The human perception of two wind turbines of different sizes, a small NTK turbine and a larger NREL model, was evaluated through their synthetically auralised sound. A wide range of wind speed conditions and observer locations was considered. The simulated sounds were analyzed using equivalent sound pressure levels and psychoacoustic sound quality metrics. Moreover, listening experiments were conducted to evaluate the human response to the same sounds. The least-squares models fitted to the results provided scaling laws for the different sound metrics as a function of wind speed (divided into low- and high-speed regimes) and distance to the observer. At lower wind speeds, the NREL turbine’s noise and annoyance levels increase faster with increasing wind speed than the NTK turbine. The results of the NREL turbine at high wind speeds seem to indicate that turbulent boundary layer trailing-edge noise contributes more to annoyance than leading edge turbulent inflow noise. In the listening experiments, the larger wind turbine was perceived roughly 30% more annoying than the smaller one for the same conditions. The equivalent A-weighted sound pressure level and the psychoacoustic annoyance model by Zwicker were reported to closely represent the annoyance ratings reported in the listening experiment.

The influence of ambient noise in the perception of wind turbine noise is evaluated in this exploratory study. For this purpose, experimental field measurements of an NTK wind turbine at different wind speeds and background noise levels are considered. Synthetic wind turbine noise auralizations are then computed to replicate the weather and operational conditions during the experiments. Different background noise recordings were then synthetically added to the simulated auralizations to investigate the effect in sound quality metrics, such as loudness, roughness, or the psychoacoustic annoyance model by Zwicker. A least-squares analysis was applied to the resulting sound signals. It was found that adding background noise to the auralisations notably reduced the differences in metrics between simulations and experiments. However, the behaviour with respect to the A-weighted signal-to-noise ratio then becomes background-noise dependent and, hence, more challenging to predict. Therefore, for perceptual studies, it is recommended to use experimental recordings with low background noise as a ground truth.

The application of an acoustically absorbent material (melamine foam) is investigated for the treatment of turbulence grids in an anechoic open-jet wind tunnel facility featuring an axisymmetric contraction. A comparative study of both the generated turbulence and the grids’ self-noise is performed. It is found that the application of melamine foam on the downstream side of the grids marginally affects the produced turbulence, while providing an efficient suppression of tonal peaks in the grids’ self-noise spectrum. Broadband noise levels instead show opposing trends depending on the frequency range considered. On the one hand, a general decrease due to the acoustic treatment is observed for Strouhal numbers lower than unity. On the other, an increase, in the form of broad peaks, is seen to occur over certain higher frequency ranges.

The far-field acoustic emissions of an isolated scale-model propeller ingesting turbulent inflow are experimentally investigated in wind-tunnel measurements. Phase-averaging and phase-shifting signal processing techniques are used to separate the deterministic (tonal) and random (broadband) components of the recorded sound signals. It is reported that a combination of the two techniques prevents tones unrelated to the shaft rotational frequency from contaminating the estimate of the broadband part of the signal. Scaling and directivity analyses of the obtained broadband component highlight the presence of two noise generation regimes depending on the considered frequency range. In particular, a quasi-omnidirectional directivity pattern is observed for frequencies for which the Helmholtz number is much lower than unity when turbulence is ingested. On the other hand, a dipole-like pattern with minima close to the propeller’s rotational plane gradually appears for higher frequencies. A time- and frequency-domain analysis through the Continuous Wavelet Transform (CWT) method shows how the increase in broadband noise is due to a large number of short-duration pulses linked to the ingestion of turbulence.

The far-field acoustic emissions of a six-bladed propeller were investigated in aeroacoustic experiments in an openjet wind tunnel. The propeller was operating in different isotropic inflow turbulence conditions generated by turbulence grids placed upstream of the exit plane of the wind tunnel nozzle. In addition, the collective pitch angle of the propeller blades was also varied throughout the measurements. A preliminary directivity analysis of different acoustic and psychoacoustic metrics was performed to investigate the influence of the inflow turbulence intensity and collective pitch angle on the noise emissions and sound perception. In general, increasing the inflow turbulence levels did not modify the conventional metrics recorded, e.g. equivalent sound pressure level. Nevertheless, it considerably increased the broadband noise emissions of the propeller, the loudness, and the overall psychoacoustic annoyance metrics. However, notable reductions in tonality (due to partial tone masking because of the higher levels of broadband noise) and sharpness were reported for increasing turbulence intensities. Overall, this analysis is valuable for the perception-influenced design of devices equipped with propellers, such as drones or urban air mobility vehicles, to account for installation effects.

