WESWind Energy ScienceWESWind Energ. Sci.2366-7451Copernicus PublicationsGöttingen, Germany10.5194/wes-3-713-2018Advanced computational fluid dynamics (CFD)–multi-body simulation (MBS) coupling to assess low-frequency emissions from wind turbinesAdvanced CFD-MBS coupling to assess low-frequency emissions from wind turbinesKleinLevinlevin.klein@iag.uni-stuttgart.dehttps://orcid.org/0000-0003-0134-9952GudeJonasWenzFlorianhttps://orcid.org/0000-0002-4201-588XLutzThorstenKrämerEwaldInstitute of Aerodynamics and Gas Dynamics, University of Stuttgart, Pfaffenwaldring 21, 70569 Stuttgart, GermanyLevin Klein (levin.klein@iag.uni-stuttgart.de)17October20183271372826June20185July201819September201823September2018This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://wes.copernicus.org/articles/3/713/2018/wes-3-713-2018.htmlThe full text article is available as a PDF file from https://wes.copernicus.org/articles/3/713/2018/wes-3-713-2018.pdf
The low-frequency emissions from a generic 5MW wind turbine are
investigated numerically. In order to regard airborne noise and
structure-borne noise simultaneously, a process chain is developed. It
considers fluid–structure coupling (FSC) of a computational fluid dynamics
(CFD) solver and a multi-body simulations (MBSs) solver as well as a Ffowcs-Williams–Hawkings (FW-H) acoustic solver. The approach is applied to a
generic 5MW turbine to get more insight into the sources and
mechanisms of low-frequency emissions from wind turbines. For this purpose
simulations with increasing complexity in terms of considered components in
the CFD model, degrees of freedom in the structural model and inflow in the
CFD model are conducted. Consistent with the literature, it is found that
aeroacoustic low-frequency emission is dominated by the blade-passing
frequency harmonics. In the spectra of the tower base loads, which excite
seismic emission, the structural eigenfrequencies become more prominent with
increasing complexity of the model. The main source of low-frequency
aeroacoustic emissions is the blade–tower interaction, and the contribution of
the tower as an acoustic emitter is stronger than the contribution of the
rotor. Aerodynamic tower loads also significantly contribute to the external
excitation acting on the structure of the wind turbine.
Introduction
Renewable sources of energy and
especially wind power have seen a strong expansion in the last years. Even
though the construction of large offshore wind farms is currently a strong
focus, the potential of onshore wind turbines by opening up new, previously
unused areas and repowering of existing sites is still significant. With
regard to the acceptance and the fulfillment of stricter legal requirements
concerning noise and vibrations, the research on low-frequency emissions from
wind turbines gains importance.
Emissions from wind turbines
As wind turbines are counted among the tallest machines on the planet that
work in an uncontrolled outside environment, noise and vibration emissions
occur in a broad frequency range. While sources of acoustic wind turbine
emission in the audible range are widely researched and understood and
different methods are applied to reduce aerodynamic and mechanical noise
, much less is known about low-frequency emissions
from wind turbines. Many publications about low-frequency emissions from wind
turbines concentrate on the impact on seismic measurements. The emitted
ground motion signals from wind turbines are measured by local seismic
stations built for the detection of events with small magnitudes like far-away
earthquakes or nuclear weapons tests. observed an
increase in amplitudes in a frequency range from 0.5 to
10Hz dependent on the rotational speed of the turbine and thus
wind speed at a distance of 5.5km away from a wind turbine. This
confirms the measurements by and
, who found that nearby wind turbines reduce the
sensitivity of seismic stations as they introduce wind dependence into the
measured noise spectra.
Acoustic measurements in the low-frequency range 3.3km from a wind
farm show discrete peaks at the blade-passing frequency (BPF) and its higher
harmonics below 20Hz. This was also
observed by , who evaluated the data obtained by a
micro-barometer array for infrasound detection located in northern Germany.
compared outdoor and indoor
measurements close to an Australian wind farm and found the same tonal
character in the noise spectra. Hence, the blade–tower interaction is seen to
be responsible for aeroacoustic low-frequency noise of wind farms
.
The scope of research on low-frequency noise from wind turbines is often its
impact on human beings. conclude from their
literature survey that human health is not likely to be affected by
low-frequency noise and infrasound from wind turbines.
state that the measured level of infrasound
within two Australian wind farms was similar to that measured in urban and
coastal areas and near other engineered noise sources.
Numerical approaches on low-frequency noise
For an optimization of the structure and foundations of future wind turbines
as well as for the assessment of the impact of low-frequency noise and
low-frequency seismic vibrations on the environment, reliable methods for the
prediction of emissions are of great importance.
performed a numerical study to calculate wave propagation using the boundary
element method. They developed a model which considers the seismic
vibrations mentioned as well as the low-frequency noise in air and even allows a
prediction of the sound pressure level (SPL) inside a generic building. But
as this model is only capable of calculating the propagation, reliable input
data representing the airborne and structure-borne emissions from the wind
turbine have to be provided. Computational fluid dynamics (CFD) simulations including fluid–structure
interaction (FSI) are capable of providing both. Thus,
used data made available by the authors of
the present paper.
There are few studies on the modeling of aeroacoustic low-frequency emission
from wind turbines. In the 1980s, NASA developed a code for predicting
low-frequency wind turbine noise based on Lowson's acoustic equation applied
to rotor forces . presented
a blade element momentum (BEM) based investigation of low-frequency noise
that uses the same theory for the aeroacoustic model. CFD simulations
combined with the Ffowcs-Williams–Hawkings (FW-H) propagation method have been applied by
and to assess
low-frequency noise of wind turbine rotors. While
considered the influence of the tower on the rotor aerodynamics,
and
studied the isolated rotor. investigated the
blade-passage noise of a generic model turbine numerically using CFD and
Curle's acoustic analogy. They found a significant contribution of the
induced pressure fluctuations on the tower to the tonal blade-passage noise, which was validated with experimental measurements.
In recent years, CFD-based fluid–structure coupling has been applied
frequently for the investigation of wind turbines.
presented a framework of a wind turbine aero-servo-elastic simulation
including flexible blades and tower which allows the motion of all turbine
components. In their approach, controllers for torque and blade pitch are
included as well, and they focus their studies on the impact of FSI on
aerodynamic rotor loads, drive train dynamics, controllers and wake.
developed a coupling of the CFD code
FLOWer to the multi-body simulations (MBS) solver SIMPACK with the
capability to couple isolated wind turbine rotors.
Scope and objectives
A totally revised FLOWer–SIMPACK coupling is revealed in the present
paper with the potential to take into account more degrees of freedom, like
tower deformation or changes in rotational speed in the structural model and
their impact on aerodynamics and aeroacoustics, respectively. Together with
the already existing process chain, fully coupled CFD simulations under
realistic turbulent inflow conditions can be conducted, providing both
airborne and structure-borne emissions simultaneously. A FW-H in-house code
is applied to calculate acoustic pressure at distant observers while
tower base loads represent the structure-borne emission. The aim of the
present paper is to identify the sources of low-frequency emissions and to
investigate the impact of the complexity of the numerical model on the
calculated low-frequency emissions from a generic 5MW wind
turbine. The complexity of the model is increased from a rotor only
simulation with uniform inflow to a coupled simulation including blade, tower
and foundation dynamics with turbulent atmospheric boundary layer. The
spectra of tower base loads and SPLs for seven cases overall
are compared in a frequency range from 0.1 to 25Hz for
evaluation.
