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Abstract and Figures

This study presents the integration of a flight simulation code (PSUHeloSim), a high fidelity rotor aeromechanics model with free wake (CHARM Rotor Module), and an industry standard noise prediction tool (PSU-WOPWOP) into a comprehensive noise prediction system. The flight simulation uses an autonomous controller to follow a prescribed trajectory for both steady and maneuvering flight conditions. The aeromechanical model calculates blade loads and blade motion that couple to the vehicle flight dynamics with suitable resolution to allow high fidelity acoustics analysis (including prediction of blade-vortex interaction (BVI) noise). The blade loads and motion data is sent to PSU-WOPWOP in a post-processing step to predict external noise. The coupled analysis is being used to evaluate the influence of flight path on aircraft noise certification metrics like EPNL and SEL for various rotorcraft in work for the FAA. The software was used to analyze the acoustic properties of a blade planform similar to the "Blue Edge" rotor blades developed by DLR and Airbus Helicopters-predicting BVI noise reduction as compared to more conventional blade geometries on the same order as that reported for the "Blue Edge" rotor.
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Rotorcraft Simulations with Coupled Flight Dynamics, Free Wake, and Acoustics
Umberto Saetti
M.S. Candidate
Joseph F. Horn
Kenneth S. Brentner
Willca Villafana
M.S. Candidate
Dan Wachspress
Senior Associate
Department of Aerospace Engineering
The Pennsylvania State University
University Park, PA, USA
Continuum Dynamics
Ewing Township, NJ,
This study presents the integration of a flight simulation code (PSUHeloSim), a high fidelity rotor aeromechanics model
with free wake (CHARM Rotor Module), and an industry standard noise prediction tool (PSU-WOPWOP) into a
comprehensive noise prediction system. The flight simulation uses an autonomous controller to follow a prescribed
trajectory for both steady and maneuvering flight conditions. The aeromechanical model calculates blade loads and blade
motion that couple to the vehicle flight dynamics with suitable resolution to allow high fidelity acoustics analysis (including
prediction of blade-vortex interaction (BVI) noise). The blade loads and motion data is sent to PSU-WOPWOP in a post-
processing step to predict external noise. The coupled analysis is being used to evaluate the influence of flight path on
aircraft noise certification metrics like EPNL and SEL for various rotorcraft in work for the FAA. The software was used
to analyze the acoustic properties of a blade planform similar to the Blue Edge” rotor blades developed by DLR and Airbus
Helicopters predicting BVI noise reduction as compared to more conventional blade geometries on the same order as that
reported for the “Blue Edge” rotor.
The integration of rotorcraft simulation software with
complex aeromechanical models can provide increased
fidelity and functionality of the system as compared to any
of the individual tools. Continued advancement in
computational resources allows coupled codes to be
executed efficiently and even in real-time. In 2006, the
GENHEL-PSU simulation code was integrated with the
CHARM free wake module and the coupled code was
shown to provide improved fidelity in flight dynamics.1
Real-time operation required limitations in the rotor wake
geometry, but with use of parallel computing and the steady
improvement in CPU performance these limitations can be
relaxed. Coupling of GENHEL-PSU with Navier-Stokes
CFD solutions has also been performed, with specific
application to simulation of ship airwake interactions with
the helicopter2. These simulations are still far slower than
real-time, but scaling studies have shown that with
massively parallel processing and reduced order CFD
models, real-time simulation and CFD coupling might be
possible in the near future.
GENHEL-PSU was also coupled with the acoustics
prediction software PSU-WOPWOP.3 This coupling was a
serial “one-way” coupling in that GENHEL-PSU
simulations first calculated the helicopter motion and blade
loads and then PSU-WOPWOP used this information to
predict the external acoustics. One-way coupled simulations
were reasonable since the acoustics have no impact on
aircraft dynamics. The simulations allowed predictions of
rotorcraft noise in maneuvers, whereas historically such
calculations were only performed in steady-state trimmed
flight. The limited fidelity of the blade loads predicted by
GENHEL-PSU meant that the acoustics prediction could
not account for Blade-Vortex-Interaction (BVI) noise.
However, subsequent work used a free-wake model to re-
construct more detailed blade loads for the prediction of
BVI4. The wake model was coupled “one-way” in that the
flight dynamics simulation was based on a simple blade
element rotor with finite-state inflow and was not affected
by the free wake. The free wake was used to re-construct
more detailed blade loads for use only in the acoustics
The prediction of noise in generalized maneuvering flight is
relevant in that it can be used to determine flight procedures
that minimize noise and impact on communities. This is of
particular interest to the Federal Aviation Administration,
who through the Aviation Sustainability Center of
Excellence (ASCENT), is seeking to develop noise
abatement procedures. Physics-based models are
particularly useful for noise prediction when no measured
data is available, such as for new rotorcraft designs and
configurations. To achieve these goals, the noise prediction
should be coupled with flight simulation codes that generate
realistic trajectories and pilot control input histories for
typical rotorcraft maneuvers. This could be done through
either real-time piloted simulations or through batch
simulations using an autonomous controller (that models a
pilot compensation to track a desired trajectory). In
addition, such simulations should be coupled with high
fidelity aeromechanical models that provide suitable blade
load and blade motion predictions for acoustics analysis
(including BVI), and these aeromechanical models should
be consistent with the total forces and moments acting on
the rotorcraft during the flight simulation. In this study, we
continue development of a comprehensive noise prediction
system5, that couples a flight simulation code
(PSUHeloSim), a high fidelity rotor aeromechanics model
with free wake (CHARM Rotor Module6), and an industry
standard noise prediction tool (PSU-WOPWOP7-9). All of
these tools are physics-based models that can be adapted to
predict flight dynamics, rotor loads, and noise on a variety
of rotorcraft configurations. In this paper, we present the
coupling of these codes and preliminary results showing
vehicle motion and noise prediction for steady flight
Helicopter Flight Dynamics Model
The flight dynamics simulations were performed using the
PSUHeloSim code. This is a basic simulation tool
developed at PSU to provide a generic rotorcraft flight
dynamics model for research and education. PSUHeloSim
is developed in the MATLAB/Simulink environment for
ease of development and adaptation to different rotorcraft
configurations. The simulation model is constructed in first
order state space form    , which makes it well
suited for numerical integration, trim, and linearization
calculations. It includes the 6 DoF non-linear equations of
motion of the fuselage, 2nd order rotor flapping dynamics,
and a 3-state Pitt-Peters inflow model, resulting in a 21-state
non-linear model. It uses a simple aerodynamic model of the
fuselage and empennage based on given lift and drag
properties. A static Bailey model is used for the tail rotor,
and while the main rotor includes flapping dynamics, it uses
linearized blade equations of motion and simplified analytic
integrations of the aero lift and drag forces along the blade.
The limitations in rotor model fidelity are not significant for
the current application, as the simple rotor model is replaced
with the high-fidelity CHARM (Comprehensive
Hierarchical Aeromechanics Rotorcraft Model) rotor
module in the final results. The simple rotor model is only
used in the trim calculation for initializing the simulations
and in the controller design process. A general schematic of
the PSUHeloSim flight dynamics model (not including the
controller described below) is shown in Figure 1.
