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F. Yunus
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1
This paper presents a language-model-inspired data-driven surrogate for predicting tonal and broadband noise from an isolated propeller as a function of blade geometry, operating condition, and receiver position. The model predicts acoustic spectra directly on a fixed frequency grid and represents the spectrum through tokenized broadband and tonal branches, deterministic harmonic rendering, and recombination in linear acoustic power. This formulation retains harmonic-level spectral information while imposing physically motivated structure on the predicted tonal--broadband decomposition. To improve low-order tonal fidelity, the tonal pathway incorporates geometry-, operating-, and directivity-aware inductive structure. Measured spectra provide the primary supervision, while auxiliary Ffowcs Williams--Hawkings (FW--H) simulation data are used only in restricted supporting roles for broadband pretraining and directivity regularization. When evaluated on a held-out, unseen propeller, the model achieves competitive accuracy for both raw spectra and one-third-octave levels while preserving physically interpretable harmonic ordering and broadband trends. The results demonstrate the potential of language-model-inspired spectral tokenization for low-data propeller aeroacoustic surrogate modeling, while indicating that broader generalization will require larger and more systematically sampled measured or high-fidelity synthetic datasets.
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This paper presents a language-model-inspired data-driven surrogate for predicting tonal and broadband noise from an isolated propeller as a function of blade geometry, operating condition, and receiver position. The model predicts acoustic spectra directly on a fixed frequency grid and represents the spectrum through tokenized broadband and tonal branches, deterministic harmonic rendering, and recombination in linear acoustic power. This formulation retains harmonic-level spectral information while imposing physically motivated structure on the predicted tonal--broadband decomposition. To improve low-order tonal fidelity, the tonal pathway incorporates geometry-, operating-, and directivity-aware inductive structure. Measured spectra provide the primary supervision, while auxiliary Ffowcs Williams--Hawkings (FW--H) simulation data are used only in restricted supporting roles for broadband pretraining and directivity regularization. When evaluated on a held-out, unseen propeller, the model achieves competitive accuracy for both raw spectra and one-third-octave levels while preserving physically interpretable harmonic ordering and broadband trends. The results demonstrate the potential of language-model-inspired spectral tokenization for low-data propeller aeroacoustic surrogate modeling, while indicating that broader generalization will require larger and more systematically sampled measured or high-fidelity synthetic datasets.
This paper presents a computational aeroacoustic approach for investigating rotor--rotor and rotor--airframe aeroacoustic interactions in a lift-and-cruise UAV configuration representative of a full-scale vehicle, using wind-tunnel noise measurements and hybrid aeroacoustic modeling. The computational framework couples the lattice Boltzmann method with an actuator-line model to resolve aerodynamic interactions among lifting rotors, the airframe, and a pusher propeller. The acoustic field is predicted using stationary permeable data surfaces within a frequency-domain formulation of the convected Ffowcs Williams--Hawkings equation. The approach is evaluated using two configurations: a 35\%-scale isolated propeller, which establishes baseline aerodynamic and acoustic accuracy, and a lift-and-cruise aircraft representative of a full-scale vehicle, with a truncated wingspan, two lifting rotors, and a pusher propeller. The lift-and-cruise measurements and simulations are used to identify installation and interaction effects on the radiated noise. Results show that the airframe increases tonal noise and introduces additional interharmonic spectral components, particularly beyond the sixth blade-passing-frequency harmonic. These findings demonstrate the importance of resolving rotor--rotor and rotor--airframe interaction mechanisms in multi-rotor noise prediction. Overall, the developed framework provides an efficient and reliable predictive capability for assessing aerodynamic interaction mechanisms and their acoustic impact in advanced air mobility vehicle design.
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This paper presents a computational aeroacoustic approach for investigating rotor--rotor and rotor--airframe aeroacoustic interactions in a lift-and-cruise UAV configuration representative of a full-scale vehicle, using wind-tunnel noise measurements and hybrid aeroacoustic modeling. The computational framework couples the lattice Boltzmann method with an actuator-line model to resolve aerodynamic interactions among lifting rotors, the airframe, and a pusher propeller. The acoustic field is predicted using stationary permeable data surfaces within a frequency-domain formulation of the convected Ffowcs Williams--Hawkings equation. The approach is evaluated using two configurations: a 35\%-scale isolated propeller, which establishes baseline aerodynamic and acoustic accuracy, and a lift-and-cruise aircraft representative of a full-scale vehicle, with a truncated wingspan, two lifting rotors, and a pusher propeller. The lift-and-cruise measurements and simulations are used to identify installation and interaction effects on the radiated noise. Results show that the airframe increases tonal noise and introduces additional interharmonic spectral components, particularly beyond the sixth blade-passing-frequency harmonic. These findings demonstrate the importance of resolving rotor--rotor and rotor--airframe interaction mechanisms in multi-rotor noise prediction. Overall, the developed framework provides an efficient and reliable predictive capability for assessing aerodynamic interaction mechanisms and their acoustic impact in advanced air mobility vehicle design.