The issue of acoustic reflections caused by an axisymmetric nozzle is addressed both numerically and experimentally. The contraction (with an exit diameter of 420 mm and a contraction ratio of 2) is representative of typical open-jet wind tunnel exits. Such a category of wind tunnels are extensively used in aeroacoustic studies due to the possibility of acoustic treatment of the test chamber (plenum) walls and the placement of acoustic sensors outside of the flow. The distance between the wind tunnel’s nozzle exit and the model being tested is usually limited to around one hydraulic diameter in order for the model to be fully contained within the exit jet’s core. Partly for this reason, the wind tunnel nozzle normally protrudes inside the anechoic plenum to distance the tested model from the (acoustically-treated) walls. This effectively creates a cavity, which is in communication with the test section. Acoustic simulations through a commercial finite-element code (COMSOL Multiphysics) show that the presence of the nozzle leads to interference patterns within the test section and a substantial modification of a source’s measured directivity pattern. Experimental measurements in a fully anechoic chamber confirm these results. Melamine foam inserts on both the exit flange and part of the inner walls of the contraction are shown to mitigate the issue partly.

The increasing adoption of electric vehicles (EVs), which operate more quietly than internal combustion engine vehicles, raises concerns about their detectability, particularly for visually impaired road users. Regulations mandate exterior sound signals for EVs, ensuring minimum sound pressure levels at low speeds. However, these signals are often used in already noisy urban environments, creating a challenge: enhancing detectability without adding excessive noise pollution. This study explores the use of synthetic exterior sounds that balance high noticeability with low annoyance. An audiovisual experiment was conducted with 20 participants in 15 virtual reality scenarios featuring an EV passing in front of them. Different sound signals, including pure, intermittent, and complex tones at varying frequencies, were tested alongside two baseline cases (a diesel engine and tyre noise alone, i.e., no synthetic sound added). Participants rated sounds for annoyance, noticeability, and informativeness using 11-point ICBEN scales. Trigger measurements provided additional insights into their willingness to cross in front of the EV. The results highlight optimal sound characteristics for EVs, offering guidance on improving pedestrian safety while minimising noise pollution. By refining exterior sound design, this research contributes to the development of effective and user-friendly EV sound standards, ensuring safer and more inclusive urban environments.

Novel propulsion concepts are being developed for urban air mobility (UAM). This study analyses the noise emissions of a virtual UAM vehicle equipped with 26 distributed, ducted, low-speed fans. Synthetic flyover sounds are generated using an auralization framework, which involves noise predictions, sound propagation, and the binaural audio rendering at the observer position. Since noise emissions of distributed propulsion are characterized by interference effects, this paper discusses the influence of rotational speed fluctuations of the distributed fans on the sound perception of the auralized sounds. These rotational speed fluctuations are modelled as different ranges of random and constant deviations from the nominal speed, in contrast to the baseline case with the 26 fans operating synchronously. The results of a listening experiment performed to evaluate the perceptual differences between the different configurations seem to indicate that relatively small fluctuations in the rotational speed of the fans (e.g. $\pm1\%$ with respect to the nominal rpm) already notably improve the perceived noise annoyance. The observed differences in annoyance ratings are reasonably well explained by sound metrics that consider the tonal nature of sound, such as the effective perceived noise level (EPNL), tonality, and the psychoacoustic annoyance model by Di et al.

Psychoacoustic listening experiments were conducted to investigate the human response to propeller noise under turbulent inflow conditions. The sound stimuli considered were recorded in aeroacoustic wind tunnel experiments featuring an isolated six-bladed propeller. The propeller operated under different isotropic inflow turbulence conditions and collective blade pitch angles. Higher inflow turbulence intensity levels caused a growth in the broadband noise emissions of the propeller, increasing the overall loudness levels. On the other hand, sharpness and tonality consistently decreased due to the increase in low-frequency noise and the tone-masking effect by the aforementioned broadband noise, respectively. The listening experiments aimed to elucidate the effect of these contradicting trends on sound perception. It was observed that lower noise annoyance ratings were reported for higher inflow turbulence intensity levels and lower collective blade pitch angles. Overall, only the tonality metric provided a statistically significant correlation with the annoyance ratings, indicating the importance of this perceptual aspect in propeller noise, in combination with loudness and sharpness. Other energy-based sound metrics, like the effective perceived noise level, failed to correctly describe the results of the listening experiment. In general, this analysis is valuable for the perception-influenced design of devices equipped with propellers.

