PROCEEDINGS of the23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Future low-noise aircraft technologies and procedures –Perception-based evaluation using auralised flyovers
Reto PIEREN1; Lothar BERTSCH2; Demian LAUPER1; Beat SCHÄFFER1
1

Empa, Swiss Federal Laboratories for Materials Science and Technology, 8600 Dübendorf, Switzerland.
2

German Aerospace Center (DLR), 37073 Göttingen, Germany.

ABSTRACT
Residents living in the vicinity of airports are exposed to noise from departing and approaching aircraft.
Noise may be reduced by introducing novel aircraft technologies and flight procedures. By means ofauralisation and listening experiments, such possible future changes can be evaluated by considering humansound perception. In this study, flyovers of different aircraft types and flight procedures were auralised at
multiple virtual observer locations, and subsequently evaluated in a psychoacoustic laboratory experimentwith respect to short-term noise annoyance. An existing reference aircraft, a possible low-noise retrofitted
version and a future low-noise design were simulated along standard and tailored approach procedures.
Separate source signals were synthesised for engine broadband, fan tonal, airframe broadband, and cavity
tonal noise. Further, smooth transitions between consecutive changes in configurational setting andoperational condition were modelled to create realistic sounds. To enhance plausibility, the propagation
simulation, amongst other effects, considered ground reflections and frequency-dependent amplitude
modulation due to propagation through a turbulent atmosphere. The flyover sounds were spatially
reproduced by a hemispherical loudspeaker array. The listening experiment revealed significant annoyance
reductions for low-noise aircraft types and flight procedures, that maximal benefit is achieved by thecombined optimisation of aircraft technology and procedure, and that distributed observers need to beconsidered.
Keywords: Simulation, Aircraft noise, Perception, Auralisation, Noise annoyance

1. INTRODUCTION
Residents living in the vicinity of airports are exposed to noise from departing and approachingaircraft. Aircraft noise may be reduced by introducing novel aircraft designs and flight procedures. Bymeans of auralisation and listening experiments, such possible future changes can be evaluated byconsidering the human perception of sound. Using such information to steer the aircraft technology
development process has recently been denoted as perception-influenced design (1).
In this study, flyovers of different aircraft types and different flight procedures are auralised, andsubsequently evaluated in a psychoacoustic laboratory experiment. Within the presented study, theassessment focuses on approaching aircraft due to their increased complexity caused by the varying
mixture of noise sources.

2. PERCEPTION-BASED EVALUATION PROCESS
Figure 1 illustrates the simulation process followed in this study. Starting with preselected Top
Level Aircraft Requirements (TLAR), which contain e.g. mission range and number of passengers, airvehicles are designed on a physical feasible basis with the software framework PrADO (2). Approachand departure trajectories with underlying configurational settings, such as engine operation or
high-lift usage, are simulated and optimised with the integrated FlipNA code (3). By auralisation,
flyovers of the designed aircraft and procedures are artificially rendered audible in a virtual acousticenvironment. This involves a sound source prediction, emission synthesis, propagation simulation andsound reproduction (see Section 3). Acoustic stimuli in the form of spatial sound fields of virtual
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reto.pieren@empa.ch

flyovers allow a psychoacoustic evaluation in listening experiments. Resulting perception-based
assessments are used to improve the simulation modules and ultimately also to optimise low-noise
aircraft technologies.
The focus of this paper lies on the developed auralisation strategy for flyovers of jet aircraft (4). A
comprehensive description of the concept is currently being prepared for publication elsewhere (5).

Figure 1 – Concept for perception-based evaluation of future low-noise aircraft designs and flight procedures(TLAR = Top Level Aircraft Requirements).