This paper investigates the prediction accuracy and time efficiency of two distinct low-fidelity methods for predicting the tonal and broadband noise of a drone rotor in axial and non-axial inflow conditions. These are both derived from an aerodynamic rotor model based on the blade element momentum theory, respectively coupled with a time- and a frequency-domain solution of the Ffowcs Williams-Hawkings integral equation applied to a radial distribution of acoustically compact and non-compact sources. Experimental data and scale resolving
lattice-Boltzmann/very-large eddy simulation results for a two-bladed small unmanned aerial system in transitional boundary layer conditions are used to validate the low-fidelity approaches. Comparison between low-fidelity, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modeled by the low fidelity methods, which therefore constitute a valid tool for the preliminary design of quiet drone rotors and for the estimation of the community noise impact of drone operations. ...
lattice-Boltzmann/very-large eddy simulation results for a two-bladed small unmanned aerial system in transitional boundary layer conditions are used to validate the low-fidelity approaches. Comparison between low-fidelity, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modeled by the low fidelity methods, which therefore constitute a valid tool for the preliminary design of quiet drone rotors and for the estimation of the community noise impact of drone operations. ...
This paper investigates the prediction accuracy and time efficiency of two distinct low-fidelity methods for predicting the tonal and broadband noise of a drone rotor in axial and non-axial inflow conditions. These are both derived from an aerodynamic rotor model based on the blade element momentum theory, respectively coupled with a time- and a frequency-domain solution of the Ffowcs Williams-Hawkings integral equation applied to a radial distribution of acoustically compact and non-compact sources. Experimental data and scale resolving
lattice-Boltzmann/very-large eddy simulation results for a two-bladed small unmanned aerial system in transitional boundary layer conditions are used to validate the low-fidelity approaches. Comparison between low-fidelity, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modeled by the low fidelity methods, which therefore constitute a valid tool for the preliminary design of quiet drone rotors and for the estimation of the community noise impact of drone operations.
lattice-Boltzmann/very-large eddy simulation results for a two-bladed small unmanned aerial system in transitional boundary layer conditions are used to validate the low-fidelity approaches. Comparison between low-fidelity, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modeled by the low fidelity methods, which therefore constitute a valid tool for the preliminary design of quiet drone rotors and for the estimation of the community noise impact of drone operations.
This paper investigates the prediction accuracy and time efficiency of two distinct low-order methods, Opty∂B and LOPNOR , for predicting tonal and broadband noise of a drone rotor in axial and non-axial flow conditions. These are both derived from an aero- dynamic rotor model based on the blade element momentum theory, respectively coupled with a time- (Opty∂B) and frequency-domain (LOPNOR) solution of the Ffowcs Williams- Hawkings (FW-H) integral equation applied to a radial distribution of acoustically compact and non-compact sources. Experimental data and scale-resolving lattice-Boltzmann/very- large eddy simulation (LB/VLES) results for a two-bladed small unmanned aerial system (sUAS) in transitional boundary layer conditions are used to validate the low-order ap- proaches. Comparison between low-order, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modelled by the low-fidelity methods, which therefore constitute a valid tool for preliminary design of quiet drone rotors or to estimate the noise impact of drone operations.
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This paper investigates the prediction accuracy and time efficiency of two distinct low-order methods, Opty∂B and LOPNOR , for predicting tonal and broadband noise of a drone rotor in axial and non-axial flow conditions. These are both derived from an aero- dynamic rotor model based on the blade element momentum theory, respectively coupled with a time- (Opty∂B) and frequency-domain (LOPNOR) solution of the Ffowcs Williams- Hawkings (FW-H) integral equation applied to a radial distribution of acoustically compact and non-compact sources. Experimental data and scale-resolving lattice-Boltzmann/very- large eddy simulation (LB/VLES) results for a two-bladed small unmanned aerial system (sUAS) in transitional boundary layer conditions are used to validate the low-order ap- proaches. Comparison between low-order, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modelled by the low-fidelity methods, which therefore constitute a valid tool for preliminary design of quiet drone rotors or to estimate the noise impact of drone operations.
This paper introduces a methodology for predicting the noise footprint of urban air mobility (UAM) vehicles in vertiport environments during approach and departure maneuvers. The methodology integrates a flight mechanics model, an aerodynamic model, aeroacoustic models, and a noise propagation model. The flight mechanics model employs a point-mass dynamic model to determine optimal trajectories based on prescribed criteria. The aerodynamic model utilizes blade element momentum theory, while aeroacoustic models include frequency-domain acoustic formulation and a noise propagation model based on Gaussian beam propagation method, which accounts for 3D variations in terrain and atmospheric profiles. Noise footprints are computed for several waypoints, featuring significant variations in vehicle flight speed and pitch angle, and are subsequently compared. It is observed that variations in vehicle pitch angle significantly influence noise radiation directivity. Specifically, when the vehicle pitches up, on-ground noise levels beneath the source increase, while those at receivers farther away decrease. Conversely, when the vehicle pitches down, on-ground noise levels beneath the source decrease, while those at receivers farther away increase. Additionally, as flight speed increases, on-ground noise levels rise accordingly regardless of whether the vehicle pitches up or down. This trend suggests that lower flight speeds during approach and departure maneuvers are desirable to reduce the noise footprint. Furthermore, it is noted that building blocks further shield incoming noise and decrease noise levels at receivers distributed behind them. These findings underscore the necessity of the proposed approach in evaluating the noise footprint of UAM flight trajectories in vertiport environments, providing valuable insights for early design stages.