The simulation is integrated with a non-linear dynamic
inversion control law.10 This control law has been
developed for rotorcraft application on a number of research
programs at PSU, and has recently been used for non-real-
time simulations with complex aeromechanical models.2
The controller achieves high precision closed-loop control
of the simulated helicopter and tracks a commanded
velocity vector and heading in NED frame. Note that an
evolution of this controller, designed to follow a specific
trajectory (x,y,z coordinates), will be used in future coupled
simulations. Engineering simulations require a “pilot
model” to regulate the helicopter (which may have unstable
dynamics) and keep it on a specific flight path during
maneuvers. The NLDI controller serves this purpose.
High-Fidelity Rotor Module
PSUHeloSim is integrated with a high-fidelity rotor module
for fully-coupled or one-way-coupled simulations. The
CHARM Rotor Module uses a Constant Vorticity Contour
(CVC) full-span free-vortex wake model, combined with a
vortex lattice, lifting surface blade model11. The module
calculates blade motion including structural modes in the
blade dynamics. This module runs as a separate code
obtaining the state, state derivatives and controls from
PSUHeloSim at each time step of the simulation and
returning the forces, moments, and flapping coefficients of
the rotor systems. In the one-way coupled mode, the blade
loads are stored for use in acoustic prediction, but are not
used by the PSUHeloSim flight dynamics model. In the
fully-coupled mode, the forces and moments calculated by
CHARM are used as inputs for the PSUHeloSim code. Thus
in the fully coupled mode, CHARM acts as the main rotor
module and/or tail rotor module of the simulation (it
replaces the simple built-in rotor models in PSUHeloSim).
In either mode, CHARM is able to produce loading files that
are then used by PSU-WOPWOP to determine the
aerodynamically induced noise. One can choose to couple
the main rotor, the tail rotor or both. The acoustic prediction
is able to operate with more than one rotor at a time. The
only present limitation is that the loading output for acoustic
prediction is limited to a single rotor revolution which is
assumed to be periodic. This means that acoustic analysis
can be performed just for steady or quasi-steady flight
conditions. (It is planned to relax this limitation to enable
fully coupled transient maneuver simulations.)
Noise Prediction Model
The noise prediction model used in this work, PSU-
WOPWOP7-9, is a numerical implementation of Farassat’s
Formulation 1A11 of the Ffowcs Williams Hawkings (FW-
H) equation.12 Formulation 1A is used to predict the discrete
frequency noise prediction (thickness, loading, BVI, etc.)
from first principles when provided with the aircraft and
rotor blades position, motions, and blade loading. PSU-
WOPWOP predicts the acoustic pressure time history for
either stationary or moving observers and the code is also
able to convert the output signals into acoustic spectra, such
as 1/3rd octave bands and multiple types of noise metrics
relevant to noise certification and community annoyance
(PNL, PNLT, SEL, EPNL, and OASPL, etc.). The
broadband noise is computed in PSU-WOPWOP by
implementing an empirical prediction developed by Pegg13
that predicts the broadband noise in 1/3rd octave bands.
This is then combined with the discrete frequency noise for
a total noise prediction. In a recent research effort, it has
been demonstrated that a flight simulation coupled with
CHARM and PSU-WOPWOP can predict the noise in “real
time”. The system developed in this work is somewhat
different, but it is still reasonably fast.
Schematic of the Simulation Process
The simulation process consists of three main steps: 1)
solving trim for the prescribed flight condition, 2) running a
PSUHeloSim /CHARM coupled simulation, and 3)
performing an acoustic prediction with PSU-WOPWOP
based on the results of the simulation. A Newton-Raphson
based trimming algorithm is used to find an equilibrium
condition for the state and the controls. Note that this trim
solution is based only on the base PSUHeloSim model.
Once trim is achieved, the trim state and control solution is
used as initial conditions of the coupled simulation (both for
PSUHeloSim and the CHARM rotor modules).
During the simulation, the time history of velocity and
heading commands are fed to the dynamic inverse controller
in the PSUHeloSim code. The controller calculates the
control input based on the tracking error and feedforward
signals as defined by the control law. The sim code updates
the state, state derivatives, and swashplate inputs, which are
then used as inputs for the CHARM rotor module. The
resulting main rotor forces and moments calculated by
CHARM are either saved as output (in one way coupled
mode) or fed back into the simulation model in fully-
coupled mode. When performing fully-coupled simulations,
the full coupling is not initiated until three seconds of
simulation have passed. This allows the free-wake model
time to develop and initialize. After the simulation is
completed, the PSU-WOPWOP acoustics analysis is
performed using the aircraft state and loading files
generated by CHARM. Figure 2 shows the flowchart of the
simulation process.
Figure 1. Schematic of the PSUHeloSim/CHARM/PSU-WOPWOP simulation model.
Flight Simulation Results
The helicopter used for the current simulation results is a
Bell 430; a summary of its characteristics is presented in
Table 1.
A number of basic maneuvers were simulated using the
standard PSUHeloSim model and the fully-coupled
simulation with the CHARM rotor module. The simulations
were used to verify that the fully-coupled simulations
followed the expected behavior and that the NLDI
controller can adequately stabilize and control the coupled
When using the one-way coupled simulation or the stand-
alone PSUHeloSim model, the CHARM rotor module is not
used in the flight dynamics solution. This means that the
dynamic simulation involves just the base PSUHeloSim and
the Dynamic Inversion based controller. The DI controller
is designed around linearized models of the PSUHeloSim,
which leads to very accurate tracking of controller
commands. The trim solver is also based on the
PSUHeloSim model and results in near perfect
initialization. This is seen in the red results of Figure 3,
which show the attitude response when the commanded
trajectory simply holds a 100 kts level flight trim condition.
It can be seen that there is no deviation from trim.
Mass and Inertia Properties
Figure 2. Flowchart of the simulation process.
In the fully-coupled case, the main rotor forces, moments
calculated by the CHARM rotor module are fed back into
the dynamic simulation, changing the nature of the
nonlinear model. So when the coupling is turned on, after
three seconds of simulation, the helicopter goes through a
transient due to the differences of forces and moments
between CHARM and the PSUHeloSim model. The
controller is robust enough to restore the trim, causing the
aircraft to converge to a steady state after a period of time.
The new equilibrium is usually slightly different from the
initial trim. This is partly due to differences in trim of the
CHARM rotor and the simple rotor model in PSUHeloSim.
In addition, a helicopter can trim with different
combinations of roll attitude and sideslip angle. When
trimming PSUHeloSim the yaw attitude / sideslip are set to
zero, but after coupling is initiated the system settles into a
slightly different steady state.
A decelerating descent maneuver was simulated with and
without coupling. The results are shown in Figure 4. With
coupling, the simulation is initially flown in steady 100 knot
level flight for a period of time to allow the helicopter to
return to trim after the transient at initialization. Figure 4
shows the response after the initial wait period. The
maneuver consists of a 6 decelerated descent from 100 to
60 kts at 0.1 g of deceleration. Figure 4 compares responses
of the “de-coupled” baseline PSUHeloSim and the fully
coupled model with CHARM. In both cases, the vehicle
response follows the command after the initial transient, and
the responses are similar for both models. The velocity and
altitude profiles are essentially identical, which is expected
since these are tracked by the controller. There are slight
differences in attitudes due to differences in the two rotor
models. Note that there is some deviation of the lateral cross
track (y-position), but the lateral drift is only about 4 ft after
900 ft down range motion.