Numerical process chain
A high-fidelity process chain based on multiple solvers is established for
the investigation of low-frequency emissions from wind turbines. It consists
of the CFD solver FLOWer, the MBS solver SIMPACK and the FW-H
solver ACCO. A coupling between FLOWer and SIMPACK was
developed to generate high-fidelity time series of surface pressure
distribution on the turbine and structural loads (forces and moments) acting
on the foundation of the turbine. Using the CFD results, the aeroacoustic
signal at distant, predefined observer positions is computed by means of
ACCO.
CFD solver
FLOWer is a compressible, dual time-stepping, block structured
Reynolds-averaged Navier–Stokes (RANS) solver developed by the German Aerospace
Center (DLR) . The use of independent grids for
bodies and background is enabled by the overlapping grid technique
CHIMERA, one of FLOWers' main features. The solver is
continuously extended at the Institute of Aerodynamic and Gas Dynamics (IAG)
regarding functionality and performance, including, amongst others, the
higher-order finite-difference weighted essentially non-oscillatory (WENO)
scheme , Dirichlet boundary condition to apply
arbitrary unsteady inflow, a body forces approach to superimpose
turbulence and various detached-eddy simulation (DES)
schemes . The capability of FLOWer for wind
turbine simulations has been shown in several projects. The interaction of a
wind turbine in complex terrain with atmospheric turbulence was investigated
by and code to code comparisons were
recently conducted in the European AVATAR
project .
MBS solver
SIMPACK is a commercial nonlinear MBS solver that can be applied to
simulate dynamic systems consisting of rigid and flexible bodies. Flexible
turbine components like tower and blades are modeled with linear or nonlinear
beam theory. The kinematics between the components are defined by joint
elements and internal forces can be considered. There are two ways to apply
external forces such as aerodynamic forces: either by built-in interfaces or
by programmable user routines. Controllers can also be integrated.
SIMPACK has been recently applied by industry and research groups for
the simulation of wind turbines. Examples can be found
in and .
Fluid–structure interaction
To take the influence of unsteady structural deformation on the aerodynamics
into account, a revised coupling between FLOWer and SIMPACK is
implemented. The new approach generally allows the coupling of slender beam-like
structures and is not limited to rotor blades or even wind turbines. Combined
coupling of rotating and non-rotating parts can be applied and the
deformation of adjacent structures is considered. Furthermore, coupling is
not restricted to flexible deformations but rigid-body motions
(rotations and translations) can also be realized. In the application to wind
turbines, pitch motions and changes in rotational speed of the rotor can
be transferred from the MBS solver to the CFD solver.
For the technical realization, an existing interface that was developed to
couple SIMPACK with the fluid solver ANSYS CFX for the
investigation of a tidal current turbine is
extended. Furthermore, libraries for grid deformation and load integration
which have recently been developed and integrated into
FLOWer are extended
for the coupling with SIMPACK. Without restrictions in functionality,
the setup of the coupling is kept simple and the dependencies between MBS
and CFD models are low. Thus, the resolutions of the CFD and MBS models are independent
of each other, which allows a fast and easy adjustment and replacement of MBS
structures or CFD meshes. Furthermore, the new coupling can be restarted,
allowing much longer simulation times if FLOWer runs on clusters with
limited job duration. It was already successfully applied to the blade of a
generic 10MW turbine for comparison reasons by
, who implemented a coupling of FLOWer to the
structural dynamics solver Carat++.
Explicit coupling scheme of the FLOWer–SIMPACK coupling.
General functionality
The developed coupling is a partitioned approach, where two independent
solvers run simultaneously on different machines and exchange data via a
Secure Shell (SSH) connection at discrete positions, so-called markers. The
markers are positioned inside the bodies. While rigid bodies only have one
marker, flexible bodies like rotor blades have several markers that are
distributed along the beam. On the one hand, deflections and rotations of
these markers relative to their non-deformed position are computed by
SIMPACK. On the other hand, aerodynamic forces and moments acting on these
markers are calculated in FLOWer. For each structure that is coupled, a
communication coordinate system is defined that has to be in the same
position and same orientation in both models at all times. It does not have
to be fixed but can be rotating or translating in a predefined way. All data
concerning the respective structure is communicated in this coordinate
system.
Mesh deformation
The task of the deformation library implemented in FLOWer is to apply
the deformations of the markers on the corresponding CFD surfaces and to
deform the surrounding volume mesh accordingly. The surface is represented by
a point cloud which is generated from the CFD mesh. For rigid structures only
one marker is used and all surface cloud points perform a rigid-body motion
based on the translation and rotation of this marker. A cubic spline
interpolation is applied for the mapping of flexible structures (beams)
consisting of more than one marker. The deformation of each surface cloud
point is then realized as rigid-body motion based on the corresponding
positions along the beam. While a complete spline approach is used for the
deflections, taking the rotation at the end points into account, the
rotations and the non-deformed marker positions are interpolated using
natural splines. A similar approach has been presented by
. Finally, the volume grids are deformed based on
the deformation of the point cloud using radial basis functions. To ensure
correct overlapping of deformed meshes, holes associated with the deformed
surface can also be deformed.
Load integration
The load library implemented in FLOWer
enables the calculation of aerodynamic loads on grid surfaces by the integration of friction and pressure over the cell faces. This is also necessary for the
coupling to SIMPACK, as there is no surface in the structural model
and the aerodynamic forces have to be mapped to the discrete marker
positions. For this purpose, the CFD surface is divided into segments based
on the deformed marker positions. For each of these segments, loads are
integrated and afterwards assigned to the respective markers. Moments are
calculated with respect to the origin of the corresponding communication
coordinate system. For structures with only one marker, loads are integrated
over the whole CFD surface of the respective structure.
Communication interface
The communication is realized by means of files. Data files contain
deformations or loads and status files indicate that the data file is ready
to be read. While SIMPACK is running on a local Windows machine,
FLOWer is usually executed in parallel mode on a high-performance
computing (HPC) system running on Linux. A portable communication script in
Windows' inherent scripting language PowerShell enables fast and reliable
communication between the two solvers. The Linux machine is accessed using a
SSH connection via the Windows Secure Copy (WinSCP) client.
Coupling scheme
In the presented work, an explicit coupling scheme is applied. The size of
the coupling time step is equal to the physical FLOWer time step and
remains constant throughout the simulation. Both solvers run in a
sequential way, waiting for the other solver to reach the next time step and
to send communication data. SIMPACK runs one time step ahead
doing time integration with the aerodynamic loads that FLOWer computed
at the end of the previous time step (Fig. ).
Acoustic solver
Acoustic pressure at arbitrary observer locations is calculated by means of
the in-house FW-H solver ACCO. Pressure and velocities on surfaces
enclosing the noise sources are evaluated at each time step of the transient
CFD solution, including velocities due to the deformation, translation and
rotation. For the present study, the surfaces used for the acoustic analysis
are identical with the physical surfaces of the turbine (rotor, tower, hub, etc.). Volume sources generated by free-flow turbulence are neglected, which
is justified for low Mach number flow because quadrupole volume noise is
proportional to Ma7. This approach was validated for a rod–cylinder
configuration and an airfoil in turbulent
flow . The acoustic monopole
and dipole contributions to the observer sound pressure level (SPL) are
computed by means of the FW-H equation. Its
left-hand side is the wave equation which describes the transmission of sound
to the observer, presuming undisturbed propagation and observers located in
the acoustic far field. Hence, ground reflections and nonlinear propagation
due to atmospheric layering and turbulence are not taken into account. The
acoustic far field is defined by the presence of a fully developed wave front
and thus starts several wave lengths away from the source. Parallel execution
of ACCO allows the computation of noise carpets consisting of several
thousand observer locations.