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This paper introduces a methodology for predicting the noise footprint of urban air mobility (UAM) vehicles in vertiport environments during approach and departure maneuvers. The methodology integrates a flight mechanics model, an aerodynamic model, aeroacoustic models, and a noise propagation model. The flight mechanics model employs a point-mass dynamic model to determine optimal trajectories based on prescribed criteria. The aerodynamic model utilizes blade element momentum theory, while aeroacoustic models include frequency-domain acoustic formulation and a noise propagation model based on Gaussian beam propagation method, which accounts for 3D variations in terrain and atmospheric profiles. Noise footprints are computed for several waypoints, featuring significant variations in vehicle flight speed and pitch angle, and are subsequently compared. It is observed that variations in vehicle pitch angle significantly influence noise radiation directivity. Specifically, when the vehicle pitches up, on-ground noise levels beneath the source increase, while those at receivers farther away decrease. Conversely, when the vehicle pitches down, on-ground noise levels beneath the source decrease, while those at receivers farther away increase. Additionally, as flight speed increases, on-ground noise levels rise accordingly regardless of whether the vehicle pitches up or down. This trend suggests that lower flight speeds during approach and departure maneuvers are desirable to reduce the noise footprint. Furthermore, it is noted that building blocks further shield incoming noise and decrease noise levels at receivers distributed behind them. These findings underscore the necessity of the proposed approach in evaluating the noise footprint of UAM flight trajectories in vertiport environments, providing valuable insights for early design stages.
This paper presents a low-order method for assessing tonal noise from full-electric propeller-driven aircraft during outdoor operations. A high-fidelity numerical simulation and several outdoor measurements were performed to validate the approach and identify the dominant noise source. Outdoor measurements involve constant-altitude level flight and three take-off flights. The low-order method focuses exclusively on blade and hub geometry, while the numerical simulation considers propeller blades and the spinner. Comparison of outdoor measurements, numerical simulations, and low-order model predictions reveals the propeller as the primary noise source for the specified aircraft configuration, with negligible interactions with the airframe. The study further demonstrates that during take-off flights noise levels at higher harmonics are more sensitive to variations in propeller disk angles of attack. These findings underscore the importance of addressing propeller noise in full-electric propeller-driven aircraft. Additionally, the paper emphasizes the practical application of the low-order approach for evaluating the aircraft's noise footprint during take-off flights, providing crucial insights for early design stages.
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This paper presents a low-order method for assessing tonal noise from full-electric propeller-driven aircraft during outdoor operations. A high-fidelity numerical simulation and several outdoor measurements were performed to validate the approach and identify the dominant noise source. Outdoor measurements involve constant-altitude level flight and three take-off flights. The low-order method focuses exclusively on blade and hub geometry, while the numerical simulation considers propeller blades and the spinner. Comparison of outdoor measurements, numerical simulations, and low-order model predictions reveals the propeller as the primary noise source for the specified aircraft configuration, with negligible interactions with the airframe. The study further demonstrates that during take-off flights noise levels at higher harmonics are more sensitive to variations in propeller disk angles of attack. These findings underscore the importance of addressing propeller noise in full-electric propeller-driven aircraft. Additionally, the paper emphasizes the practical application of the low-order approach for evaluating the aircraft's noise footprint during take-off flights, providing crucial insights for early design stages.
Research on drone and urban air mobility noise
Measurement, modelling, and human perception
Conference paper
(2024)
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M. Snellen, R. Merino Martinez, A. Altena, A. Amiri Simkooei, C.I. Andino Cappagli, A.M. Morin, F. Yunus, R.M. Yupa Villanueva
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.
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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.
Advanced Air Mobility (AAM) vehicles are usually capable to operate in both forward and vertical flight thanks to their design configurations featuring multiple (tilting) rotors. Such maneuvering agility can be leveraged to minimize their acoustic footprint during operations close to the ground. The present work compares the acoustic footprint of optimal trajectories of AAM aircraft using low-order aero-acoustic models. The methodology is applied to the case of an AAM quad-rotor aircraft, which is modelled as a rotating point-mass with three Degrees of Freedom and two input controls. The trajectories are globally optimal in the sense of standard mission objectives, such as maneuver time or traveled horizontal distance, and are subject to realistic performance constraints. Results show that minimum-time trajectories generate higher and more concentrated noise footprints compared to minimum-distance trajectories, which distribute noise levels more evenly and result in overall lower noise footprints. Departure trajectories exhibit lower noise levels than approach trajectories. Adopting minimum-distance trajectories can significantly reduce noise impacts for both approach and departure maneuvers.