Main Rotor
Tail Rotor
Table 1. Bell 430 key characteristics.
a) Position
b) Absolute velocity and acceleration
Figure 3. Coupling transient: dashed line marks the
start of the coupling.
Figure 5 shows a 90 turn maneuver at 100 kts forward
airspeed. Once again, time was allotted to allow the
controller to stabilize the aircraft after the coupling
transient. Once again we see very similar flight path with
both the coupled and de-coupled PSUHeloSim. Note that
the velocity fluctuations are quite small. The accelerations
seen are largely in the lateral axis due to Dutch Roll
oscillations. This mode appears to be less damped with the
coupled model.
When simulating main rotor and tail rotor physics with the
CHARM rotor module, the simulation time step is driven by
the largest allowable tail rotor blade sweep per time step
(since the tail rotor has a larger RPM). For example, 15°
blade sweep per time step is usually considered the largest
acceptable time step for blade element rotor simulations in
flight dynamics. Consequently the main rotor (which turns
slower) will have a smaller blade sweep.
One of the unique features of this system is the ability to
capture relevant physics for the acoustics. In particular, the
free wake needs a sufficient number of elements for
accurate blade loading, which in BVI conditions should be
as fine as 1 azimuthal resolution. With such high temporal
(azimuthal) and corresponding spatial resolution
requirements, it is impossible to perform real-time analysis
with the free wake and could take substantial computational
power to be useful in the computation of realistic maneuvers
tens of hours on a single processor. Fortunately, this issue
has been addressed in the CHARM rotor module through
“reconstruction” of the rotor wake in post-processing. In
this approach, a low resolution wake and larger time step is
used in the flight simulation step, which is acceptable for
flight dynamics modeling. Then, for the regions of the
maneuver where acoustics are of interest, a higher
resolution wake and blade loading is reconstructed in the
CHARM rotor module14. These high resolution blade loads
are then used by PSU-WOPWOP to predict BVI-dominated
noise. In recent work, this method was used to perform real-
time, BVI-noise predictions15. Currently reconstruction can
only be applied to one rotor.
c) Attitude
Figure 4. Results from a 6 decelerated descent at 0.1 g
of deceleration.
a) Trajectory
b) Absolute velocity and acceleration
c) Attitude
Figure 5. Results from a 90 turn at 100 knots.
Acoustic Results
Helicopter rotor noise consists of several noise sources
including discrete frequency noise (thickness, loading, and
blade-vortex-interaction (BVI) noise), broadband noise, and
high-speed-impulsive (HSI) noise (HSI noise only occurs in
high speed forward flight). Each of these noise sources has
a unique directivity, as shown in Figure 6. Thickness noise
is dominant in the plane of the rotor, so it is the primary
noise heard as a distant helicopter approaches. Only the
motion of the rotor blades and the aircraft, along with the
geometry of the rotor blades, is needed to compute the
thickness noise; hence, the flight simulation code is readily
able to provide this information (at very low computational
cost). High-speed impulsive noise has the same directivity
as thickness noise, but it only occurs in high-speed flight
(and will not be addressed here).
Loading noise is another important source of rotor noise,
which is typically directed below the rotor so loading
noise is important as the aircraft is overhead. There are two
important types of loading noise that are generally dealt
with separately: BVI noise and broadband noise. BVI noise
is the dominant noise source when it occurs. It has a very
impulsive nature and originates from a nearly parallel close
interaction between a blade and the tip vortex of a previous
blade. BVI noise is highly directional and depends strongly
on the vortex strength, miss distance, and interaction angle.
This is the reason that a high-fidelity rotor and wake model
are needed in this system to predict BVI noise accurately.
Broadband noise is another type of loading noise that is a
result of stochastic loading due to various airfoil self-noise
sources, turbulence ingested into the rotor, or turbulence
entrained by tip vortices (when they are not quite close
enough to cause significant BVI noise). The empirical
model derived by Pegg13 are used in PSU-WOPWOP to
predict the broadband noise and the input data is relatively
easy to obtain from the flight simulation system.
Figure 7 shows the contribution to each of the noise
components to the Overall Sound Pressure Level (OASPL)
as function of the uprange/downrange distance for the Bell
430 helicopter flying at 100kts at an altitude of 150m. At
  , the helicopter is directly overhead. OASPL is not
weighted by frequency and hence tends to reflect the large
amplitude of the low frequency components of the rotor
noise. Notice that as the aircraft approaches (negative
distances) the thickness noise is the dominant source of
noise. This is because the thickness noise directivity is in
the plane of rotor; hence, the observer hears it first. The
loading noise becomes begins takes over as the dominant
noise source as the aircraft passes overhead and continues
downrange (positive distances). The broadband noise
makes only a contribution to OASPL, so it is not shown in
the figure.
Figure 8 shows a similar plot of the noise components, but
in this case the tone corrected, perceived noise level (PNLT)
is plotted as a function of the uprange/downrange distance
from the target observer location and the aircraft is directly
overhead at  . PNLT uses a frequency weighting that
is intended to be representative of human annoyance; hence,
higher frequencies are more important. The relative
importance of the various noise sources is quite different in
this case. The thickness noise is still the dominant noise as
the aircraft is approaching (larger negative distances), but
the broadband noise is significant as the aircraft approaches
the overhead condition and dominant for all downrange
positions (positive distances). The loading noise also
increases overhead and downrange, but is always lower in
this flight condition than broadband noise. This is because
the loading noise in level flight has fairly low frequency
content as this is a level flight condition. For level flight
BVI noise is not expected, but if there had been BVI noise
Figure 6. Typical direction of primary radiation for
various rotor noise sources.
Figure 7. Noise components and their contribution to
the OASPL predictions for a 100 kts flight case flown
at 150 m altitude.
the loading noise levels would have been substantially
Demonstration Calculation Prediction of BVI Noise
Reduction using the Blue Edge-like Blades
An important attribute of this work is that the coupled
system can accurately predict the acoustic characteristics of
dominant noise sources without reliance on test data. During
approach and landing, blade-vortex interaction (BVI) noise
is a dominant out-of-plane noise source responsible for
much of the ground noise. In order to provide a tool for
evaluating the impact of modifications to flight path and
rotor design on ground noise exposure during landing, it is
necessary to demonstrate that the model can accurately
predict BVI noise for BVI-dominant flight conditions. The
ability of the CHARM/WOPWOP and subsequently
CHARM/PSU-WOPWOP solutions to predict main rotor
BVI noise in these flight conditions for conventional rotors
(and tiltrotors) was demonstrated in prior work.14,15 In the
current work, this demonstration was extended to an
advanced blade design known to reduce BVI noise (Figure
9)16, Airbus Helicopter’s “Blue Edge” blade. The concept
behind this design is described in Ref. 17 as:
With a standard blade, air coming off the end of the blade
causes a vortex around the tip. Under certain flight
conditions the advancing blade then hits the vortex of the
preceding blade. This causes a sudden change in the
relative angle of attack and thus a change in pressure on
the surface of the blade. This BVI causes the slapping
sound ubiquitous to helicopter operations. With Blue Edge
technology, the blade tip is swept forward, then aft. This
causes the advancing blade tip to hit the previous blade’s
vortex at an oblique angle, reducing the noise level by 3 to
4 EPNdB.17
Calculations were performed to demonstrate the ability of
the new analysis system to predict the reduction in BVI
noise obtained using a Blue Edge-like planform. Three
blade planforms were compared operating on a Bell 430
rotor/aircraft configuration: 1) conventional rectangular
blades nominally the current Bell 430 blade; 2) tapered
blades, 3) Blue Edge-like planform with taper and
forward/aft sweep. The planform characteristics of each of
these three blade sets are provided in Table 2 below. Figure
10 compares the tapered and Blue Edge-like planforms. No
optimization of the tapered and Blue Edge-like planforms
was performed to minimize noise. The Blue Edge-like
planform forward/aft sweep schedule is roughly comparable
to photographs of the Airbus Blue Edge blade, capturing the
key feature of reducing the “parallel” nature of the BVI.
