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05.04 Urban Air Mobility Community Noise, Part 2

Community noise from urban air mobility (UAM) and its control by traffic management
Time: 7:20 am

Author: Michael Bauer

Abstract ID: 1333

The awareness about UAM is amplified by steadily growing numbers of air taxi concepts being announced. In general environmentally friendly by electric propulsion, community noise and en-route noise are still prominent open questions. Several studies for larger UAM aircraft, describing the acoustic characteristics of a variety of potential air taxi concepts, have been performed by the author. Due to the abovementioned multitude of different vehicle concepts and their multiple operational conditions, each of them shows individual sound characteristics. Therefore, further investigations of noise created by air taxi fleets appear to be crucial. Understanding of community noise around vertiports and along air taxi routes will strongly depend on those fleets. In this paper, acoustically different air taxi systems are composing different sets of air taxi fleets, used for air traffic noise simulations. The simulations start with baseline scenarios of equally represented taxi systems on fixed flight paths with several flight levels in a certain air lane. The final fleets are consisting of random air taxi composition with randomly populated flight paths. The results, based on common noise metrics and changes in the number of affected residents, could provide a first indication how to reduce community noise by future UAM traffic management.

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Community noise assessment of urban air mobility vehicle operations using the FAA Aviation Environmental Design Tool
Time: 11:40 am

Author: Stephen Rizzi

Abstract ID: 1482

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate in communities close to the public at large.  The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration’s Aviation Environmental Design Tool (AEDT), does not support analysis of such operations due to a combined lack of a UAM aircraft performance model and aircraft noise data. This paper discusses the initial development of a method to assess the acoustic impact of UAM fleet operations on the community using AEDT and demonstrates its use for representative UAM operations. In particular, methods were developed using fixed-point flight profiles and user-supplied noise data in a manner that avoids unwanted behavior in AEDT. A set of 32 routes in the Dallas-Ft. Worth area were assessed for single and multiple (fleet) operations for two concept vehicles.

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The AIRNOISE-UAM tool and verification with FAA aviation environmental design tool
Time: 12:00 pm

Author: jinhua li

Abstract ID: 1488

Noise disruption is expected to be a significant factor for public acceptance of urban air mobility vehicle operations. Today the noise exposure caused by fixed-wing aircraft and/or helicopters operating from airports can be predicted using the Federal Aviation Administration’s Aviation Environmental Design Tool (AEDT) software. The noise at the receiver is calculated by interpolating and/or extrapolating noise data as a function of power and distance, named Noise-Power-Distance (NPD) data, for each vehicle type in the AEDT database. The noise data at the receiver fully accounts for atmospheric propagation and includes several adjustments including those for vehicle speed, lateral attenuation, and noise fraction. Urban air mobility will introduce a new class of vehicles named electric Vertical Take-Off and Landing (eVTOL). In this paper, a new tool named “AIRNOISE-UAM” has been developed together with new NPD data named “Gen-1 NPD” to predict noise exposure caused by eVTOL aircraft operations. The predicted noise exposure results from individual flight segments and integrated scenarios are verified with those from AEDT.

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An investigation into the impact of unmanned aerial vehicles on soundscape perception in urban and rural environments
Time: 11:20 am

Author: Rory Nicholls

Abstract ID: 1570

It is predicted that urban air mobility, including the use of small to medium sized unmanned aerial vehicle (UAV) delivery systems, will be introduced into cities across the globe within the next 15 years.  It is known, however, that noise is one of the main limiting factors for the wider adoption of these vehicles.  Neither the metrics nor the methods used for conventional aircraft seem to be optimal for this novel source of noise.  This research will aid in developing suitable psychoacoustic methodologies and metrics, specifically designed to quantify community noise impact of these vehicles.  This paper describes a psychoacoustic experiment used to gather participant responses to UAV sound recordings, both isolated and with typical background noise in a diversity of soundscapes.  Results from this psychoacoustic experiment will be used to correlate perceptions of UAV noise with objective sound quality metrics, and build new regression relationships that could describe the impact of a given UAV on the perception of soundscape environments.  Future extension to the research may include evaluating the differences in psychoacoustic responses when introducing more accurate reproduction methods, such as virtual reality systems, and how these could be incorporated into a standardised human response measurement procedure.

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ATEFA – A first German approach on UAM community noise and air-taxi certification
Time: 7:00 am

Author: Michael Bauer

Abstract ID: 1638

Urban air mobility (UAM) includes larger air taxis, driven by multiple distributed propellers or fans, installed in a fixed configuration or as tilted wings/engines. These novel electric air vehicles will always generate tonal and broadband noise, in some cases with components from a specific installation situation. In any case, noise will propagate to the ground, into high populated areas of large cities or into their urban environment, individually depending on the operational situation of air taxi use. Some of the populated areas, where no significant noise from air traffic has been observed so far, will be exposed to this new type of aircraft noise. ATEFA, as the first German national funded research project on UAM community noise, aims to provide first answers. Three selected air taxi concepts, strongly differing acoustically from each other, will be technically described and their noise emissions will be modeled and predicted. Air taxi operations will be simulated by generic traffic scenarios in a selected area of southern Germany, and community noise near vertiports, but also “en-route” along the flight paths, will be computed. Beside this, noise certification aspects will be assessed regarding metrics and procedures and compared to a light low-noise helicopter as reference aircraft.