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Advanced Air Mobility (AAM) vehicles are usually capable to operate in both forward and vertical flight thanks to their design configurations featuring multiple (tilting) rotors. Such maneuvering agility can be leveraged to minimize their acoustic footprint during operations close to the ground. The present work compares the acoustic footprint of optimal trajectories of AAM aircraft using low-order aero-acoustic models. The methodology is applied to the case of an AAM quad-rotor aircraft, which is modelled as a rotating point-mass with three Degrees of Freedom and two input controls. The trajectories are globally optimal in the sense of standard mission objectives, such as maneuver time or traveled horizontal distance, and are subject to realistic performance constraints. Results show that minimum-time trajectories generate higher and more concentrated noise footprints compared to minimum-distance trajectories, which distribute noise levels more evenly and result in overall lower noise footprints. Departure trajectories exhibit lower noise levels than approach trajectories. Adopting minimum-distance trajectories can significantly reduce noise impacts for both approach and departure maneuvers.
The demand for transportation has increased significantly in recent decades, resulting in rising community noise pollution, with aircraft identified as one of the major contributors. The emergence of urban air mobility (UAM) vehicles as a new transportation mode has further intensified noise concerns because these vehicles operate differently from conventional aircraft and are expected to fly within densely populated urban environments. Accurately evaluating their noise footprint while accounting for design, operational, and environmental factors is therefore essential for developing effective noise mitigation strategies. However, existing aircraft community noise (ACN) prediction methods often simplify or neglect these factors. This thesis proposes new methodologies and algorithms to improve ACN predictions by incorporating these influences.
The study first examines the relationship between aircraft design and operational parameters and their acoustic footprint in a homogeneous propagation environment. A computational framework combining a low-fidelity noise source prediction approach with a straight-ray propagation model is used. The effects of advance ratio and blade count during steady forward flight are analysed. Results show that higher advance ratios can change source directivity and increase the acoustic footprint by up to 30 dBA. Increasing the blade count from five to seven leads to a variation of 16 dBA due to directivity changes. While additional blades reduce loading noise, total noise levels remain largely unchanged due to increased thickness noise and higher tip Mach numbers. Overall, ground noise levels are more sensitive to changes in advance ratio than to blade count.
The influence of atmospheric conditions on long-distance noise propagation is then investigated using a newly developed 3D curved-ray tracing algorithm. Simulations for steady level flight under typical summer weather conditions reveal that upwind flight can generate a refractive shadow zone, particularly when the vehicle is far from receivers. This effect diminishes as the vehicle approaches. In contrast, downwind flight shows limited impact on the acoustic footprint. These findings highlight the role of atmospheric conditions in shaping long-range sound propagation.
To capture more realistic urban environments, the study introduces an advanced ray-acoustics model based on Gaussian beam tracing. This model accounts for three-dimensional variations in temperature, wind velocity, and multiple reflections from irregular terrain and buildings. A semi-empirical formulation is proposed to reduce truncation errors in beam summation, improving accuracy compared to conventional implementations. Validation against finite element simulations demonstrates that the method provides reliable and computationally efficient predictions for high-frequency noise propagation in urban areas.
The framework is further extended to include complex source directivity and moving atmospheric media to assess noise impacts of eVTOL vehicles in vertiport environments. Results show that buildings can increase ground noise levels by about 5 dB due to reflections, while simultaneously creating shadow zones behind structures. Wind flow also modifies acoustic patterns and can intensify noise levels, particularly at higher frequencies.
Finally, broadband noise calculations are enabled by coupling the Gaussian beam tracer with a high-fidelity noise source model. Simulations of helicopter noise over mountainous terrain show that terrain and atmospheric flow can significantly alter acoustic propagation, producing variations of up to 35 dB. These findings provide insights that can support the design and operation of future UAM vehicles to minimize noise impacts on surrounding communities ...
The study first examines the relationship between aircraft design and operational parameters and their acoustic footprint in a homogeneous propagation environment. A computational framework combining a low-fidelity noise source prediction approach with a straight-ray propagation model is used. The effects of advance ratio and blade count during steady forward flight are analysed. Results show that higher advance ratios can change source directivity and increase the acoustic footprint by up to 30 dBA. Increasing the blade count from five to seven leads to a variation of 16 dBA due to directivity changes. While additional blades reduce loading noise, total noise levels remain largely unchanged due to increased thickness noise and higher tip Mach numbers. Overall, ground noise levels are more sensitive to changes in advance ratio than to blade count.