The application of the FW-H analogy allows the evaluation of the contribution of
selected components of the wind turbine to SPL by excluding surfaces of
particular components (e.g., tower) from the analysis.
Computational setupThe turbine
The examined turbine is based on the
generic 5 MW turbine developed by the National Renewable Energy Laboratory (NREL;
) and was
slightly modified in the OFFWINDTECH
project . The main modifications concern
the rated conditions which were changed to a rotational speed of
11.7RPM and a pitch angle of -2.29∘ at a wind speed at
hub height of 11.3ms-1. The turbine is investigated at rated
conditions in an onshore configuration with a hub height of 90m, a
rotor diameter of 126m with a tilt angle of 5∘ and a
pre-cone angle of 2.5∘. The original tower with a bottom diameter
of 6m and a top diameter of 3.87m is used.
CFD surface mesh, showing the connection of hub, blades and nacelle with overlapping meshes.
CFD model
The CFD model of the OFFWINDTECH turbine consists of 10 independent body meshes, which are embedded in a Cartesian hanging grid node
background mesh using the CHIMERA technique. Blades, hub, nacelle and
tower are considered in the simulation with fully resolved boundary layer
(y+≤1). No gaps are left between the components of the turbine, as
blade–hub connectors and a hub–nacelle connector are included in the CFD mesh
(Fig. ). Blades are meshed in a C-H mesh topology with
120 cells in radial direction and 180 cells around the airfoil, summing
up to approximately 5.3 million cells per blade. Two different Cartesian
background grids with hanging grid nodes are used. One for the case with
prescribed atmospheric turbulence where the mesh is additionally refined to a
cell size of 1m3 upstream of the turbine (64.5 million cells)
and another for the case without atmospheric turbulence where only the mesh
close to the turbine is refined (20.8 million cells). The computational
domain is approximately 48.8 rotor radii (R) long (12.7R upstream of
the rotor plane), is approximately 24.4R wide and has a height of
approximately 16.2R. According to a previous study using
FLOWer , the background grids expand more
than sufficiently in all directions to avoid influencing the flow field around
the turbine. Overall, the fine setup consists of 86 million cells and the coarse setup of 42 million cells.
Concerning inflow, three different cases are regarded in the present study.
Uniform inflow, steady atmospheric boundary layer and turbulent atmospheric
boundary layer. An exponent of 0.19 is applied for the power law profile
describing the steady atmospheric boundary layer, keeping the wind speed at
hub height at 11.3ms-1. Atmospheric turbulence with a reference
length scale of 42m, created using Mann's
model , is introduced into the flow field using body
forces 16m downstream of the inlet, superimposing the steady
boundary layer profile. The resulting turbulence level at the turbine
position is 16%. Unsteady RANS (URANS) simulations are applied with a
second-order dual time-stepping scheme for temporal discretization. The
second-order central discretization with the Jameson–Schmidt–Turkel (JST)
artificial dissipation term is used for spatial discretization in body
meshes, and the fifth-order WENO scheme is applied to the background mesh in order to
reduce the dissipation of vortices. Menter's shear stress transport (SST) model is deployed
for turbulence modeling. A physical time step corresponding to
0.75∘ azimuth (≈0.01068s) with 100 inner
iterations is applied for the evaluated part of the simulations.
Structural model
The SIMPACK model of the OFFWINDTECH turbine was built
by . The blades are modeled nonlinearly by using
multiple flexible bodies per blade. The structural properties of the tower
are adopted from the NREL 5MW turbine
taking 20 modes into account. Hub and nacelle
are defined as rigid bodies. The foundation is modeled as a rigid body
connected to the ground with a spring–damper system. Details can be found in
Table .
Details on the foundation of the wind turbine, similar to .
Overall, 160 markers are used for the fluid structure coupling of the
OFFWINDTECH turbine (Fig. ), 49
markers for each blade, 11 markers for the tower, and 1 marker each for the nacelle and hub.
Since in the structural model and the CFD model a fixed
rotational speed is prescribed, a rotating communication coordinate system in
the center of the hub is used for the rotating parts. The communication for
tower and nacelle is performed in a fixed coordinate system placed at the
tower base (Fig. ). In the SIMPACK model of
the turbine, additional rigid bodies are created for the definition of the
undeformed markers. The corresponding moving markers are attached to the
flexible structures of the turbine. With this approach, the measured
deformations between deformed and undeformed markers are composed of flexible
deformations of the body itself plus rigid-body motion due to the deformation or
motion of the adjacent body.
CFD surface of turbine including markers for coupling with
SIMPACK. Rotating hub coordinate system is shown in blue and tower
base coordinate system in red.
Simulation cases
In Table all regarded simulation cases are listed. For
evaluation they are assigned to three studies. In the first study, no FSI is
considered and thus all turbine components are kept rigid. The influences of
the presence of the tower and the distance of the blade to the tower are
evaluated at uniform inflow conditions by comparing LC1, LC2 and
LC2_FSC1SD. In case LC2_FSC1SD, the blade deformation is equal
to the averaged blade deformation of case LC2_FSC1 to obtain a
realistically deformed shape of the blades with reduced distance between
blades and tower. In a second study the degrees of freedom of the structural
model are increased at uniform inflow conditions. Three cases are compared:
the rigid case with steady deformed blades (LC2_FSC1SD), a case with
flexible blades (LC2_FSC1), and a case with flexible blades as well as
a flexible tower and foundation (LC2_FSC3). In the third study, the
inflow conditions are varied, keeping the structural model the same. Case
LC2_FSC3 is used as reference. A steady atmospheric boundary layer
(ABL) is prescribed at the inlet by means of a power law inflow profile in
case LC3_FSC3. This steady ABL is superposed with velocity
fluctuations modeling a turbulent atmospheric boundary layer in the case of LC4_FSC3.
Evaluation
The aim of the simulation chain is to model airborne and
structure-borne emissions simultaneously by evaluating SLPs at
distant observers and load fluctuations at the tower base. In the
fluid–structure coupled simulations tower base loads are evaluated directly
in the structural model at the interface between tower and foundation,
whereas in the non-coupled simulations aerodynamic loads are computed from
CFD results. In both cases the tower base loads are presented with respect to
the tower base coordinate system which is shown in
Fig. . The temporal resolution of the data is equal
to the coupling time step. To achieve the same temporal resolution in the
acoustic emission, each time step a CFD surface solution is saved temporally
as input for the acoustic simulations.
Observer positions for the evaluation of aeroacoustic emissions. Tower
base coordinate system shown in red. View from above; turbine in the center; wind from left.
Acoustic simulations using ACCO are conducted to calculate the
acoustic pressure at a carpet of observers on the ground surrounding the turbine.
