper can be decomposed into three parts: the mean velocity of the inverse gust, the underlying shape of the inverse gust as a recurring, global large-scale flow structure, and the turbulence within the gust. This triple decomposition is illustrated in Fig.

Example of a spectral decomposition of the inverse gust

In the following, the properties of the mean gust velocity flow field will be investigated by looking at the evolution of

Note that the mean gust velocity differs by this definition from the mean velocity of the whole time series.

. The average standard deviation is determined similarly. For a better comparison between the measurements, the same window with respect to the chopper position is used for all data sets for the respective chopper frequency.Interpolated surface plot of the downstream evolution of the mean velocity of the inverse gust for

In Fig.

In Fig.

Interpolated surface plot of the mean velocity of the inverse gust in the

Next, the average turbulence intensity of the inverse gust is plotted. For this, the average over the standard deviations

Interpolated surface plot of the turbulence intensity of the inverse gust for

As presented in Fig.

Interpolated surface plot of the turbulence intensity of the inverse gust in the

Plot of all inverse gusts captured in the time series measured at the centerline 5.425

In the following, the underlying inverse gust shape

In the case of

Span-wise evolution of the smoothened average inverse gust at

To increase the understanding of the underlying inverse gust shape

These observations also hold for the high chopper frequency (Fig.

Moving downstream to the last measurement position at

Span-wise evolution of the smoothed average inverse gust at

With a chopper blade width of

Average normalized characteristic time

In order to quantify the characteristic time of the inverse gust and its dispersion, Fig.

Energy spectral density of all inverse gusts (blue–green–yellow color map) with the average spectrum plotted in red and a decay according to

Interpolated surface plot of the integral length scale of the gust fluctuations for

After investigating the mean gust properties and the underlying inverse gust shape, next, some turbulence characteristics of the gust will be discussed by investigating the gust fluctuations

To further characterize the gust turbulence, the one-dimensional energy spectrum is as suggested by

The integral length scale is of interest when carrying out aerodynamic experiments because the interaction between the airfoil and the flow structures depends on the ratio

The chopper, a new system for the generation of strong, sudden inverse gusts in a wind tunnel, has been presented together with a first investigation of the flow generated by it. The experimental campaign was performed at 65 measurement points in the three-dimensional volume of the test section to characterize the stream-wise flow behind this new perturbation system. The focus of this study was on the identification of governing parameters that influence the unsteady flow to refine experiments in the future. The inverse gust structure induced by the chopper has been examined for a fixed inflow velocity and two different chopper frequencies, and the parameters were chosen to match the specifications of future experiments. First, the periodic flow variation that is generated each time the chopper blade crosses the inlet was discussed by means of the time series and its energy spectrum. To gain a better understanding of the inverse gust structure itself, in the next step, the gust events were brought into focus. It was shown how the inverse gust has an underlying shape with superimposed fluctuations, so that each inverse gust can be decomposed into a mean gust velocity

Overall, a new system was presented that is capable of generating large, rapid velocity fluctuations while also inducing turbulence. By means of the downstream position and the chopper frequency, experiments can be carried out in different regions of the flow field that have different characteristics and different complexity. The complexity of the flow increases towards the inlet. For example, the aerodynamic behavior of an airfoil can be studied downstream where the flow is already quite homogeneous, and then it can be compared to the aerodynamic behavior of the airfoil positioned farther upstream in the inhomogeneous region where three-dimensional effects will be present. This gives an opportunity to study the effect of radial inflow changes which may cause similar effects as rotational augmentation that is observed in rotational blades due to an additional radial flow (see

This investigation has shown us limits and opportunities of the setup and the measurements, which helps us to improve the setup in the future. The currently very high blockage induced by the chopper blade will be reduced in the future by reducing the chopper blade width. We expect this to also decrease the currently very high velocity amplitudes of the gust. Moreover, new chopper blade designs are possible that reduce the inhomogeneity of the flow field. To generate “normal” instead of inverse gusts, the design of a rotating disc with varying blockage is also possible. As the flow between the gusts has a low turbulence intensity, in addition, background turbulence can be added by installing a grid upstream of the chopper blade. To verify to what extent the gust generation mechanisms are universal with respect to the chopper frequency, more chopper frequencies need to be investigated. The experimental campaign that was presented gives a good overview of the flow evolution in the test section, but it should be complemented by measurements of all flow components and with higher spatial resolution of the measurement points. To form a comprehensive picture both in space and in time, future investigations may involve phase-averaged and/or time-resolved particle image velocimetry as well as simulations.

The data are available upon request.

CB was in charge of the project administration and the resources, and she designed the system and acquired the funding. IN developed the methodology, acquired the data, performed the formal analysis and data investigation, and wrote the original draft. IN and CB reviewed and edited the manuscript.

The authors declare that they have no conflict of interest.

This article is part of the special issue “Wind Energy Science Conference 2019”. It is a result of the Wind Energy Science Conference 2019, Cork, Ireland, 17–20 June 2019.

The authors would like to thank WEAMEC (West Atlantic Marine Energy Community). Further, the authors would like to thank CSTB for providing measurement equipment.

This work was carried out within the research projects ASAPe with the funding from region Pays-de-Loire, École Centrale de Nantes, and Ville de Nantes (grant no. 2018 ASAPe) and ePARADISE with the funding from ADEME/region Pays-de-Loire (grant no. 1905C0030).

This paper was edited by Katherine Dykes and reviewed by three anonymous referees.