Figure 8. Noise components and their contribution to
the PNLT predictions for a 100 kts flight case flown at
150 m altitude.
Figure 9. Blue Edge blade concept from Eurocopter
(now Airbus Helicopters).16
Tip Speed
Rotor Cutout
Rotor Chord
 - rectangular
linear taper -
tapered and Blue Edge
Anhedral Tip
Swept tip
none - rectangular and tapered
forward -12 at r/R=0.6
aft 34.4 at 0.85 (Blue Edge)
Root Airfoil
NACA 0012
Tip Airfoil
NACA 0012 - rectangular
NACA 0009 - tapered and Blue
Air Density
Speed of Sound
Hub Type
Lock Number
Table 2. Characteristics of the three blade planforms.
The flight condition studied was a descent at low speed
(=0.15) with the rotor tilted back 6 relative to the flight
path. The sound pressure level was determined in a plane
one rotor radius beneath the rotor plane. The CHARM
solution was performed with an azimuthal resolution of
=15 and then reconstructed to a resolution of =1
using the method described in14. The blade aerodynamics
and acoustic solution at 187 observer points was completed
in 3 minutes on a single core of an off-the-shelf CPU.
Figure 11 shows predictions of both the overall sound
pressure level (OASPL) and the BVI sound pressure level
(BVISPL) (harmonics 6-40 in blade passage frequency) for
this configuration. The magnitude and directionality
predicted is characteristic of the results seen for BVI-noise
dominated descent flight conditions. The analysis predicts
that the taper reduces the peak BVISPL by roughly 2dB and
the Blue Edge-like planform further reduces the peak
BVISPL by another 3dB for a total reduction of peak
BVISPL of 5dB, capturing the documented benefit of the
Blue Edge planform.
Figure 10. Tapered and Blue Edge-like planforms.
OASPL (harmonics 0 50 BPF)
BVISPL (harmonics 6 40 BPF)
Figure 11. CHARM/PSU-WOPWOP main rotor OASPL and BVISPL predictions one rotor radius beneath the nominal
Bell 430 rotor for the three blade geometries; s=6 (back), =0.15 and CT=.00143. The black circle represents the rotor tip
advancing side on the right.
Figure 12 shows the advancing-side BVI for the Blue Edge
planform compared with a rectangular blade as predicted by
the CHARM code. Notice in the figure that the tip vortex
(the red curved line) is nearly parallel to the entire length of
the blade for the rectangular blade (left), while the shape of
the Blue Edge planform (right) results in an interaction that
occurs over a wider range of rotor azimuth angles; hence, it
is a much less impulsive interaction.
The measurement plane shown in Figure 11 reveals that the
main rotor BVI noise is significantly reduced by the Blue
Edge-like rotor planform, but a more typical noise
prediction for a complete rotorcraft is made either on a
hemisphere or a ground plane. To demonstrate the fully-
coupled system this BVI noise was predicted for the full
helicopter configuration. Here the aircraft flight condition
is a forward speed of 68 kts and a 6° descent flight profile
providing the same main rotor operating condition as shown
in Figures 11 and 12. Figure 13 shows the OASPL of the
Bell 430 helicopter (with rectangular main rotor blades and
the tail rotor included). Notice in the figure that the focused
region of BVI noise is still clearly evident on the hemisphere
Figure 14 shows the acoustic pressure time histories for
each of the main rotor planforms at a point located on the
hemisphere at an azimuth of 125° and down 45° from the
main rotor tip-path plane (indicated by a small black dot in
Figure 13). Notice in the figure, for each blade geometry
there are 4 very narrow and high amplitude pressure spikes
(or group of spikes). These are the BVI from each of the
four blades on the main rotor. The thickness and loading
noise of the main rotor also occur approximate the same
time, so they are difficult to see. These pulses are the tail
rotor thickness noise. Comparison of the three different
rotor blade geometries shows how the BVI acoustic
pressure spikes amplitude is greatly reduced for the case of
the Blue Edge-like rotor. The tapered blade also has a small
reduction in BVI spike amplitude, primarily seen on the
positive part of the pressure spike. The other features, i.e.,
the tail rotor noise, is essentially unchanged.
Figure 12. BVI event as predicted by CHARM for the baseline
RECTANGULAR blade and the BLUE EDGE blade.
Figure 13. Contours of OASPL on a 30.48m radius
hemisphere, centered at the Bell 430 c.g. location. The
hemisphere follows the aircraft. OASPL contours shown are
for the standard rectangular blades.
Direction of flight
The noise comparisons shown in this section demonstrate
the utility of the flight simulation, high-fidelity wake, noise
prediction system that has been developed here.
Furthermore, design changes to reduce BVI noise one of
the more challenging components of the noise to predict
show the expected noise reduction trends.
A simulation tool has been developed that couples: 1) A
flight dynamics simulation with closed loop control
(PSUHeloSim), 2) A high-fidelity aeromechanics model of
the rotor with a free wake (CHARM rotor module), and 3)
an industry-standard noise prediction code (PSU-
WOPWOP). Both uncoupled and fully coupled simulations
were first tested for some basic maneuvers, and the results
showed that the rotorcraft (with controller) was able to fly
the prescribed trajectory when using the CHARM rotor
module for rotor force and moment calculations, and that
the control and attitude response was reasonable. Coupling
with PSU-WOPWOP acoustics analysis was then tested,
with a focus in this paper on a BVI-dominated descent
condition. Then three different blade geometries were
evaluated on the Bell 430 helicopter, including a Blue Edge-
like blade planform that is expected to provide significant
BVI noise reduction. The acoustic analysis predicted the
expected noise reductions with approximately the same
level of noise reduction as reported by Airbus Helicopters.
Some specific conclusions from this effort:
1. It has been demonstrated that the integrated simulation
was capable of predicting realistic maneuvers when
coupling the CHARM rotor module and PSUHeloSim
simulation. It is crucial that the simulation include a
robust flight controller, to handle the transients and
change in aeromechanics upon coupling with the higher
fidelity main rotor and tail rotor models.
2. The time step and wake resolution requirements for
accurate acoustic predictions of the main rotor and tail
rotor would be much slower than real-time execution,
but the use of wake reconstruction to get higher
resolution of the blade loading in post-processing
(especially in BVI dominated conditions) was found to
be a critical tool for improving efficiency of the tool
and approaches real-time prediction speeds while still
providing highly accurate, high-fidelity blade loading
for noise prediction.