Figure shows the 3600 observers located on 20
concentric rings around the turbine at radial positions of 100 to
2000m with a radial resolution of 100m and a
circumferential resolution of 2∘. Unweighted SPL is calculated from
sound pressure time series at the observers with a reference sound pressure
of 20µPa. The sound propagation and directivity for discrete
frequencies can be evaluated by plotting the SPL contour on the ground. Four
observers at a distance of 1000m from the turbine are chosen for a detailed evaluation of SPL spectra (large dots in
Fig. ). Prior to frequency analyses by means of fast
Fourier transform (FFT), the time series signals of loads and sound pressure
are cut to multiples of one rotational period of the turbine in order to
supply a preferably periodical signal to the FFT and to avoid the influence of
start-up effects. In coupled simulations, the first two revolutions are
excluded from evaluation. For case LC4_FSC3 14 revolutions and for
all other cases, eight revolutions are evaluated. As the sampling rate is equal
to the physical time step of the simulation, the highest resolved frequency
(Nyquist frequency) is 46.8Hz.
ResultsRigid simulations
In this section three non-fluid–structure coupled cases are compared at
uniform inflow conditions. As reference the rotor only case (LC1) is regarded
where unsteady effects on the loads only result from the tilt of the rotor,
the proximity to the ground and unsteady flow separation. In a second case,
the tower is considered (LC2), and in a third case steady deformation is
applied to the blades (LC2_FSC1SD). The CFD surfaces of all three
cases are shown in Fig. .
CFD turbine surfaces of cases LC1 (a), LC2 (b) and
LC2_FSC1SD (c). Snapshot with one blade in front of the tower at
180∘ azimuth.
Spectra of aerodynamic loads with respect to tower base (moment reference
point) for cases LC1, LC2 and LC2_FSC1SD.
Tower base loads
In the non-fluid–structure coupled cases, no unsteady structural forces occur
as all structures are rigid. Thus, load fluctuation only arises from
aerodynamics. Figure shows the spectra of
Mx and My of all three cases with respect to the tower base coordinate
system (moment reference point). No distinctive peaks can be found in the
spectra of LC1. After including the tower in the simulation (LC2), sharp
peaks at the blade-passing frequency and its higher harmonics appear with
significantly increased amplitudes up to a frequency of approximately
10Hz. Regarding Mx, a general increase in the amplitudes below
BPF is present with a peak at approximately 0.3Hz caused by vortex
shedding, which will be shown later. In LC2_FSC2SD the distance between
tower and blades is reduced due to the steady deformation of the blades. This
leads to an increase in the amplitudes at blade-passing harmonics. The
relative increase is stronger for higher frequencies. The amplitude of My
is increased by more than 50% for frequencies between 5 and
10Hz. For Mx the amplitude at BPF stays almost constant while
amplitudes are increased for the higher harmonics compared to case LC2. The
maximum amplitude of Mx is shifted to the second harmonic of BPF. The
amplitudes of Mz are much lower compared to the other load components and are therefore not shown.
The composition of the aerodynamic loads is investigated in detail for case
LC2_FSC1SD. Therefore, aerodynamic loads on rotor and tower were
evaluated separately with respect to the tower base coordinate system (moment
reference point). Figure shows the
resulting spectra. The peak amplitudes of the tower spectra are dominant over
the whole frequency range. Especially for Mx, the tower load amplitudes are
up to 10 times higher compared to the rotor load amplitudes. For Mx the
general level below BPF is higher in the tower load spectra. This can be
interpreted as the impact of unsteady flow separation at the tower induced by
vortex shedding. This phenomenon, known as von Kármán vortex street, leads
to unsteady forces on blunt bodies with a frequency described by the
dimensionless Strouhal number. Assuming an inflow velocity of
8ms-1 (reduced due to induction of the rotor) results in a
Reynolds number of 2.8×106 with respect to the mean diameter of the
tower (4.9m). The corresponding Strouhal number of approximately 0.24
leads to a theoretical vortex shedding frequency of 0.38Hz. As
both diameter and inflow velocity are not constant over the length of the
tower and inflow is disturbed by the rotor, a broader range of vortex
shedding frequencies can be expected as it is present in the spectrum of
Mx.
The surface pressure amplitudes on the tower are displayed in
Fig. at two different frequencies. At BPF
(0.585Hz) as well as at 0.292Hz where the spectra of
Mx have a local maximum. A strong peak appears at BPF at the front of the
tower shifted to the side of the approaching blade. The symmetric shape of
the pressure amplitude distribution and the higher amplitudes at the rear
side of the tower at 0.292Hz can very likely be associated with
vortex shedding creating the peak in the load spectra. These observations
support the idea of the superposition of blade-passing effects and vortex
shedding at the tower.
Spectra of aerodynamic loads with respect to tower base (moment
reference point) for case LC2_FSC1SD. Comparison of loads on rotor,
tower and all surfaces.
Pressure amplitudes on CFD tower surface of case LC2_FSC1SD
at 0.292Hz(a) and blade-passing frequency (0.585Hz) (b).
Aeroacoustic emission
Figure shows the
spectra of the SPL for observers C and D for the cases LC1, LC2 and
LC2_FSC1SD. The spectrum at observer A is very similar to the one at
observer C. The same applies to observers B and D. The maximum SPL for LC1,
the case without a tower, occurs at observer B at BPF and is the only prominent
peak. The emission at this frequency shows a strong directivity, as the
amplitude is much higher at the sides than upstream and downstream of the
turbine. The presence of the tower (LC2 and LC2_FSC1SD) causes a
massive increase in amplitudes at the BPF harmonics while the broadband noise
level stays low. The highest peak appears upstream of the turbine at observer C
at the third BPF harmonic and is approximately 4dB higher in case
LC2_FSC1SD compared to case LC2. The spectra of case LC2 show only a
weak directivity for the BPF harmonics as the amplitudes at the upstream and
downstream observers are just slightly lower than at the side observers. A
stronger directivity can be observed for case LC2_FSC1SD at BPF where
the amplitudes are clearly higher at the upstream and downstream observer.
Compared to case LC1 the SPL at frequencies below BPF also rises but only at
observer positions B and D. Comparing LC2_FSC1SD to LC2, the increase in amplitudes due to reduced blade–tower distance is most prominent between
the 5th and 10th harmonic of BPF where it amounts to more than
10dB. The SPL peaks drop below 20dB at around
15Hz even for case LC2_FSC1SD.
Spectra of unweighted SPL (reference sound pressure of 20µPa)
at two observer positions on the ground with a distance of
1000m from the turbine for cases LC1, LC2 and LC2_FSC1SD.
To examine the aeroacoustic noise emission in detail, the noise emission
originating from tower and rotor surfaces are evaluated separately for case
LC2_FSC1SD. Figure shows the SPL
spectra at observer positions C and D. It can be seen that for all BPF
harmonics the calculated SPL emitted by the tower is higher than the one
emitted by the rotor. The global maximum of the rotor-induced SPL is
about 8dB lower compared to the global peak of the tower-induced
SPL; both occur at observer C. The emission from the rotor shows a
strong directivity to the upstream and downstream direction, with clearly
lower amplitudes at observers B and D. At BPF, the emission of the tower
shows the same directivity but is less pronounced, whereas the directional
differences at higher harmonics of BPF are marginal. The SPL increase in the
plane of rotation for frequencies below BPF is mainly caused by the tower
emission. This is similar to the increase in amplitudes in the tower base
load spectra for Mx caused by pressure fluctuations on the tower surface,
which is described in the previous section. Thus, SPL increase at frequencies
below BPF is very likely induced by surface pressure fluctuations due to
vortex shedding at the tower, too. Looking at the noise carpet for the third
BPF harmonic in Fig. gives more
insight into the directivity. The rotor emission is strongly directed towards
20 and 190∘, whereas for the tower emission only a small shift in
the generally concentric shape towards 220∘ is present. The
superposed signal shows a directivity towards 180/350∘ and is
slightly biased upstream. The result also shows that the shape of the SPL
isolines beyond approximately the 500m radius around the turbine
is independent of the radius. The same behavior can be observed for the other
harmonics of BPF. Thus, the previously regarded observers at the
1000m radius are clearly out of near-field effects for BPF
harmonics.