3. AURALISATION OF FLYOVERS OF JET AIRCRAFT
3.1 Emission synthesis
The simulation follows the source-path-receiver concept. Noise sources are predicted along theaircraft trajectory. In contrast to noise mapping applications, auralisation requires high time andfrequency resolutions, and source descriptions with high temporal continuity (4).
Emissions of the major noise sources are calculated by the aircraft noise prediction tool PANAM(6). PANAM contains parametric calculation models for various componential noise sources of anaircraft. Engine and airframe noise sources are separately described as a function of aircraft design
geometries and operational conditions. The componential noise sources are condensed into threecontributions: (i) airframe broadband, (ii) engine broadband, and (iii) engine fan tones. Radiation
angle-specific spectral sound emission levels are calculated in source time steps of 0.5 s. On that basis,
source sound pressure signals for contributions (i) and (ii) are generated by subtractive synthesis
where pink noise signals are spectrally shaped with a 1/3 octave band filter bank. The sound pressuresource signal of the first five fan tones, p em,fantones, is generated using additive synthesis by fivenumerically controlled oscillators with amplitude and frequency controls (7):k5pem,fantones [k]=ξ2p0 ෍ 10
j=1

Lem,fantone,j [k]/20

2ʌjcos ቌĳj +෍ fBPF [k']ቍ
fs(1)

̵=0

with the signal sample indices k and k’, the reference pressure p0 = 20 μPa, the fan tone emission levels
Lem in dB, a random initial phase angle ĳ in radians, the audio sampling rate fs in Hz, and the fan blade
passing frequency f BPF in Hz.
Also relatively small structures at the airframe may lead to relevant narrowband aero-acoustic
sources. One example is the wing cavity tones originating from fuel overpressure ports (FOPP) in theAirbus A320 family (8,9). The sound power of this double tone shows a strong speed dependency. For
example, an airspeed increase from 80 to 100 m/s leads to a 10 dB increase in sound power. Initialattempts to synthesise cavity tones using additive synthesis failed, because listening comparisons torecordings revealed a very different hearing impression. In fact, cavity tones are generated by aHelmholtz resonator excited by a grazing airflow, featuring a random excitation pattern and a certain
spectral bandwidth. Following this conception, in the developed synthesis model cavity tones aregenerated by subtractive synthesis with white noise as basic waveform and peak filters of the form
(Laplace notation):

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Ȧ20Hpeak (s)= 2s +2ȗȦ0 s+Ȧ20(2)with the Laplace variable s, the peak angular frequency Ȧ0 , and the damping ratio ȗ used to set thebandwidth to about 2 Hz (see synthesis example in Figure 2). The synthesis parameters for the wing
cavity tones are set based on field measurements (10,11).
40
Measured receding A320
Synthesized source
Measured approaching A320

Sound pressure level, dB/Hz

3530
25
2015
10
50300

400

500

600

700

800

900

1000

Frequency, HzFigure 2 – Narrowband sound pressure spectra with distinct wing cavity tones as measured from an Airbus
A320 at Mach 0.3 during approach. The Doppler effect shifts the two peaks from around 800 Hz (red) to 400
Hz (green) during the flyover event. Simulated data at Mach 0.3 by the developed synthesis model is shownin black (without Doppler effect).
3.2 Propagation filtering
The model conception behind the propagation simulation is that the most relevant propagation
effects are independently described and modeled, similarly to current engineering propagation models.
Time-variable propagation filters transform the source (emission) sound pressure signal into anobserver sound pressure signal. The considered propagation effects are Doppler frequency shift,geometrical spreading, air absorption, ground effect and turbulence effect (7,12).
Attenuation due to atmospheric absorption is modelled for a stratified atmosphere described by thecollection of height profiles for air temperature, relative humidity and static pressure. The effective
atmospheric absorption coefficient is integrated along the propagation path using 20 vertical sampling
points. From the atmospheric attenuation spectrum, an FIR filter with 1024 taps (at a sampling rate
f s = 48 kHz) is designed using the IFFT. The filter taps are updated every 200 ms.
Wave propagation through a turbulent atmosphere leads to distinctly audible amplitude
modulations (AM). This effect was included to enhance plausibility of the hearing impression. The
developed model considers that turbulence-induced AM is of random nature and depends on frequency
and the propagation distance. Turbulence-induced AM is modeled by a high shelf filter with
distance-dependent transition frequency and a random, time-dependent gain (12). A minimum phasefirst-order IIR filter is used here with the transfer functionȦc +10G(t)/20 s(3)Ȧc +swith the Laplace variable s, the high-frequency gain G in dB, and the angular transition frequency
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Ȧc =2ʌ(4)ඥd(t)
Htturb ሺsሻ=