The growing adoption of electric vehicles, known for their quieter operation compared to internal combustion engine vehicles, raises concerns about their detectability, particularly for vulnerable road users. To address this, regulations mandate the inclusion of exterior sound signals for electric vehicles, specifying minimum sound pressure levels at low speeds. These synthetic exterior sounds are often used in noisy urban environments, creating the challenge of enhancing detectability without introducing excessive noise annoyance. This study investigates the design of synthetic exterior sound signals that balance high noticeability with low annoyance. An audiovisual experiment with 14 participants was conducted using 15 virtual reality scenarios featuring a passing car. The scenarios included various sound signals, such as pure, intermittent, and complex tones at different frequencies. Two baseline cases, a diesel engine and only tyre noise, were also tested. Participants rated sounds for annoyance, noticeability, and informativeness using 11-point ICBEN scales. The findings highlight how psychoacoustic sound quality metrics predict annoyance ratings better than conventional sound metrics, providing insight into optimising sound design for electric vehicles. By improving pedestrian safety while minimising noise pollution, this research supports the development of effective and user-friendly exterior sound standards for electric vehicles

Aircraft noise annoyance is inherently subjective, and its accurate quantification represents a challenging task. There is a lack of consensus in the scientific community regarding which metrics are best for effectively representing this type of annoyance. The present study aims at relating various sound metrics to noise annoyance ratings measured in listening experiments featuring 60 aircraft flyover recordings (30 landings and 30 takeoffs). This is done by considering different sound quality metrics (SQMs), psychoacoustic annoyance models, and more conventional noise certification metrics, such as the effective perceived noise level (EPNL) or the sound exposure level. A correlation analysis was subsequently performed on a large pool of sound metrics considering both linear and non-linear functions. The results show that, in general, metrics derived from psychoacoustic annoyance models (especially those proposed by Zwicker and Di et al.) present considerably better correlations compared to conventional metrics and most individual SQMs. The metrics of loudness, EPNL, and maximum perceived noise level (PNL) also exhibit strong correlations and capacity to predict a substantial portion of the variance observed in the reported annoyance ratings. Moreover, considering non-linear functions (e.g. logarithmic or hyperbolic tangent power) further improves the prediction performance.

The growing adoption of electric vehicles, known for their quieter operation compared to internal combustion engine vehicles, raises concerns about their detectability, particularly for vulnerable road users. To address this, regulations mandate the inclusion of exterior sound signals for electric vehicles, specifying minimum sound pressure levels at low speeds. These synthetic exterior sounds are often used in noisy urban environments, creating the challenge of enhancing detectability without introducing excessive noise annoyance. This study investigates the design of synthetic exterior sound signals that balance high noticeability with low annoyance. An audiovisual experiment with 14 participants was conducted using 15 virtual reality scenarios featuring a passing car. The scenarios included various sound signals, such as pure, intermittent, and complex tones at different frequencies. Two baseline cases, a diesel engine and only tyre noise, were also tested. Participants rated sounds for annoyance, noticeability, and informativeness using 11-point ICBEN scales. The findings highlight how psychoacoustic sound quality metrics predict annoyance ratings better than conventional sound metrics, providing insight into optimising sound design for electric vehicles. By improving pedestrian safety while minimising noise pollution, this research supports the development of effective and user-friendly exterior sound standards for electric vehicles.