The influence of atmospheric conditions on long-distance noise propagation is then investigated using a newly developed 3D curved-ray tracing algorithm. Simulations for steady level flight under typical summer weather conditions reveal that upwind flight can generate a refractive shadow zone, particularly when the vehicle is far from receivers. This effect diminishes as the vehicle approaches. In contrast, downwind flight shows limited impact on the acoustic footprint. These findings highlight the role of atmospheric conditions in shaping long-range sound propagation.
To capture more realistic urban environments, the study introduces an advanced ray-acoustics model based on Gaussian beam tracing. This model accounts for three-dimensional variations in temperature, wind velocity, and multiple reflections from irregular terrain and buildings. A semi-empirical formulation is proposed to reduce truncation errors in beam summation, improving accuracy compared to conventional implementations. Validation against finite element simulations demonstrates that the method provides reliable and computationally efficient predictions for high-frequency noise propagation in urban areas.
The framework is further extended to include complex source directivity and moving atmospheric media to assess noise impacts of eVTOL vehicles in vertiport environments. Results show that buildings can increase ground noise levels by about 5 dB due to reflections, while simultaneously creating shadow zones behind structures. Wind flow also modifies acoustic patterns and can intensify noise levels, particularly at higher frequencies.
Finally, broadband noise calculations are enabled by coupling the Gaussian beam tracer with a high-fidelity noise source model. Simulations of helicopter noise over mountainous terrain show that terrain and atmospheric flow can significantly alter acoustic propagation, producing variations of up to 35 dB. These findings provide insights that can support the design and operation of future UAM vehicles to minimize noise impacts on surrounding communities ...
The demand for transportation has increased significantly in recent decades, resulting in rising community noise pollution, with aircraft identified as one of the major contributors. The emergence of urban air mobility (UAM) vehicles as a new transportation mode has further intensified noise concerns because these vehicles operate differently from conventional aircraft and are expected to fly within densely populated urban environments. Accurately evaluating their noise footprint while accounting for design, operational, and environmental factors is therefore essential for developing effective noise mitigation strategies. However, existing aircraft community noise (ACN) prediction methods often simplify or neglect these factors. This thesis proposes new methodologies and algorithms to improve ACN predictions by incorporating these influences.
The study first examines the relationship between aircraft design and operational parameters and their acoustic footprint in a homogeneous propagation environment. A computational framework combining a low-fidelity noise source prediction approach with a straight-ray propagation model is used. The effects of advance ratio and blade count during steady forward flight are analysed. Results show that higher advance ratios can change source directivity and increase the acoustic footprint by up to 30 dBA. Increasing the blade count from five to seven leads to a variation of 16 dBA due to directivity changes. While additional blades reduce loading noise, total noise levels remain largely unchanged due to increased thickness noise and higher tip Mach numbers. Overall, ground noise levels are more sensitive to changes in advance ratio than to blade count.
The influence of atmospheric conditions on long-distance noise propagation is then investigated using a newly developed 3D curved-ray tracing algorithm. Simulations for steady level flight under typical summer weather conditions reveal that upwind flight can generate a refractive shadow zone, particularly when the vehicle is far from receivers. This effect diminishes as the vehicle approaches. In contrast, downwind flight shows limited impact on the acoustic footprint. These findings highlight the role of atmospheric conditions in shaping long-range sound propagation.
To capture more realistic urban environments, the study introduces an advanced ray-acoustics model based on Gaussian beam tracing. This model accounts for three-dimensional variations in temperature, wind velocity, and multiple reflections from irregular terrain and buildings. A semi-empirical formulation is proposed to reduce truncation errors in beam summation, improving accuracy compared to conventional implementations. Validation against finite element simulations demonstrates that the method provides reliable and computationally efficient predictions for high-frequency noise propagation in urban areas.
The framework is further extended to include complex source directivity and moving atmospheric media to assess noise impacts of eVTOL vehicles in vertiport environments. Results show that buildings can increase ground noise levels by about 5 dB due to reflections, while simultaneously creating shadow zones behind structures. Wind flow also modifies acoustic patterns and can intensify noise levels, particularly at higher frequencies.
Finally, broadband noise calculations are enabled by coupling the Gaussian beam tracer with a high-fidelity noise source model. Simulations of helicopter noise over mountainous terrain show that terrain and atmospheric flow can significantly alter acoustic propagation, producing variations of up to 35 dB. These findings provide insights that can support the design and operation of future UAM vehicles to minimize noise impacts on surrounding communities
The study first examines the relationship between aircraft design and operational parameters and their acoustic footprint in a homogeneous propagation environment. A computational framework combining a low-fidelity noise source prediction approach with a straight-ray propagation model is used. The effects of advance ratio and blade count during steady forward flight are analysed. Results show that higher advance ratios can change source directivity and increase the acoustic footprint by up to 30 dBA. Increasing the blade count from five to seven leads to a variation of 16 dBA due to directivity changes. While additional blades reduce loading noise, total noise levels remain largely unchanged due to increased thickness noise and higher tip Mach numbers. Overall, ground noise levels are more sensitive to changes in advance ratio than to blade count.