3. The use of the CHARM rotor module significantly
enhances the fidelity level of the simulation, by adding
free wake and nonlinear dynamics of flexible blades (as
opposed to 3-state inflow, and a rotor disk model with
linearized flapping dynamics). While this level of
fidelity is not necessarily required for flight simulation,
the CHARM rotor module captures higher resolution
blade loading needed for acoustics calculations. One of
the motivations for full coupling (feedback of CHARM
rotor forces to the vehicle dynamics) is to ensure
consistency of the rotor force output with the flight
trajectory flown.
4. The CHARM rotor module successfully captured the
behavior of the “Blue Edge” blade in terms of blade
vortex interaction thus underlining its strength in
comparison to other more classic blade geometries.
This case also demonstrates the predictive capability of
the entire system.
5. The coupling of the simulation and CHARM rotor
module results in a coupling transient. The transient is
a simulation artifact and not relevant to the physics of
interest. Some additional processing time is required to
allow the controller to stabilize and re-trim the aircraft
before performing the maneuver of interest. We are
currently working to reduce this transient to improve
efficiency of the tool.
This work was funded by the U. S. Federal Aviation
Administration (FAA) Office of Environment and
Energy as a part of ASCENT Project 6 under FAA
Award Number: 13-C_AJFE-PSU-006. Any opinions,
findings, and conclusions or recommendations
Figure 14. Acoustic pressure time history at azimuth angle   , elevation angle    below the rotor plane,
and radius of 30.48m from the helicopter c.g. (i.e., the location of the black dot in Figure 13).
expressed in this material are those of the authors and
do not necessarily reflect the views of the FAA or other
ASCENT Sponsors.
1. Horn, J.F., Bridges, D.O., Wachspress, D.A, and
Rani, S.L., “Implementation of a Free-Vortex Wake
Model in Real-Time Simulation of Rotorcraft,” AIAA
Journal of Computing, Information, and
Communications, Vol. 3, (3), March 2006.
2. Oruc, I., Horn, J.F., Polsky, S., Shipman, J. and
Erwin, J., “Coupled Flight Dynamics and CFD
Simulations of Helicopter/Ship Dynamic Interface,”
American Helicopter Society 71st Annual Forum
Proceedings, Virginia Beach, VA, May 2015.
3. Brentner, K.S., Lopes, L.V., Chen, H.N., and Horn,
J.F., “Near Real-Time Simulation of Rotorcraft
Acoustics and Flight Dynamics,” AIAA Journal of
Aircraft, Vol. 42, (2), March-April 2005, pp. 347-355.
4. Chen, H.N., Brentner, K.S., Lopes, L.V., and Horn,
J.F., “An Initial Analysis of Transient Noise in
Rotorcraft Maneuver Flight.” International Journal of
Aeroacoustics, Vol. 5, (2), April 2006.
5. Li, Y., Brentner, K. S., Wachspress, D. A., Horn, J. F.,
Saetti, U., and Sharma, K., “Tools for Development
and Analysis of Rotorcraft Noise Abatement”,
American Helicopter Society International, Inc.
Sustainability 2015, Montréal, Québec, Canada,
September 22-24, 2015.
6. Wachspress, D. A., Quackenbush, T. R., &
Boschitsch, A. H. (2003, May). First-principles free-
vortex wake analysis for helicopters and tiltrotors. In
Annual Forum Proceedings American Helicopter
Society (Vol. 59, No. 2, pp. 1763-1786).
7. Brès, G. A., Brentner, K. S., Perez, G., and Jones, H.
E., “Maneuvering rotorcraft noise prediction,” Journal
of Sound and Vibration, 275(3-5):719-738, August
8. Brès, G. A., “Modeling the noise of arbitrary
maneuvering rotorcraft: Analysis and implementation
of the PSU-WOPWOP noise prediction code,” M.S.
thesis, Department of Aerospace Engineering, The
Pennsylvania State University, June 2002.
9. Perez, G., “Investigation of the influence of maneuver
on rotorcraft noise,” M.S. thesis, Department of
Aerospace Engineering, The Pennsylvania State
University, June, 2002.
10. Enns, D., Bugajski, D., Hendrick, R., & Stein, G.
(1994). Dynamic inversion: an evolving methodology
for flight control design. International Journal of
Control, 59(1), 71-91.
11. Farassat, F. and Succi, G. P., “The Prediction of
Helicopter Discrete Frequency Noise,” Vertica,
7(4):309320, 1983.
12. Ffowcs Williams, J.E., Hawkings, D.L., “Sound
generated by turbulence and surfaces in arbitrary
motion,” Philos. Trans. R. Soc. A 1969;
13. Pegg, R.J., “A Summary and Evaluation of Semi-
Empirical Methods for the Prediction of Helicopter
Rotor Noise,” NASA Technical Memorandum 80200,
December 1979
14. Wachspress, D.A. and T.R. Quackenbush (2001).
"BVI Noise Prediction using a Comprehensive
Rotorcraft Analysis," American Helicopter Society
57th Annual Forum, Washington, D.C., May
15. Wachspress, D.A., K.S. Brentner, and J.A. Page
(2005). "Real-Time Noise Prediction of V/STOL
Aircraft in Maneuvering Flight," CDI Report No. 05-
14 under NASA Contract NNL05AB01P, July.
16. Paur, J. Eurocopter Moves One Step Closer To
'Whisper Mode'. 2010 Feb 25, 2010 [accessed
3/4/2016]; Available from:
17. Nelms, D. (2015). "New Eco-Friendly Bluecopter
Unveiled," Vertiflite 61(5): pp. 26-28.
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... This dissertation focuses on addressing the critical gaps mentioned in the previous sections. The enhancement of the previously coupled noise prediction system [45,46], validation of the system, and analysis to aid in understanding the events occurring during the flight test procedure in the interest of studying the noise source generation mechanism and for developing noise abatement procedures is the main contribution from the current work. The noise prediction system couples [29,45,46, 54] a flight simulation code (PSUHeloSim), a high-fidelity rotor aeromechanics model with free wake (CHARM Rotor Module) [39-44, 55, 56], and an industry-standard noise prediction tool (PSU-WOPWOP) [5,6,6,7] to predict noise generated during a flight procedure. ...
... The enhancement of the previously coupled noise prediction system [45,46], validation of the system, and analysis to aid in understanding the events occurring during the flight test procedure in the interest of studying the noise source generation mechanism and for developing noise abatement procedures is the main contribution from the current work. The noise prediction system couples [29,45,46, 54] a flight simulation code (PSUHeloSim), a high-fidelity rotor aeromechanics model with free wake (CHARM Rotor Module) [39-44, 55, 56], and an industry-standard noise prediction tool (PSU-WOPWOP) [5,6,6,7] to predict noise generated during a flight procedure. The tools used are physics-based models that can be adapted to predict flight dynamics, rotor loads, and noise from various rotorcraft configurations. ...
... PSUHelosim [45,46] The roll up of the vortex sheet or the trailed vortex filament eventually forms a single trailed tip vortex whose core size and structure can be determined analytically using the Vatistas equation [51][52][53]. This tip vortex model and its trajectory is further used to determine BVI airloads. ...