Distributed propulsion systems are developed to power a new generation of aircraft. However, it is not known yet which noise emissions these propulsion systems produce, which psychoacoustic characteristics such systems exhibit, and how the generated noise is perceived. This paper investigates how fans with fewer stator than rotor blades affect the noise perception of a distributed propulsion system intended for an urban air mobility vehicle, which is equipped with 26 low-speed ducted fans. Three fan designs with different tonal to broadband noise ratio and opposite dominant noise radiation directions are examined. An analytical process is applied to determine the noise emission, propagate the sound through the atmosphere, auralize the flyover signals, and calculate psychoacoustic metrics. A validation and comparison with A320 turbofan engines at takeoff is provided. The results indicate that the distributed propulsion system generates noise signatures with complex directional characteristics and high sharpness. By applying tonal noise reduction mechanisms at source, a significant effective perceived noise level reduction is achieved for the considered fan stages with fewer stator than rotor blades. In addition, tonality, loudness and roughness are reduced well above one noticeable difference compared to a baseline fan and similar or even lower values are achieved than with turbofans.

This study investigates the relationship between sound quality metrics (SQMs) and noise annoyance caused by airborne wind energy systems (AWESs). In a controlled listening experiment, 75 participants rated their annoyance on the International Commission on Biological Effects of Noise (ICBEN) scale in response to recordings from in-field measurements of two fixed-wing and one soft-wing ground-generation AWES. All recordings were normalized to an equivalent A-weighted sound pressure level of 45 dBA. The results revealed that sharpness was the only SQM predicting participants' annoyance. Fixed-wing kites, characterized by sharper and more tonal and narrowband sound profiles, were rated as more annoying than the soft-wing kite, characterized by higher loudness values. In addition, the effect of some SQMs on annoyance depended on participant characteristics, with loudness having a weaker impact on annoyance for participants familiar with AWESs and tonality having a weaker effect on annoyance for older participants. These findings emphasize the importance of considering psychoacoustic factors in the design and operation of AWESs to reduce noise annoyance.

An experimental aeroacoustic study on the influence of the collective blade pitch angle in the noise emissions by an isolated propeller under different turbulent inflow conditions is presented. Acoustic and aerodynamic measurements are conducted in an anechoic, open-jet wind tunnel facility. Different inflow turbulence characteristics are achieved by employing square-mesh, square-bar turbulence grids positioned ahead of an additional 2:1 contraction at the wind tunnel's exit. It is found that the ingestion of grid-generated turbulence does not significantly impact the thrust produced by the propeller for any of the tested collective blade pitch angles. On the other hand, turbulence ingestion greatly increases noise production in both broadband and tonal components. The grouping of broadband noise around the Blade Passing Frequency (BPF) and its harmonics ("haystacking'') does not prove to be a phenomenon of particular relevance in grid-generated turbulence ingestion. A directivity analysis shows that an increase in inflow turbulence intensity is responsible for increased noise emissions downstream of the propeller.

Experimental aeroacoustic measurements conducted in wind tunnels are crucial for informing the design process of various devices, including aircraft components or wind turbine blades. Whereas closed-section wind tunnels typically offer better aerodynamic conditions compared to their open-jet counterparts, they often introduce challenges related to noisier test environments and the optimal placement of acoustic sensors, such as microphone arrays, within the test section. As advancements in noise reduction measures lead to quieter test models and our knowledge regarding the location of their main noise sources improves, accurately quantifying the sound sources within these models becomes increasingly important. The present manuscript offers valuable guidelines aimed at enhancing the precision of sound source quantification. It provides practical recommendations regarding microphone placement and the utilization of post-processing techniques, such as manipulations of the cross-spectral matrix. The experimental setup consists of an array of 16 microphones in two different configurations (flush-mounted and recessed in cavities). To assess the quantification accuracy, a speaker playing broadband noise at different sound pressure levels outside of the flow serves as a known reference sound source. A wide range of signal-to-noise ratios (SNRs) are achieved by employing different flow velocities and speaker settings. The results indicate that relatively accurate sound source quantification can be achieved with SNRs down to −10 dB. Lastly, a scaling law for the expected quantification error is proposed in terms of the number of microphones within the array and the SNR. In this manner, the experimental setup can be adapted accordingly to obtain the required level of accuracy.