The influence of atmospheric conditions on long-distance noise propagation is then investigated using a newly developed 3D curved-ray tracing algorithm. Simulations for steady level flight under typical summer weather conditions reveal that upwind flight can generate a refractive shadow zone, particularly when the vehicle is far from receivers. This effect diminishes as the vehicle approaches. In contrast, downwind flight shows limited impact on the acoustic footprint. These findings highlight the role of atmospheric conditions in shaping long-range sound propagation.
To capture more realistic urban environments, the study introduces an advanced ray-acoustics model based on Gaussian beam tracing. This model accounts for three-dimensional variations in temperature, wind velocity, and multiple reflections from irregular terrain and buildings. A semi-empirical formulation is proposed to reduce truncation errors in beam summation, improving accuracy compared to conventional implementations. Validation against finite element simulations demonstrates that the method provides reliable and computationally efficient predictions for high-frequency noise propagation in urban areas.
The framework is further extended to include complex source directivity and moving atmospheric media to assess noise impacts of eVTOL vehicles in vertiport environments. Results show that buildings can increase ground noise levels by about 5 dB due to reflections, while simultaneously creating shadow zones behind structures. Wind flow also modifies acoustic patterns and can intensify noise levels, particularly at higher frequencies.
Finally, broadband noise calculations are enabled by coupling the Gaussian beam tracer with a high-fidelity noise source model. Simulations of helicopter noise over mountainous terrain show that terrain and atmospheric flow can significantly alter acoustic propagation, producing variations of up to 35 dB. These findings provide insights that can support the design and operation of future UAM vehicles to minimize noise impacts on surrounding communities
Efficient calculation of urban air mobility noise footprint in a vertiport environment, considering acoustic effects of various designs, operational conditions, and environmental factors, is essential to limit the noise impact on the community at an early stage. To this purpose, the computationally efficient low-fidelity approach presented by the authors in Fuerkaiti et al. (2022) [11] is extended to calculate the noise footprint of an aircraft in a generic 3D environment. The straight-ray propagator is replaced with a Gaussian beam tracer that accounts for complex source directivity, 3D varying terrain topology, and wind profiles. The reliability of the Gaussian beam tracer has been verified in previous studies by the authors. In this work, it is further extended to include complex source directivity in the presence of a moving medium. Noise sources, obtained using a low-fidelity toolchain, are stored on a sphere surrounding the aircraft and are propagated through an inhomogeneous anisotropic atmosphere. Noise footprints, predicted for different terrain topologies, source directivities, and wind flow conditions, are compared. It is shown that, compared to flat terrain, for the case under investigation, the building blocks increase on-ground noise levels by 5 dB in the illuminated zone due to multiple reflections; they also shield the incoming sound field by creating shadow zones behind the building. The shielding increases with increasing frequency in a quiescent atmosphere. The change between the source directivities, corresponding to the first and second harmonics of the blade passing frequency, results in a difference of up to 40 dB in the noise footprint. The presence of the wind flow can contribute a significant variation in the acoustic footprint by changing the lobes of the footprint pattern and intensifying the noise levels; the variation increases with increasing frequency. Compared to the straight-ray propagator, the present approach reduces the prediction error by 5 dB in the illuminated zones and 35 dB in the terrain shadow zones.
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Efficient calculation of urban air mobility noise footprint in a vertiport environment, considering acoustic effects of various designs, operational conditions, and environmental factors, is essential to limit the noise impact on the community at an early stage. To this purpose, the computationally efficient low-fidelity approach presented by the authors in Fuerkaiti et al. (2022) [11] is extended to calculate the noise footprint of an aircraft in a generic 3D environment. The straight-ray propagator is replaced with a Gaussian beam tracer that accounts for complex source directivity, 3D varying terrain topology, and wind profiles. The reliability of the Gaussian beam tracer has been verified in previous studies by the authors. In this work, it is further extended to include complex source directivity in the presence of a moving medium. Noise sources, obtained using a low-fidelity toolchain, are stored on a sphere surrounding the aircraft and are propagated through an inhomogeneous anisotropic atmosphere. Noise footprints, predicted for different terrain topologies, source directivities, and wind flow conditions, are compared. It is shown that, compared to flat terrain, for the case under investigation, the building blocks increase on-ground noise levels by 5 dB in the illuminated zone due to multiple reflections; they also shield the incoming sound field by creating shadow zones behind the building. The shielding increases with increasing frequency in a quiescent atmosphere. The change between the source directivities, corresponding to the first and second harmonics of the blade passing frequency, results in a difference of up to 40 dB in the noise footprint. The presence of the wind flow can contribute a significant variation in the acoustic footprint by changing the lobes of the footprint pattern and intensifying the noise levels; the variation increases with increasing frequency. Compared to the straight-ray propagator, the present approach reduces the prediction error by 5 dB in the illuminated zones and 35 dB in the terrain shadow zones.