Full-text available
The main contribution from the current work is the enhancement of a comprehensive noise prediction system for rotorcraft and a methodology to analyze flight test procedures in the interest of understanding the noise source generation mechanisms and aid development of noise abatement procedures. This dissertation describes a rotorcraft noise prediction system and its development to incorporate time-dependent information–including trajectory, attitude, blade loads and rotor thrust–for predicting noise generated during a complex maneuver. The validation process is carried out by comparing the predicted noise levels (SELdBA, OASPL and A–weighted SPL) and processed flight test data. The examples considered are: level flight; descent flight; level turns; level, decelerating turns; and descending turns. This range of operations is considered to analyze the prediction system and understand its capabilities and deficiencies for future work. Overall the predicted noise levels were able to match the trends and levels within a 2–4 dB of that measured during the flight test. The time histories are studied in detail to understand the influence of events (such as steady flight conditions, with constant speed, roll angle or descent rate, and transient flight conditions, including roll-in and roll-out of turn, start and end of deceleration or acceleration) occurring during the flight procedure on noise levels and directivity. The key takeaways are that the noise prediction system was able to capture the noise levels but missed blade-vortex-interaction (BVI) noise directivity during some complex maneuvers. Transient maneuvers generate higher-harmonic loading and BVI noise and the intensity depends on the rate of change of flight conditions. The tail rotor not only contributes the thickness noise below the flight path but has significant contribution at sideline observer locations during a maneuver. The radiation distance and directivity have shown a stronger effect on noise levels than the harmonic noise sources. Lastly, the broadband noise dominates the A–weighted SPL for the steady maneuvers (except descent) and its importance is less during the transient flight segments. A final thing to note is that the noise generated during a 6° steady descent (the standard descent angle for approach) was much higher than any other complex procedures studied in the current work.
... Blade-vortex interaction (BVI) is identified as the dominant source of noise in rotorcraft. Vortex methods are powerful tools for researchers to study interactions of blade wake vortices with each other as well as with other rotorcraft components [23,[53][54][55]. Rotorcraft are strongly affected by unsteady aerodynamic loads (e.g., BVI), which significantly contribute to vibration and structural deformation. ...
... The wake field plays an important role in rotorcraft performance with significant impacts on rotorcraft's performance, vibration [105], maneuverability [106], and noise [54,105]. The dominant vortical structures of the rotor wake are the inboard vortex sheet and the tip vortices [25]. ...
... As a result of the presence of shedding vortices from the leading edge of the airfoil, nonlinear variations in lift, drag, and pitching moment coefficients as a function of angle of attack occur, and their values in the stall and post-stall regions are completely different from the static aerodynamic coefficients. Dynamic stall (54) ...
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Electric vertical take-off and landing (eVTOL) aircraft with multiple lifting rotors or prop-rotors have received significant attention in recent years due to their great potential for next-generation urban air mobility (UAM). Numerical models have been developed and validated as predictive tools to analyze rotor aerodynamics and wake dynamics. Among various numerical approaches, the vortex method is one of the most suitable because it can provide accurate solutions with an affordable computational cost and can represent vorticity fields downstream without numerical dissipation error. This paper presents a brief review of the progress of vortex methods, along with their principles, advantages, and shortcomings. Applications of the vortex methods for modeling the rotor aerodynamics and wake dynamics are also described. However, the vortex methods suffer from the problem that it cannot deal with the nonlinear aerodynamic characteristics associated with the viscous effects and the flow behaviors in the post-stall regime. To overcome the intrinsic drawbacks of the vortex methods, recent progress in a numerical method proposed by the authors is introduced, and model validation against experimental data is discussed in detail. The validation works show that nonlinear vortex lattice method (NVLM) coupled with vortex particle method (VPM) can predict the unsteady aerodynamic forces and complex evolution of the rotor wake.
... This new DEP aircraft noise prediction system is inspired by the previous helicopter noise prediction system consisting of the PSUHeloSim helicopter flight dynamics simulation code, CHARM, and PSU-WOPWOP (Refs. [3][4][5]17), but integrates the new PSUDEPSim flight simulator and an updated software coupling methodology tailored to the unique characteristics of DEP aircraft. Each of the components of this noise prediction system are described in more detail in the section "Noise Prediction System Architecture" that follows. ...
... PSUDEPSim PSUDEPSim is an extension of the HeloSim flight simulation system developed at Penn State (Ref.17). Like PSUHeloSim, PSUDEPSim performs a full nonlinear simulation of vehicle flight dynamics, including 6-DOF rigid body equations of motion, rotor flapping dynamics, and finitestate inflow dynamics, and is coupled with the CHARM Rotor Module. ...
Conference Paper
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A major barrier to certification and public acceptance of emerging distributed electric propulsion (DEP) aircraft is their noise. Like conventional helicopters, accurate noise prediction of DEP aircraft requires accurate modeling of realistic flight dynamics and controls. Furthermore, aspects unique to DEP aircraft must be modeled, such as variable rotor speed for thrust control, and unsteady aerodynamics arising from rotor thrust control and aerodynamic interactions between rotors and the airframe. To address these needs, this paper describes the development and software coupling of a noise prediction system for DEP aircraft. This system is demonstrated for maneuvering flight simulations consisting of a roll attitude doublet in low speed forward flight, for two rotor thrust control schemes: variable rotor speed and variable collective pitch. Loading noise levels for this configuration generally exceeded thickness noise levels. For a single rotor, loading noise modulated with thrust, regardless of the cause of the time variation of loading (variable rotor speed or collective pitch). However, the range of modulation was greater for the variable rotor speed case than for variable pitch. Less modulation is observed in the total noise for all rotors, because the rotor thrusts must vary to balance the aircraft. Interference patterns are observed for the constant speed case due to coherent phase relations between the rotors, whereas the noise of the variable speed rotors does not add coherently.
... The development of DI flight control laws for rotorcraft has been a major area of research at the Pennsylvania State University over the past two decades. The majority of these studies concentrated on full-scale rotorcraft [1][2][3][4][5][6][7][8], whereas only a few focused on small-scale UAS [9,10]. Further, the studies that focused on small-scale quadrotors only implemented DI for outer guidance/navigation loops and relied on the UAS built-in controllers for the inner attitude loops. ...
... A DI [1,21] control law is designed to achieve stability, disturbance rejection, an attitude command/attitude hold (ACAH) response around the 032006-5 Pitch phugoid 1.5698 ± 2.8634i λ 6 Pitch subsidence −3.3964 λ 7 Yaw subsidence −0.5616 λ 8 Yaw integrator 0 λ 9 Heave subsidence −0.1734 roll and pitch axes, and a rate command/attitude hold (RCAH) response around the yaw and heave axes. A similar controller was previously implemented on a B-430, as discussed in (Ref. ...
The objectives of this paper are to advance dynamic inversion (DI) and explicit model following (EMF) flight control laws for quadrotor unmanned aerial systems (UAS) and to develop an efficient strategy to compute the stability and performance robustness statistics of such control laws given parametric model uncertainty. For this purpose, a parametric model of a quadrotor is identified from flight-test data. The identified model is validated both in frequency and time domains. Next, DI and EMF flight control laws are designed for both inner attitude and outer velocity loops. Finally, a novel approach based on an unscented transform is used to evaluate the statistics of the controller’s performance based on the statistics of the uncertain model parameters.