Spectra of unweighted SPL (reference sound pressure of 20µPa)
at two observer positions on the ground with a distance of
1000m from the turbine for case LC2_FSC1SD. Comparison of
noise emitted from rotor, tower and all surfaces.
Unweighted SPL (reference sound pressure of 20µPa) at
third BPF harmonic (1.755Hz) on the ground around the turbine for case
LC2_FSC1SD. Aeroacoustic emission from rotor (a), tower (b)
and all surfaces (c). ΔSPL between black contour lines is
2dB.
Influence of degrees of freedom at uniform inflow
In the second study, the cases LC2_FSC1SD, LC2_FSC1 and
LC2_FSC3 are regarded. The aim is to evaluate the influence of the
degrees of freedom of the structural model on the low-frequency emissions
from the wind turbine. Case LC2_FSC1SD has zero degrees of freedom
but considers the mean blade deformation of case LC2_FSC1 where only
the rotor blades are flexible; thus, it is chosen as reference case for this
study.
Tower base loads
The spectra of the tower base loads for all three cases are plotted in
Fig. . The flexibility of the rotor blades in
case LC2_FSC1 mainly has an impact on the amplitudes at harmonics of
BPF. Mx amplitudes increase with the highest peaks at the first and second
harmonic of BPF rising by more than 30% compared to case
LC2_FSC1SD. By contrast, a decrease is observed for My, especially
for the second and third harmonic of BPF.
Spectra of tower base bending moments for the cases LC2_FSC1SD, LC2_FSC1 and LC2_FSC3.
There are two effects which go hand in hand, both having an influence on the
tower base loads. When considering the flexibility of the blades, on the one hand,
gravitational forces and inertial forces start acting and, on the other hand,
aerodynamic forces change due to unsteady deflection of the blades. The mean
blade tip deflection applied in case LC2_FSC1SD is 6.34m
out of plane (OOP) and -0.58m in plane (IP). In case
LC2_FSC1 the OOP deflection reaches its maximum of approximately
6.46m when the blade is passing the tower, just before the blade
deformation is reduced due to the tower blockage. The IP deflection
oscillates between -0.13 and -1.02m, which is mainly caused by
the gravitational force that makes the blade bend downwards. Due to the
inertia of the blade, the IP blade tip velocity reaches its maximum just
after the tower passage. This increases the absolute velocity of the blade
when passing the tower and the relative flow velocity on the blade. On the
other hand, the swinging of the blades mainly induces structural forces in
y and z direction, which explains the increase in Mx amplitudes at
BPF.
The enabled flexibility of the tower in case LC2_FSC3 shows a much
stronger impact on the tower base loads compared to case LC2_FSC1 as
it significantly changes the structural eigenmodes of the turbine. In Mx
and My, the amplitudes at first, second and third harmonics of BPF are
clearly reduced. Especially the reduction at BPF is remarkable: over 70%
for both loads. For Mx the amplitude at BPF even drops to the level of the
broadband fluctuations of the other two cases. For My the maximum
amplitude shifts to the fifth harmonic of BPF, which is close to three
structural eigenfrequencies of the turbine. For Mx it occurs at
approximately 0.32Hz, which matches the first side–side bending
mode of the tower. An increase in the amplitudes in the frequency range
around 0.32Hz can also be observed for My but is less
pronounced. The first fore–aft bending mode is also at this frequency, but
the aerodynamic damping is much higher compared to the side–side direction.
Aeroacoustic emission
The increase in degrees of freedom in the structural model only marginally
influences the SPL at the observers. The spectrum at observer position C
shows a small decrease in the amplitude at BPF while there is a small
increase at second to sixth harmonics of BPF. However, observer D shows a
small increase at BPF while amplitudes of higher harmonics are almost
unchanged. Generally, the effect is a bit stronger for case LC2_FSC3.
These small changes might be an impact of the slightly reduced blade–tower
distance and the increased blade tip velocity when the blade passes the
tower, which is reported in the previous section. For frequencies below BPF,
the maximum amplitude increases slightly, which could be induced by the
structural eigenmodes of the turbine as well as by the impact of vortex
shedding at the tower.
Influence of inflow
In the last study the influence of inflow conditions on the tower base loads
and on the aeroacoustic emission is investigated. While uniform inflow is
applied for the previous studies, more realistic inflow is considered in this
study. Two cases – one with vertically sheared inflow (LC3_FSC3) and
one with turbulent vertically sheared inflow (LC4_FSC3) – are
compared to the uniform inflow case (LC2_FSC3). For the turbulent
inflow case, a longer time series is evaluated in order to obtain more
representative results.
Tower base loads
The spectra of tower base loads in Fig. show
that for case LC3_FSC3 an increase in amplitudes is only present for
My at BPF. Amplitudes at higher harmonics of BPF tend to reduce for Mx
and My. The result also shows that the broadband load level at frequencies
between the first and fifth BPF harmonics rises. For Mx there is a clear
peak just above 1Hz, which even exceeds the peak at BPF. The
reduction in amplitudes at higher harmonics of BPF can be explained as a
result of the reduced inflow velocity below hub height due to the power law
profile. Because of the lower aerodynamic thrust in this region, OOP
deflection in front of the tower reduces to approximately 5.5 compared to
6.46m in case LC2_FSC3. The rise of amplitudes at BPF can
be explained as an effect of vertical shear. While blade passing is a short
pulse and many higher harmonics of BPF are excited, the effect of vertical
shear stretches over the whole revolution and is much closer to a sine
function. Thus, the excitation of higher harmonics of BPF is much weaker
compared to blade passing. The combination of vertical shear and reduced
blade-passing effect finally leads to an increase in amplitudes at BPF while
amplitudes at higher harmonics decrease.
Spectra of tower base bending moments for the cases LC2_FSC3, LC3_FSC3 and LC4_FSC3.
By superimposing turbulence on the vertically sheared flow in case
LC4_FSC3, the character of the spectra changes as the amplitudes at
BPF harmonics become much less prominent. There are some clear peaks
remaining, but the broadband load level massively increases. The global
maximum now arises for My at approximately 0.32Hz,
corresponding to an eigenmode of the structural model. Additionally the
amplitude at BPF is strongly increased for Mx and My; however, side
peaks occur that are partially even higher. The amplitude at approximately
1Hz further increases compared to case LC3_FSC3, and
another wide peak appears at frequencies around approximately
2.75Hz, which again corresponds to nearby structural eigenmodes.
The higher amplitudes at frequencies near structural eigenmodes can be
explained by the broadband excitation due to the influence of turbulent
inflow on the aerodynamic loads. Without turbulent inflow the main excitation
occurs at BPF harmonics because all unsteady effects except for the vortex
shedding are periodic with BPF (blade–tower interaction, tilt angle,
vertical shear).