This paper presents a noise propagation approach based on the Gaussian beam tracing (GBT) method that accounts for multiple reflections over three-dimensional terrain topology and atmospheric refraction due to horizontal and vertical variability in wind velocity. A semi-empirical formulation is derived to reduce truncation error in the beam summation for receivers on the terrain surfaces. The reliability of the present GBT approach is assessed with an acoustic solver based on the finite element method (FEM) solutions of the convected wave equation. The predicted wavefields with the two methods are compared for different source-receiver geometries, urban settings, and wind conditions. When the beam summation is performed without the empirical formulation, the maximum difference is more than 40 dB; it drops below 8 dB with the empirical formulation. In the presence of wind, the direct and reflected waves can have different ray paths than those in a quiescent atmosphere, which results in less apparent diffraction patterns. A 17-fold reduction in computation time is achieved compared to the FEM solver. The results suggest that the present GBT acoustic propagation model can be applied to high-frequency noise propagation in urban environments with acceptable accuracy and better computational efficiency than full-wave solutions.
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This paper presents a noise propagation approach based on the Gaussian beam tracing (GBT) method that accounts for multiple reflections over three-dimensional terrain topology and atmospheric refraction due to horizontal and vertical variability in wind velocity. A semi-empirical formulation is derived to reduce truncation error in the beam summation for receivers on the terrain surfaces. The reliability of the present GBT approach is assessed with an acoustic solver based on the finite element method (FEM) solutions of the convected wave equation. The predicted wavefields with the two methods are compared for different source-receiver geometries, urban settings, and wind conditions. When the beam summation is performed without the empirical formulation, the maximum difference is more than 40 dB; it drops below 8 dB with the empirical formulation. In the presence of wind, the direct and reflected waves can have different ray paths than those in a quiescent atmosphere, which results in less apparent diffraction patterns. A 17-fold reduction in computation time is achieved compared to the FEM solver. The results suggest that the present GBT acoustic propagation model can be applied to high-frequency noise propagation in urban environments with acceptable accuracy and better computational efficiency than full-wave solutions.
Electric vertical take-off and landing vehicle community noise prediction
From flow simulation to flight mission analysis
This paper presents an overview of noise prediction capabilities available at Dassault Systèmes and Delft University of Technology in the field of electric vertical takeoff and landing vehicle aeroacoustics. Three main aspects are covered: (i) noise source calculation via scale-resolving high-fidelity Lattice-Boltzmann flow simulations, (ii) noise propagation calculations in urban environments via Gaussian-beam tracing techniques, (iii) and flight mission analysis via a multi-fidelity model-based system engineering framework. Key features of the different numerical simulations techniques are discussed in more detail. Finally, a vision of a combined experimental/digital eVTOL noise certification process is outlined.
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This paper presents an overview of noise prediction capabilities available at Dassault Systèmes and Delft University of Technology in the field of electric vertical takeoff and landing vehicle aeroacoustics. Three main aspects are covered: (i) noise source calculation via scale-resolving high-fidelity Lattice-Boltzmann flow simulations, (ii) noise propagation calculations in urban environments via Gaussian-beam tracing techniques, (iii) and flight mission analysis via a multi-fidelity model-based system engineering framework. Key features of the different numerical simulations techniques are discussed in more detail. Finally, a vision of a combined experimental/digital eVTOL noise certification process is outlined.
Journal article
(2022)
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Yunusi Fuerkaiti, Edoardo Grande, Damiano Casalino, Francesco Avallone, Daniele Ragni
A noise footprint prediction framework for propeller-driven aircraft which couples an aerodynamic model and several aeroacoustic models is presented in this study. The aerodynamic model is based on the blade element momentum theory, while the aeroacoustic models are based on a time-domain compact dipole/monopole Ffowcs-Williams and Hawking's acoustic analogy, a trailing edge noise model, and a noise hemisphere database approach including a straight-ray propagation model, respectively. In order to reduce the runtime, the frequency-domain acoustic formulation, derived by Hanson (1980), is implemented and validated against the compact dipole/monopole Ffowcs-Williams and Hawking's acoustic analogy. The framework evaluates the acoustic effects of variations in the design and operating conditions of a propeller in forward flight. Noise footprints, obtained with different propeller configurations having varying advance ratio and number of blades are compared. It is found that, for a given thrust, a drop in advance ratio alters the source directivity dramatically, which resulting in a variation of up to 30 dBA on the acoustic footprint. When the advance ratio is kept the same and the number of blades increases from 5 to 7, the variation becomes 16 dBA due to the change in the source directivity, but the maximum noise level remains the same. The latter condition reduces the loading for each blade, and consequently the associated noise. However, the total noise remains unchanged as a consequence of increasing thickness noise due to the lower advance ratio, high blade tip Mach number, and addition of extra blades.