... The PSUHeloSim/CHARM/PSU-WOPWOP helicopter noise prediction system developed in [24][25][26] and validated by Botre et al. [2,27] is used to calculate the noise during maneuvering flight of a Bell 206 helicopter, which was previously studied by the authors in [8]. No attempt was made to track state variable variations from the nominal flight state in PSUHeloSim [2,27,28]: i.e., the flight simulations are periodic, whereas flight tests are never truly periodic due to disturbances. ...
Conference Paper
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Rotor broadband noise is typically computed and analyzed as a spectrum over a time scale on the order of the rotor period. However, temporal variation of the broadband spectrum within a rotor revolution has been shown to be significant to noise levels and perception. The time variation of helicopter rotor broadband noise caused by aerodynamic interactions and the tail rotor was analyzed for a Bell 206 in level and descending flight. Spectrograms were constructed using both flight test noise measurements and computational predictions using the Brooks, Pope, and Marcolini (BPM) model; these are then compared to validate the predictions, provide insight into the important noise source physics, and inform how the prediction models could be improved. Modulation trends were well-predicted, especially modulation depths. In contrast, peak broadband noise levels were underpredicted, especially for the tail rotor and excess noise caused by aerodynamic interactions. The duty cycle of main rotor broadband noise modulation was overpredicted. Broadband noise modulation with the tail rotor blade passage frequency was found to be significant, especially for observers on the main rotor retreating side, even when blade-vortex interactions (BVI) are present. This is because tail rotor broadband noise had similar peak levels to main rotor broadband noise when BVI noise does not dominate. Tail rotor broadband noise modulation had a significant modulation depth (>10 dB), with a higher modulation frequency (equal to the blade passage frequency) than the main rotor. Furthermore, this modulation exhibited significant aperiodicity, causing substantially-different noise spectra between different blade passages.
... Because the fidelity of flight simulation codes in the prediction blades loads may be limited, high-fidelity aeromechanics models (e.g., free wake, CFD) are added as a third element in the case where the capability of predicting blade-vortex interaction (BVI) noise is needed (Refs. [3][4][5]. ...
Conference Paper
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The paper discusses the development of a novel linearization algorithm to obtain high-order linear time-invariant (LTI) models of the coupled rotorcraft flight dynamics, vibrations, and acoustics. To demonstrate the methodology, the study makes use a nonlinear simulation model of a generic utility helicopter (PSU-HeloSim) that is coupled with an aeroacoustic solver based on a marching cubes algorithm. First, a revisited harmonic balance algorithm based on harmonic decomposition is applied to find the periodic equilibrium and approximate high-order LTI dynamics at 80 kts level flight. Next, the proposed output linearization scheme is applied to derive time-invariant, linearized equations of the main rotor forces and moments, and acoustics. Simulations are used to validate the response of the linearized models against that from nonlinear simulations. Additionally, the cost of linearization and potential performance benefits of employing linear models versus nonlinear simulations are assessed. The high-order LTI models thus obtained are shown to provide similar acoustic predictions compared to those of nonlinear simulations for small amplitude maneuvers, but at a fraction of the computational cost. These linear simulations are shown to run in the order of thousands of times faster than real time, and four orders of magnitude faster than nonlinear acoustic predictions based on a marching cubes algorithm.
... CHARM can reconstruct wake with higher resolution, and this ability helps to catch bladevortex interaction loads successfully. It is also a highly used comprehensive tool for the noise analysis of rotorcrafts [13,[26][27][28][29][30][31]. ...
Full-text available
The noise of the rotorcraft has become nonignorable with their increasing use in daily life. The aerodynamically active components such as the main and tail rotors are the primary sources of noise, and therefore, their evaluation during the design phase must also be carefully included. Pressure variations caused by several aerodynamic mechanisms on the rotor blades are responsible for the generation of the noise, which may be obtained by computational fluid dynamics. Along with rotor locked self pressure fields, the tail rotor being in the main rotor wake and exposed to strongly nonstationary airflow also need attention. Hence, full helicopter modeling is required to have an accurate evaluation on the tail rotor. However, this modeling and solution are costly for computational fluid dynamics. Therefore, an alternative approach for acoustic analysis is developed in this study. Accordingly, the goal of the thesis is to propose a coupling methodology between comprehensive rotorcraft analysis and an aeroacoustic solver, and to implement of the methodology for investigation of scissors tail rotor. Firstly, the comprehensive analysis approach is validated using available required power data and sectional blade airloads. Then, the proposed pressure distribution methodology is implemented to couple comprehensive analysis approach and acoustic solver. A CFD generated airfoil pressure database is used to find pressure distribution over each blade section. Additionally, this coupling is validated using sectional loads and acoustic pressure. Furthermore, aerodynamic and aeroacoustic behavior of the tail rotor are evaluated for isolated and main rotor interacted conventional tail rotor configuration. Finally, effects of vertical distance and scissors angle on aerodynamic and aeroacoustic behavior of the main rotor interacted scissors type tail rotor configuration are investigated. Results indicate that the main rotor wake has a significant impact on the tail rotor at certain flight conditions, and vertical distance and scissors angle changes the oscillatory loads, and there are scissors tail rotor configurations which offers lower noise level than conventional tail rotor.
Conference Paper
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A preliminary investigation of impact of piloting and flight control strategies on maneuver noise is conducted on a generic eVTOL configuration undergoing a 50 knot level-turn maneuver. The piloting strategy involved control of aircraft pitch to change split between rotor lift and wing lift, while the control strategy involved comparing a rotor thrust control with fixed pitch rotors operating with variable rotation rate and a rotor thrust control strategy with variable pitch rotors operating at constant angular velocity. With the rotors operating in the low tip-Mach number flow regime, it was revealed that broadband noise due to airfoil self-noise dominates the noise levels overwhelmingly. The turbulent boundary layer trailing edge noise contributed the most, with blade stall found to result in significant addition to noise levels (nearly 10 dBA). Deterministic noise was found to be sensitive to rotor thrust control strategies, with control biases offering an additional layer of influence over individual rotor tip-Mach number and thrust levels. Individual rotor thrust and trim were found to be important parameters controlling deterministic noise, while combined rotor thrust levels was found to be the important influence over time-averaged broadband noise levels.
Based on the FW-H equations and the CFD method, the rotor aeroacoustic characteristics during collective pitch aperiodic variation in hover are calculated and analyzed. First, a set of analysis method for aperiodic rotor aeroacoustic characteristics is developed. The aerodynamic and aeroacoustic characteristics of the BO-105 rotor in hover, the AH-1G rotor in forward flight and the NACA rotor in a ramp increase of collective pitch are calculated, and the employed numerical analysis method is validated through comparisons with experimental data. Then, the aeroacoustic characteristics of the NACA rotor during an oscillating collective pitch are analyzed, and the sound pressure peak at different collective pitch is discussed in detail. Finally, the BO-105 rotor in hover during collective pitch aperiodic variation is calculated. In addition, parameters, such as the collective pitch change rate, are quantified, and some conclusions are obtained. The configuration of collective pitch change rate will influence the directivity of rotor noise in the collective pitch increasing process, and the loading noise will be smaller if the change rate is decreasing.
Conference Paper
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The objective of this paper is to demonstrate the use of the Julia language for developing complex flight simulation models and performing flight control design. Three simulation models are developed: a simple helicopter model (J-SimpleHel), a higher-fidelity helicopter model (J-GenHel), and a fighter jet model (J-F16). These models are validated against flight test data, when available, and are used to predict the dynamic characteristics of the three aircraft in consideration. Model-following control laws are implemented for each aircraft to enhance the response characteristics.