where d is the source–receiver distance in meter. The gain G is created with a random process and isnormally distributed with standard deviation ı and mean value μ = í0.115ı2 , to ensure
energy-neutrality of the turbulence effect.
3.3 Reproduction
To create a perceivable sound field, the (monophonic) sound pressure signal is distributed to a 3D

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loudspeaker array using directional information of sound incidence (time histories of azimuth andelevation angle). The 3D reproduction rendering is accomplished by dual-band amplitude panningwhere different normalisations are used for two frequency bands (13). The low frequency content issplit off with a digital crossover (Linkwitz-Riley filters at 100 Hz) as subwoofer feed.
3.4 Application
A listening experiment with 32 subjects was performed in the listening test facility AuraLab at
Empa in Switzerland. The sound reproduction system consisted of an upper-hemisphere layout with 15
satellite speakers (Neumann, KH 120 A) and two subwoofers (Neumann, KH 805) that were connected
to a digital audio processor (Xilica, Neutrino A0816). The listening room features high structure- andairborne sound insulations, low background noise (below 7 dBA, GK0) and controlled room acoustics
with a reverberation time of T mid = 0.11 s.
The subjects rated short-term noise annoyance of individual flyover events on the ICBEN 11-point
numerical scale (14). Approaches of three civil tube-and-wing narrow-body aircraft with two flightprocedures each and four observer locations were examined, making a total of 24 virtual flyovers.
No suspicious comments or remarks about plausibility were given by any of the subjects during orafter the experiment, even though most had personal experience with aircraft noise. Furthermore, in a
specific technical workshop, acousticians and aircraft noise experts rated the acoustic stimuli as “veryplausible”.
Exemplary results of the listening experiment are shown in Figure 3. The novel aircraft design
performs significantly better in terms of noise annoyance compared to the reference aircraft (similar toan existing A319-100). At distances closer than 15 km to the touch-down point, the tailored flightprocedure leads to an additional improvement. However, this is not the case at larger distances,
showing that distributed observer locations need to be considered for the assessment of low-noise
aircraft technologies. Note that for this initial application example, only observer locations below theflight trajectory are assessed.

Figure 3 – Observed (symbols) mean short-term noise annoyance ratings for two aircraft types (Referenceand Game changer) and two flight procedures (Standard and Tailored) at four observer locations. The curves
show modelled data including confidence intervals.

4. CONCLUSIONSIn this study, a methodological approach for perception-based evaluation of future low-noise
aircraft technologies was developed that involves, amongst others, enhanced auralisation models.
Flyovers of different aircraft types with different approach procedures were successfully auralised at
multiple virtual observer locations. Although the flyover sounds were fully synthetically generated,
they were perceived as plausible. A listening experiment revealed significant reductions in short-termannoyance for low-noise aircraft types and flight procedures, that maximal benefit is achieved by thecombined optimisation of aircraft technology and procedure, and that spatially distributed observers

1657need to be considered to reliably assess low-noise aircraft noise technologies and procedures. Future
work will furthermore include observer locations aside the flight ground track, departure procedures
and different propulsion concepts, e.g., geared turbofan or propeller engines.

ACKNOWLEDGEMENTS
The work of Empa was partly funded by the Swiss Federal Office for the Environment (FOEN). The
DLR activity was supported via a travel budget by the Projektförderung zur Internationalen
Zusammenarbeit (PiZ). Some of the joint work was performed in the context of the project ARTEM,
which has received funding from the European Union's Horizon 2020 research and innovation
programme under grant agreement No. 769350.

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