This manuscript summarizes the main recent research efforts at Delft University of Technology in the field of drone and urban air mobility (UAM) vehicle noise. Illustrative examples are showcased, specifically in terms of acoustic measurements (both in-field and in wind-tunnel facilities), noise modelling (both data-driven and physics-based), and human perception of these sounds. In particular, the measurements feature microphone arrays and acoustic imaging to detect, localize, and isolate drone noise emissions. Regarding drone noise modelling, the proposed approaches cover noise generation, propagation, and acoustic footprint calculation. The evaluation of the human perception of drone noise and the perceived annoyance is another crucial aspect. To this end, psychoacoustic listening experiments are conducted in laboratory conditions and the results are analyzed using perception-based sound metrics. Data from aeroacoustic measurements and synthetic sound auralizations are considered. Combining these three main approaches holistically, the perception-driven design and assessment can be performed by targeting the minimization of the perceived noise annoyance, rather than merely reducing sound pressure levels.

Current validation of wind turbine noisemodels primarily focuses on sound levels averaged over time, typicallyexpressed in metrics such as the equivalent A-weighted sound pressure level(LA,eq). Whereas valid for regulatory purposes, these methods are notsufficient for psychoacoustic research, as time-averaged levels alone do notfully explain the measured noise annoyance. Therefore, this research aims toestablish whether psychoacoustic sound quality metrics (SQMs) provideadditional value when analysing wind turbine noise models. This work employsthe Horizontal Axis Wind turbine simulation Code 2 (HAWC2) to generate noisesource spectrograms, which are propagated through the atmosphere with aGaussian beam-tracing approach. The final sound signals are retrieved throughan inverse Short-Time Fourier Transform (iSTFT). This methodology is applied toa case study featuring a stall-controlled, horizontal-axis, Nordtank NTK 500/41wind turbine. The results are evaluated against measurements by consideringLA,eq, SQMs, and a comparative listening experiment. The LA,eq metric shows aconsistent underprediction of the simulations with respect to measurements,which is partly explained by a ground reflection modelling error. In thehigh-frequency range, stall noise is known to be significantly underpredictedby the aero-acoustic simulation model. This usually translates in increasingdiscrepancies between measurements and models as the wind speed increases. Thecomparative listening experiment confirms that participants experience thesimulations and the measurements as significantly different. The differenceratings show a good agreement with the differences in the psychoacousticannoyance and loudness metrics. It is more difficult to relate the results fromthe listening experiment to LA,eq. These findings confirm that an evaluationwith psychoacoustic metrics next to conventional methods provides additionalvalue in validating wind turbine noise models for human perception research.

In recent years, the search for more sustainable propulsion systems for aviation has led to an increased interest in electric propulsion aircraft. These aircraft are often claimed to be more silent due to the lack of an internal combustion engine which eliminates the combustion and exhaust noise. However, the dominant noise source for single-propeller aircraft, independent of the propulsion method, is often the propeller itself. Additionally, lower noise levels simply assessed with conventional sound metrics like the sound pressure levels might not necessarily correspond to lower noise annoyance. Therefore, this research investigates the noise levels and expected psychoacoustic annoyance of the electric aircraft Pipistrel Velis in comparison to its fuel-burning counterpart, the Pipistrel Virus. The Velis can serve as a direct replacement for the Virus as they have the same number of seats and the same take-off weight, raising the question of what the effect of this replacement is on community noise annoyance. The research is based on experimental measurements during flyovers of both aircraft. Overall, it was found that the Velis is found to have lower noise emissions and lower psychoacoustic annoyance according to its sound quality metrics. This is reflected in the loudness, tonality, and impulsiveness, likely due to the presence of fewer tones below 500 Hz.

The current study reports the results of a psychoacoustic listening experiment investigating the human response to the noise emissions from various types of drone flyovers, recorded during acoustic field experiments. The investigation covers six quadcopters with single propellers, a quadcopter with counterrotating propellers, and two types of hybrid electric vertical take-off and landing (eVTOL) drones. These recorded audio samples were employed in a dedicated listening experiment conducted at the Psychoacoustic Listening Laboratory (PALILA) in the faculty of Aerospace Engineering of Delft University of Technology, involving 57 participants. The two eVTOL drones were perceived as considerably less annoying than their quadcopter counterparts, whereas the coaxial-propeller quadcopter was found to be the most annoying drone. Strong correlations were found between the mass and volume of the quadcopter drones and the annoyance ratings from the listening experiments. Psychoacoustic annoyance metrics from different models proved to predict the perceived noise annoyance more accurately than conventional sound metrics typically employed in noise assessment.