Aeroacoustic emissions
Figure shows the spectra of the acoustic
spectra of the SPL at observers C and D for the regarded cases. The vertically sheared
inflow (case LC3_FSC3) leads to a slight decrease in SPL at BPF
harmonics with a stronger effect at higher frequencies. Only a small increase in amplitude can be observed at BPF for observer D. For observer C an
increase in the broadband noise level between approximately 2
and 10Hz can be found, but it does not exceed 30dB. The
reduction in SPL can be explained with the reduced blade tip deflection in
front of the tower already mentioned above, which reduces the pressure
fluctuations on the tower.
Spectra of unweighted SPL (reference sound pressure of 20µPa)
at two observer positions on the ground with a distance of
1000m from the turbine for cases LC2_FSC3, LC3_FSC3
and LC4_FSC3.
Taking the turbulent inflow into account (case LC4_FSC3) leads to an
increase in the broadband noise level due to turbulent inflow noise,
generated by the interaction of the rotor blade with the turbulence. The
inflow noise is emitted from the rotor and predominantly directed in upstream
and downstream direction, leading to higher broadband noise levels at
observer C compared to observer D. Since the rotor blades encounter the
turbulence at considerably higher relative velocity than the tower, the
emission from the tower hardly increases compared to case LC3_FSC3.
However, despite the increased broadband noise level, the peaks at BPF
harmonics are still dominant at both observer positions.
Discussion
In the first study the influence of the presence of the tower and of steady
blade deformation on low-frequency emissions is evaluated at uniform inflow
conditions in stand-alone CFD simulations. Concerning the aerodynamic loads,
the presence of the tower leads to an increase in amplitudes at BPF and its
higher harmonics. Applying a steady deformation to the rotor blades further
increases the amplitudes especially for higher harmonics due to the stronger
blade–tower interaction. Splitting the loads up into rotor and tower loads
shows that the major part of the fluctuations originates from the tower and
is caused by blade–tower interaction. Load oscillations induced by vortex
shedding can be observed but do not play an important role. Evaluating the
SPL on the ground at a distance of 1000m shows
similar results. Through the presence of the tower a tonal noise emission
with prominent peaks at BPF harmonics arises. Reduced blade–tower distance
further increases the amplitudes of BPF harmonics especially at higher
frequencies. Comparing the contributions of tower and rotor to the noise
emission shows a strong directivity for the rotor emission in the direction
of the rotor axis and a weak directivity for the tower emission except at
BPF. Generally the emission from the tower is stronger in all directions in
the regarded frequency range. This corresponds to the findings by
, who did research on blade-passage noise and
claimed a significant contribution of the tower. While
investigated a small model turbine with a symmetric blade in stationary air
and a BPF of 45Hz, the present study shows that their assumption
is also valid for a realistic multi-megawatt turbine under uniform inflow and
a BPF in the low-frequency range.
In a second study, the influence of degrees of freedom in the structural
model is investigated using three cases: one with steady blade deformation
already regarded in the first study, another with flexible blades, and a
third with additionally flexible tower and foundation. Flexible blades have
only a minor impact on the calculated tower base loads. Structural eigenmodes
play a more significant role in the third case when tower and foundation are
flexible too. The peaks at BPF harmonics are still prominent, but the
amplitudes change and the maxima are shifted towards BPF harmonics close to
structural eigenfrequencies. Additionally, peaks corresponding to the first
bending modes of the tower (0.32Hz) occur, being dominant in the
spectrum of Mx. Concerning aeroacoustics, the emission slightly increases
but no clear influence of structural eigenmodes can be found in the regarded
frequency range.
The third study deals with the influence of the inflow condition on the
emissions. Uniform inflow is compared to vertically sheared inflow with and
without turbulence. For vertical shear inflow, tower base loads tend to
increase at BPF and decrease at higher harmonics of BPF. With superimposed
turbulence, the peaks become much less prominent since the broadband load
level rises. Amplitudes at frequencies close to structural eigenmodes rise,
and BPF harmonics become less dominant in the spectra. The tonal noise level
of the aeroacoustic emission tends to reduce slightly with the vertical shear
and increase again due to the superimposed turbulence. The broadband noise
level strongly increases, especially for observers upstream and downstream of
the turbine, which is mainly caused by turbulent inflow noise emitted by the
rotor. Thus, the BPF harmonics become less prominent but are still dominant
in the spectra.
As a generic wind turbine is investigated, no measurements for validation are
available. Nevertheless, a qualitative comparison between the presented
results and two studies found in the literature is drawn.
showed seismic measurements in Germany that
suggest an independence of discrete frequency peaks and blade-passing
frequency. Although the amplitudes increase with increasing wind speed and
rotational speed, the frequencies of the peaks do not change. This can be
interpreted as a dominance of structural eigenmodes of the turbine in the
origin of the seismic waves. However, at high (rated) rotational speed the
dominant frequencies correspond very well to harmonics of the blade-passing
frequency. analyzed seismic measurements of a
gravitational wave observatory in Italy close to a wind farm and found steady
spectral lines as well as time-varying peaks which could all be identified as
emitted by a wind turbine. The results of both studies coincide with the
findings of the presented paper where tower base loads at BPF harmonics close
to eigenfrequencies of the turbine are prominent in the spectra. The tonal
character of the low-frequency noise was also shown in acoustic field
measurements . They showed
that the BPF harmonics are dominant in the measured spectra and thus the peak
frequencies shift depending on the rotational speed of the turbine.
furthermore compared measurements of a single 200kW turbine to
estimated SPL from the Viterna method . They
found an underestimation of SPL which they explained with environmental
conditions neglected in the model. Taking the present study into account, it
is more likely that the neglect of tower emission in the Viterna method has a
major impact on the results.
Despite the advanced modeling approach applied in the presented study, there
are still several limitations that have to be mentioned. In the applied FW-H
calculations, effects of unsteady flow field, refraction and reflection of
acoustic waves and atmospheric layering are not taken into account for the
propagation. On the other hand, this makes the method very suitable for the
investigation of the aeroacoustic emission of the turbine, as the SPL
at the observer positions is not influenced by the effects mentioned above.
Due to the computationally expensive CFD approach, there are limitations
concerning the length of the time series and temporal resolution and
consequently the statistical convergence of the results and the resolved
frequency range. Although the flexibility of rotor blades, tower and
foundation is considered in the simulations, further degrees of freedom are
neglected. The drive train is kept totally rigid and at fixed rotational
speed. As SIMPACK is a MBS solver and only deformations of points
along a beam are transferred, eigenmodes of the shell cannot be considered in
the presented approach. However, the shortcomings mentioned do not change the
general findings of this paper.
Conclusions
In the present paper the low-frequency emissions from a generic
5MW turbine are investigated using a high-fidelity time-resolved
fluid–structure coupled CFD approach. Three different studies are conducted
to identify sources, to better understand mechanisms and to evaluate the
influence of the model complexity on the resulting emissions. Tower base
loads are compared to study the effect of structure-borne noise as seismic
wave propagation cannot be calculated with the presented method. The
aeroacoustic noise propagation is computed using a Ffowcs-Williams–Hawkings
method. To consider aeroelasticity in the simulations, a new coupling of the
CFD solver FLOWer to the MBS solver SIMPACK is presented in this paper.