Conference Paper
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This paper is focused on gaining a deeper understanding on how different flight procedures relate to noise generation and how helicopter rotor noise may be abated. The paper describes a noise prediction system composed of a flight simulation model, a rotor airloads and airwake model, and a rotor noise prediction code which can be used to predict the helicopter rotor noise in various flight conditions. Using this system the noise is predicted for a variety of cases and then analyzed to determine how flight operation procedures can mitigate the noise levels. This system should provide guidance that may ultimately aid pilots, operators, and land use planners to determine flight operations and maneuvers will produce less noise. The system developed is a physics-based system which quickly provides accurate noise and aerodynamic results. The computational speed of the system should also allow it to be incorporated into the design and analysis rotorcraft. INTRODUCTION For years, helicopters have been used for various missions: search and rescue, disaster relief, commercial operations, air ambulances, scientific research, and military operations. Conventional rotorcraft-especially those operating in urban environments and in military missions-can produce unwanted noise. To reduce rotorcraft noise, the development of rotorcraft noise abatement procedures through computational and analytical modeling would be very helpful. This paper highlights how noise prediction tools can aid in rotorcraft noise abatement. Using physics based tools, it is possible to inform pilots, operators, and land use planners which flight operations and maneuvers will produce less noise. The Helicopter Association International (HAI) in their "fly neighborly" program has provided guidelines on how to fly helicopters in a manner to produce less noise, but the physics based tools can give pilots both qualitative and quantitative, type-specific noise data that can be used to plan and put into practice reduced noise flight operations. Helicopter rotor noise consists of several noise sources including discrete frequency noise (thickness, loading, and blade-vortex-interaction (BVI) noise), broadband noise, and high-speed-impulsive (HSI) noise (HSI noise only occurs in high speed forward flight). Each of these noise sources has a Presented at the Sustainability 2015,
Conference Paper
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The objective of this study is the development of a virtual dynamic interface simulation using fully coupled Navier-Stokes CFD with a helicopter flight dynamics model. The results show the initial coupling of the codes and development of baseline cases. The long-term goal is to develop more efficient numeric techniques and integrate the simulation on advanced computing hardware with the objective of achieving real-time computations. The unsteady flow over the generic simple frigate shape (SFS2) was calculated using the CRAFT Tech computational fluid dynamics solver, CRUNCH CFD®. The GENHEL-PSU simulation code was integrated with the flow solution, and simulations were performed with a non-linear dynamic inversion control law to hold hover or follow a prescribed trajectory. An Actuator Disk Model with Gaussian distribution of source terms stacked vertically around the rotor disk is developed and sensitivity studies were performed for cases with the vehicle fuselage dynamics frozen. Free flight simulations were then performed, with full rotorcraft flight dynamics regulated by the NLDI controller and coupled with the CFD flow solutions. The time history results include: the helicopter hovering in an open domain both in and out of ground effect, the helicopter hovering over the SFS2 ship deck, and the helicopter performing an approach to the SFS2 ship deck. Results compare responses with no CFD coupling, using a one-way coupled CFD airwake, and using fully coupled simulations. Fully coupled simulations are shown to be feasible, to exhibit reasonable physical behavior, and to capture expected aerodynamic coupling effects.
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This paper examines the additional noise produced by a helicopter rotor during a short-time maneuver, which we call “transient maneuver noise.” A coupled flight simulation/noise prediction system was developed to predict the low-frequency noise generated during transient maneuvers. The system is partially validated for steady noise predictions in this paper. A simulation of a complex 80-second maneuver flight is performed and transient maneuver noise is identified both in the entry and exit of a coordinated turn. The characteristics of the transient maneuver noise were examined in detail by studying the turn entry. The noise generated during short-duration maneuvers is due to multiple sources: aperiodic blade motions, aircraft attitude changes, and transient aerodynamic loading. More aggressive maneuvers produce higher noise levels. The primary effect of a transient maneuver on thickness noise is to change the acoustic directivity, while both loading noise directivity and levels change significantly during aggressive maneuvers.
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Free-vortex wake models are capable of providing an accurate and physically detailed representation of the main rotor wake for flight dynamics simulation. Recent advances in computing power and efficient algorithms have made it feasible to use free wakes for real-time simulation. The CHARM free-vortex wake model was integrated with the GENHEL flight dynamics simulation of the UH-60A helicopter. A high fidelity wake model was defined by increasing the spatial and temporal resolution of the wake until a converged response was observed, but this baseline model could not execute in real-time. A parametric study was performed to find the best combination of wake parameters to achieve real-time execution with minimal deviation from the baseline model in terms of the frequency and time responses in the pitch and roll axes. A real-time model was found and showed reasonable agreement with the baseline model as compared to a simple finite-state inflow model. A parallel implementation of the free wake model was also investigated. An increase in computational efficiency could be achieved using a distributed processing approach with asynchronous communications.
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In this paper, a near-real time rotorcraft flight dynamics–acoustics prediction system is presented. Limited internal consistency checks and comparison with previous maneuver noise predictions, based on CAMRAD 2 airloads and motions, are presented to partially validate the system. A complex 80-second maneuver was used to demonstrate the capability of the coupled GENHEL–PSU-WOPWOP system. This realistic maneuver includes a climb, coordinated turn, and level flight conditions. Prediction of overall sound pressure level was performed over a region 2000 meters by 1600 meters with 8181 individual measurement locations. The noise predictions show changes in noise radiation strength and directivity due to maneuver transients, aircraft attitude changes, and the aircraft flight. A comparison of the total noise with the thickness and loading noise components helps explain the noise directivity. The computations for a single observer were very fast—although not real-time. Real-time loading noise prediction is demonstrated and the feasibility of real-time noise prediction of the total noise signal is evaluated.
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This paper presents the unique aspects of the development of an entirely new maneuver noise prediction code called PSU-WOPWOP. The main focus of this work is development of a noise prediction methodology, which will enable the study of the aeroacoustic aspects a rotorcraft in maneuvering flight. It is assumed that the aeromechanical data (namely aircraft and blade motion, blade airloads) are provided as input data. This new noise prediction capability was developed for rotors in steady and transient maneuvering flight. Featuring an object-oriented design, the PSU-WOPWOP code allows great flexibility for complex rotor configuration and motion (including multiple rotors and full aircraft motion). The relative locations and number of hinges, flexures, and body motions can be arbitrarily specified to match any specific rotorcraft. An analysis of algorithm efficiency was performed for maneuver noise prediction along with a description of the tradeoffs made specifically for the maneuvering noise problem. Noise predictions for the mainrotor of a rotorcraft in steady descent, transient (arrested) descent, hover and a “pop-up” maneuver are demonstrated.
This paper describes nonlinear dynamic inversion as an alternative design method for flight controls. The method is illustrated with super-manoeuvring control laws for the F-18 high angle-of-attack research vehicle.
Thesis (M.S.)--Pennsylvania State University, 2002. Library holds archival microfiches negative and service copy.
Existing prediction techniques are compiled and described. The descriptions include input and output parameter lists, required equations and graphs, and the range of validity for each part of the prediction procedures. Examples are provided illustrating the analysis procedure and the degree of agreement with experimental results.