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A noise footprint prediction framework for propeller-driven aircraft which couples an aerodynamic model and several aeroacoustic models is presented in this study. The aerodynamic model is based on the blade element momentum theory, while the aeroacoustic models are based on a time-domain compact dipole/monopole Ffowcs-Williams and Hawking's acoustic analogy, a trailing edge noise model, and a noise hemisphere database approach including a straight-ray propagation model, respectively. In order to reduce the runtime, the frequency-domain acoustic formulation, derived by Hanson (1980), is implemented and validated against the compact dipole/monopole Ffowcs-Williams and Hawking's acoustic analogy. The framework evaluates the acoustic effects of variations in the design and operating conditions of a propeller in forward flight. Noise footprints, obtained with different propeller configurations having varying advance ratio and number of blades are compared. It is found that, for a given thrust, a drop in advance ratio alters the source directivity dramatically, which resulting in a variation of up to 30 dBA on the acoustic footprint. When the advance ratio is kept the same and the number of blades increases from 5 to 7, the variation becomes 16 dBA due to the change in the source directivity, but the maximum noise level remains the same. The latter condition reduces the loading for each blade, and consequently the associated noise. However, the total noise remains unchanged as a consequence of increasing thickness noise due to the lower advance ratio, high blade tip Mach number, and addition of extra blades.
This work presents a novel noise propagation approach based on the Gaussian Beam Tracing (GBT) method that accounts for complex source directivity, weather conditions, and irregular ground topology for the evaluation of the noise footprint. The approach takes a precomputed noise sphere as input and propagates the acoustic pressure fluctuations through a moving inhomogeneous atmosphere over realistic three-dimensional (3D) terrain. Noise footprints, obtained with di erent source noise spheres and wind flow conditions, are compared. It is found that, in a quiescent atmosphere, a change in the source directivity results in a variation up to 15 dB on the acoustic footprint. In the presence of the mean flow, the variation in the noise footprint can reach up to 35 dB. The results suggest that any variation in the source directivity and wind flow can cause a significant change in the acoustic footprint predicted in 3D environments with varying terrain topology and wind flow.
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This work presents a novel noise propagation approach based on the Gaussian Beam Tracing (GBT) method that accounts for complex source directivity, weather conditions, and irregular ground topology for the evaluation of the noise footprint. The approach takes a precomputed noise sphere as input and propagates the acoustic pressure fluctuations through a moving inhomogeneous atmosphere over realistic three-dimensional (3D) terrain. Noise footprints, obtained with di erent source noise spheres and wind flow conditions, are compared. It is found that, in a quiescent atmosphere, a change in the source directivity results in a variation up to 15 dB on the acoustic footprint. In the presence of the mean flow, the variation in the noise footprint can reach up to 35 dB. The results suggest that any variation in the source directivity and wind flow can cause a significant change in the acoustic footprint predicted in 3D environments with varying terrain topology and wind flow.
This paper presents an atmospheric propagation model, based on ray acoustics, that accounts for realistic weather conditions in the evaluation of the noise footprint of an aircraft. Noise sources, obtained using the Ffowcs Williams and Hawkings acoustic analogy applied to scale-resolved flow simulation data, are stored on a hemisphere surrounding the vehicle. These noise sources are propagated using a propagation model that takes into account the vertical variability of air temperature and wind velocity. The electric vertical takeoff and landing aircraft, presented by Casalino, van der Velden, and Romani [(2019). in Proceedings of the AIAA Scitech 2019 Forum, January 7-11, San Diego, CA, pp. 1834-1851], is used as a case study; noise footprints, obtained considering various vertically varying temperature and wind velocity distributions, are compared. It is shown that weather conditions in the acoustic wave propagation can contribute to mismatch up to 4 dBA in the illuminated zone and a significant drop in the refractive shadow zone caused by the vertical air temperature and wind velocity gradients. This work constitutes the first accomplishment in including realistic atmospheric effects in aircraft community noise prediction based on scale-resolved flow simulations.
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This paper presents an atmospheric propagation model, based on ray acoustics, that accounts for realistic weather conditions in the evaluation of the noise footprint of an aircraft. Noise sources, obtained using the Ffowcs Williams and Hawkings acoustic analogy applied to scale-resolved flow simulation data, are stored on a hemisphere surrounding the vehicle. These noise sources are propagated using a propagation model that takes into account the vertical variability of air temperature and wind velocity. The electric vertical takeoff and landing aircraft, presented by Casalino, van der Velden, and Romani [(2019). in Proceedings of the AIAA Scitech 2019 Forum, January 7-11, San Diego, CA, pp. 1834-1851], is used as a case study; noise footprints, obtained considering various vertically varying temperature and wind velocity distributions, are compared. It is shown that weather conditions in the acoustic wave propagation can contribute to mismatch up to 4 dBA in the illuminated zone and a significant drop in the refractive shadow zone caused by the vertical air temperature and wind velocity gradients. This work constitutes the first accomplishment in including realistic atmospheric effects in aircraft community noise prediction based on scale-resolved flow simulations.