With this method not only blade deformation can be taken into account, but
deformations, translations and rotations of all parts of the turbine. Thus,
fluid–structure coupled simulations with flexible tower and foundation could
be conducted.
A major advantage compared to lower-fidelity approaches is that, as all
geometries of the turbine are fully resolved, the unsteady pressure
distributions on all surfaces, and thus all aerodynamic loads, are a direct
outcome of the simulations. Regarding the aeroacoustic emission it is found
that the blade–tower interaction plays a key role and the noise emitted from
the tower is higher compared to the noise emitted from the rotor. Only an
indirect impact of fluid–structure coupling on the aeroacoustics could be
observed. Elastic blades reduce the distance between blade and tower and thus
increase the strength of the blade–tower interaction. Turbulent inflow on
the other side mainly influences the broadband noise level of the rotor. For
the regarded turbulence level of 16% the noise has a tonal character
with dominant peaks at blade-passing frequency harmonics.
Blade–tower interaction also has a great influence on the tower base loads;
however, with increasing degrees of freedom structural eigenmodes play a much
stronger role than for the aeroacoustic emission and amplitudes at
eigenfrequencies become more dominant when turbulent inflow is applied.
Nevertheless, blade-passing frequency harmonics can still be identified in
the spectra. For aerodynamic load fluctuations at uniform inflow, it is found
that the contribution of the tower exceeds the contribution of the rotor.
Several conclusions for the modeling of low-frequency emissions using CFD
simulations can be drawn from the conducted studies. The blade–tower
interaction is found to be the main source of aeroacoustic noise and triggers
a major part of the aerodynamic load fluctuations. The tower itself as well
as a realistic blade–tower distance has to be considered in the simulation
to capture the blade–tower interaction properly. Fluid–structure coupling
is the most appropriate way to a realistic blade–tower distance and is
mandatory if structural emission shall be regarded. Moreover, the acoustic
emission from the tower has to be considered in the noise evaluation and the
loads on the tower have to be included in the fluid–structure coupling.
Concerning the structural emission, it is not only the flexibility of the
rotor blades but also that of the tower and foundation that have to be taken
into account as they change the character of the tower base load spectra.
Turbulent inflow should also be taken into account because it enhances the
excitation of structural eigenmodes.
The findings can be transferred to any modeling method of low-frequency
emissions from wind turbines. The method has to be capable of capturing the
impact of blade passing not only on the blades but also on the tower and its
effect, on the one hand, on the aerodynamic load fluctuations and, on the
other hand, on the aeroacoustic noise emission.
Future work will deal with several of the listed limitations. A slightly
smaller commercial wind turbine will be investigated numerically with the
presented approach and field measurements will be available for comparison.
Subsequently, the turbine will be simulated taking into account the
operational conditions of the measurements. The influence of full shell
coupling on the low-frequency emission will be investigated in a future
study. Based on the presented findings, constructional measures such as
lattice towers, increased blade tower distance or swept blades are likely to
reduce low-frequency emissions and should be taken into account for future
research.
Data of the NREL 5MW turbine are available from
.
LK implemented the coupling, performed the CFD-MBS simulations and wrote
most of the paper. JG was responsible for the acoustic simulations and the turbulent
inflow and contributed parts of the manuscript. FW contributed parts of the manuscript.
TL and EK initiated the research, supervised the work and revised the manuscript.
The authors declare that they have no conflict of interest.
Acknowledgements
The studies were conducted as part of the joint research project “Objective
Criteria for Seismic and Acoustic Emission of Inland Wind Turbines (TremAc),
FKZ 0325839A”, funded by the German Federal Ministry for Economic Affairs and
Energy (BMWi). The authors are grateful for the financial support. The
authors gratefully acknowledge the High Performance Computing Center
Stuttgart for providing computational resources within the project
WEALoads.
Edited by: Alessandro Bianchini
Reviewed by: three anonymous referees
ReferencesArnold, M., Cheng, P. W., and Biskup, F.: Simulation of
Fluid-Structure-Interaction on Tidal Current Turbines Based on Coupled
Multibody and CFD Methods, in: The Twenty-third International Offshore and
Polar Engineering Conference, International Society of Offshore and Polar
Engineers,
available at: https://www.onepetro.org/conference-paper/ISOPE-I-13-101 (last access: 9 October 2018),
2013.
Bekiropoulos, D., Lutz, T., Baltazar, J., Lehmkuhl, O., and Glodic, N.:
D2013-3.1: Comparison of benchmark results from CFD-Simulation, Deliverable
report, KIC-OFFWINDTECH, 2013.Bozorgi, A., Ghorbaniasl, G., and Nourbakhsh, S.: The reduction in
low-frequency noise of horizontal-axis wind turbines by adjusting blade cone
angle, Int. J. Environ. Sci. Te.,
1–14, 10.1007/s13762-017-1639-x, 2018.Ghasemian, M. and Nejat, A.: Aerodynamic noise prediction of a horizontal Axis
wind turbine using improved delayed detached eddy simulation and acoustic
analogy, Energ. Convers. Manage., 99, 210–220,
10.1016/j.enconman.2015.04.011, 2015.Gortsas, T. V., Triantafyllidis, T., Chrisopoulos, S., and Polyzos, D.:
Numerical modelling of micro-seismic and infrasound noise radiated by a wind
turbine, Soil Dyn. Earthq. Eng., 99, 108–123,
10.1016/j.soildyn.2017.05.001, 2017.
Hansen, K. L., Zajamšek, B., and Hansen, C. H.: The Occurrence of
Nocturnal Wind Farm Rumbling Noise, 7th International Conference on Wind
Turbine Noise Rotterdam, 2–5 May 2017, Willem Burger Complex, De Doelen, Rotterdam, Netherlands, 1–11, 2017.
Illg, J., Lutz, T., and Krämer, E.: Aeroacoustic Simulation of an Airfoil
in Turbulent Inflow, in: 6th International Conference on Wind Turbine Noise,
Glasgow, 20–23 April 2015, Radisson Blu Hotel, 301 Argyle Street, Glasgow G2 8DL, UK, 2015.Jassmann, U., Berroth, J., Matzke, D., Schelenz, R., Reiter, M., Jacobs, G.,
and Abel, D.: Model predictive control of a wind turbine modelled in
Simpack, J. Phys.-Conference Series, IOP
Publishing, 524, 1–11, 10.1088/1742-6596/524/1/012047, 2014.Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
reference wind turbine for offshore system development, Tech. rep., National
Renew. Energ. Lab.(NREL), Golden, CO, United States,
10.2172/947422, 2009.Knopper, L. D., Ollson, C. A., McCallum, L. C., Whitfield Aslund, M. L.,
Berger, R. G., Souweine, K., and McDaniel, M.: Wind Turbines and Human
Health, Frontiers in Public Health, 2, 63, 10.3389/fpubh.2014.00063,
2014.
Kowarsch, U., Keßler, M., and Krämer, E.: High order CFD-simulation
of the rotor-fuselage interaction, 39th European Rotorcraft Forum,
3–9 September, Moscow, 2013.Kranzinger, P. P., Kowarsch, U., Schuff, M., Keßler, M., and Krämer,
E.: Advances in parallelization and high-fidelity simulation of helicopter
phenomena, in: High Performance Computing in Science and Engineering, Springer International
Publishing,
15, 479–494,
10.1007/978-3-319-24633-8_31, 2016.Kroll, N., Rossow, C.-C., Becker, K., and Thiele, F.: The MEGAFLOW project,
Aerosp. Sci. Technol., 4, 223–237,
10.1016/S1270-9638(00)00131-0, 2000.Li, Y., Castro, A., Martin, J., Sinokrot, T., Prescott, W., and Carrica, P.:
Coupled computational fluid dynamics/multibody dynamics method for wind
turbine aero-servo-elastic simulation including drivetrain dynamics,
Renew. Energ., 101, 1037–1051, 10.1016/j.renene.2016.09.070, 2017.Liu, W.: A review on wind turbine noise mechanism and de-noising techniques,
Renew. Energ., 108, 311–320, 10.1016/j.renene.2017.02.034, 2017.Luhmann, B., Seyedin, H., and Cheng, P.-W.: Aero-structural dynamics of a
flexible hub connection for load reduction on two-bladed wind turbines, Wind
Energy, 20, 521–535, 10.1002/we.2020, 2017.Lutz, T., Arnold, B., Bekiropoulos, D., Illg, J., Krämer, E., Wolf, A.,
Hann, R., and Kamruzzaman, M.: Prediction of Flow-Induced Noise Sources of
Wind Turbines and Application Examples, Int. J.
Aeroacoust., 14, 675–714, 10.1260/1475-472X.14.5-6.675, 2015.Madsen, H. A.: Low frequency noise from wind turbines mechanisms of generation
and its modelling, J. Low Freq. Noise Vib., 29, 239–251, 10.1260/0263-0923.29.4.239, 2010.Mann, J.: The spatial structure of neutral atmospheric surface-layer
turbulence, J. Fluid Mech., 273, 141–168,
10.1017/S0022112094001886, 1994.
Matha, D., Hauptmann, S., Hecquet, T., and Kühn, M.: Methodology and
results of loads analysis of wind turbines with advanced aeroelastic
multi-body simulation, DEWEK, Bremen, 2010.Menter, F. R.: Two-equation eddy-viscosity turbulence models for engineering
applications, AIAA Journal, 32, 1598–1605, 10.2514/3.12149, 1994.Pilger, C. and Ceranna, L.: The influence of periodic wind turbine noise on
infrasound array measurements, J. Sound Vib., 388, 188–200,
10.1016/j.jsv.2016.10.027, 2017.Saccorotti, G., Piccinini, D., Cauchie, L., and Fiori, I.: Seismic noise by
wind farms: a case study from the Virgo Gravitational Wave Observatory,
Italy, B. Seismol. Soc. Am., 101, 568–578,
10.1785/0120100203, 2011.
Sayed, M., Lutz, T., and Krämer, E.: Aerodynamic investigation of flow over a
multi-megawatt slender bladed horizontal-axis wind turbine, in: Renewable
Energies Offshore, CRC Press, 773–780, ISBN 9781138028715, 2015.Sayed, M., Lutz, T., Krämer, E., Shayegan, S., Ghantasala, A., Wüchner,
R., and Bletzinger, K.-U.: High fidelity CFD-CSD aeroelastic analysis of
slender bladed horizontal-axis wind turbine, J. Phys. Conf.
Ser., 753, 042009, 10.1088/1742-6596/753/4/042009, 2016.Schepers, J., Ceyhan, O., Boorsma, K., Gonzalez, A., Munduate, X., Pires, O.,
Sørensen, N., Ferreira, C., Sieros, G., Madsen, J., Voutsinas, S., Lutz, T.,
Barakos, G., Colonia, S., Heißelmann, H., Meng, F., and Croce, A.: Latest
results from the EU project AVATAR: Aerodynamic modelling of 10 MW wind
turbines, J. Phys. Conf. Ser., 753, 022017,
10.1088/1742-6596/753/2/022017, 2016.
Schuff, M., Kranzinger, P., Keßler, M., and Krämer, E.: Advanced
CFD-CSD coupling: Generalized, high performant, radial basis function based
volume mesh deformation algorithm for structured, unstructured and
overlapping meshes, in: Proceedings of the 40th European Rotorcraft Forum,
Southhampton, Great Britain, 2014.Schulz, C., Klein, L., Weihing, P., and Lutz, T.: Investigations into the
Interaction of a Wind Turbine with Atmospheric Turbulence in Complex Terrain,
J. Phys. Conf. Ser., 753, 032016,
10.1088/1742-6596/753/3/032016, 2016a.Schulz, C., Meister, K., Lutz, T., and Krämer, E.: Investigations on the
wake development of the MEXICO rotor considering different inflow
conditions, in: New Results in Numerical and Experimental Fluid Mechanics X, Springer,
871–882, 10.1007/978-3-319-27279-5_76,
2016b.
Stammler, K. and Ceranna, L.: Influence of wind turbines on seismic records of
the Gräfenberg array, Seismol. Res. Lett., 87, 1075–1081,
10.1785/0220160049, 2016.
Streiner, S., Hauptmann, S., Kühn, M., and Krämer, E.: Coupled
fluid-structure simulations of a wind turbine rotor, in: Deutsche
Windenergie-Konferenz (DEWEK), Bremen, Germany, DEWI-German Wind Energy
Institute, 2008.Styles, P., Stimpson, I., Toon, S., England, R., and Wright, M.: Microseismic
and infrasound monitoring of low frequency noise and vibrations from
windfarms, Recommendations on the Siting of Windfarms in the Vicinity of
Eskdalemuir, Scotland, Report to MOD/FTI/BWEA, 125 pp.,
available at: https://www.keele.ac.uk/geophysics/appliedseismology/wind/Final_Report.pdf (last access: 9 October 2018), 2005.
Turnbull, C., Turner, J., and Walsh, D.: Measurement and level of infrasound
from wind farms and other sources, Acoust. Aust., 40, 45–50, 2012.Van den Berg, G.: The beat is getting stronger: the effect of atmospheric
stability on low frequency modulated sound of wind turbines, J. Low
Freq. Noise Vib., 24, 1–23,
10.1260/0263092054037702, 2005.Viterna, L. A.: The NASA-LERC wind turbine noise prediction code, NASA CP,
2185, available at: https://ntrs.nasa.gov/search.jsp?R=19820015854 (last access: 9 October 2018), 1981.Weihing, P., Letzgus, J., Bangga, G., Lutz, T., and Krämer, E.: Hybrid
RANS/LES Capabilities of the Flow Solver FLOWer – Application
to Flow Around Wind Turbines, in: Progress in Hybrid RANS-LES Modelling, Springer International Publishing,
369–380,
10.1007/978-3-319-70031-1_31, 2018.Yauwenas, Y., Zajamšek, B., Reizes, J., Timchenko, V., and Doolan, C. J.:
Numerical simulation of blade-passage noise, The Journal of the Acoustical
Society of America, 142, 1575–1586, 10.1121/1.5003651, 2017.Zajamšek, B., Hansen, K. L., Doolan, C. J., and Hansen, C. H.:
Characterisation of wind farm infrasound and low-frequency noise, J.
Sound Vib., 370, 176–190, 10.1016/j.jsv.2016.02.001, 2016.Zieger, T. and Ritter, J. R.: Influence of wind turbines on seismic stations in
the upper rhine graben, SW Germany, J. Seismol., 22, 105–122,
10.1007/s10950-017-9694-9, 2018.