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Comparison of two community noise models applied to a NASA urban air mobility concept vehicle
Time: 12:20 pm

Author: Juliet Page

Abstract ID: 1650

Predictions of community noise exposure from the NASA urban air mobility (UAM) concept vehicles have been conducted for representative operations using the FAA Aviation Environmental Design Tool (AEDT) in order to demonstrate modeling tool interoperability and assess applicability, capabilities and limitations of integrated noise modeling tools. To both quantify limitations and highlight other capabilities, a comparative analysis is performed using a time simulation method, in particular, using the Volpe Advanced Acoustic Model (AAM). Starting with the same source noise model, the 3D directivity of a UAM concept vehicle is predicted in terms of aeroacoustic pressure time histories at a sphere of observers near the vehicle. In addition to distilling those data to a set of noise-power-distance data for input to AEDT, the data are processed preserving directivity, into narrowband, one-twelfth and one-third octave bands for input to AAM. Results from AEDT and AAM modeling are provided for a variety of metrics to demonstrate the effect that source noise and propagation modeling fidelity have on predicted results at receptors over a study area.

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Sound, noise, annoyance? Information as a means to strengthen the public acceptance of civil drones
Time: 7:20 am

Author: Hinnerk Eissfeldt

Abstract ID: 2045

Civil drones are becoming ever more present in public perception. Ranging from parcel delivery to wildlife protection and from precision farming to law enforcement, many applications are said to have market-changing potential. Against this background, nations and institutions around the world are trying to keep up with the dynamic technological developments by means of rules and regulations. Since all parties involved expect a strong increase in both the number of drones and the range of their uses, there is a rising interest in the public acceptance of these vehicles. Widespread acceptance can promote the dissemination of new technologies. Conversely, citizens’ concerns about the use of drones in their daily environment may pose barriers to the further proliferation of civil drones, especially in urban areas. The psychoacoustic properties of the vehicles have repeatedly been discussed as being one such limiting factor. This paper discusses results of a representative national study on the social acceptance of civil drones, taking a closer look at effects of information about drones as potential means to foster public acceptance. The findings underline the role of well planned information campaigns as well as community engagement in managing the contribution of drones in future urban soundscapes.

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Visual and audio perception study on drone aircraft and similar sounds in an Urban Air Mobility setting
Time: 7:00 am

Author: Roalt Aalmoes

Abstract ID: 2160

Urban Air Mobility (UAM) is a novel aerospace concept involving drones and Personal Air Vehicles (PAVs) operating in a densely populated urban environment. Most of such vehicles will be electric-powered and rotor-based, creating a distinct sound in the proposed setting of a city. Public acceptability, partially due to noise impact, is a valid concern for the introduction of UAM. To evaluate human perception and noise annoyance of these vehicles, a study is set up that comprises audio-only and combined audio-visual stimuli of hovering and fly-over events using a Virtual Reality experiment. For both types of stimuli, two ambient environments, recorded with synchronized spherical video and ambisonics audio, are provided as background: a louder urban street environment, and a quieter urban street environment. In addition to the drone sounds, more familiar sounds are also evaluated, namely a helicopter and a lawnmower sound, with and without a visualisation. Test subjects are asked about their noise sensitivity according to a shortened Weinstein scale, and their attitude towards drones using a separate questionnaire at the end of the experiment. [Note from authors: The laboratory study is ongoing and the first results are being analysed. The final results are expected well before the paper deadline. This abstract will be complemented with the main results and conclusions.]

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Techniques for adaptive metamodelling of propeller arrays far-field noise
Time: 6:20 am

Author: Umberto Iemma

Abstract ID: 2203

The fast development of Urban-Air-Mobility as well as the constant growth of the air transport have made the acoustic pollution abatement a crucial requirement for the aviation industries in order to comply with the increasingly demanding constraints for the community acceptance. The aeroacoustic characterization of arrays of electrically-powered propellers is one of the most challenging issues. The vast majority of the UAM concepts under development adopt propulsion systems based on multiple propellers, for which reliable and cost-efficient aeroacoustic models are still lacking. The present paper proposes the development of surrogate models for the description of acoustic emission of multi-propeller configurations. The numerical investigation focuses on surrogate models able to take into account the effects of the propeller blade geometry (e.g., chord and twist distributions) and global propeller-array geometric parameters (e.g., propellers clearance) on acoustic performances of the whole system. An innovative Artificial Neural Network adaptive metamodelling technique is applied on a numerical database obtained through a boundary integral formulation for the solution of incompressible potential flows around lifting/thrusting bodies, followed by the application of the Farassat 1A boundary integral formulation for the noise field evaluation.

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Noise prediction for urban air taxi operation
Time: 6:40 am

Author: Mark Koehler

Abstract ID: 2278

Solutions to escape crowded streets are increasingly taking up new forms of mobility. This also includes air taxis or VTOLs. In addition to passenger traffic, suggestions, such as parcel delivery by drones, are also regularly part of future visions. Air taxis pose additional safety requirements due to the transport of people and they also represent a major potential source of noise. A challenge that urban planners, pollution control officers and decision-makers have to face. Using the concrete example of an urban landing place for air taxis at the main train station in the city of Ingolstadt, possible problems, issues related to noise protection and their legal basis were examined. This presentation is a summary of the projects results. The examinations include the creation of noise mapping in order to simulate the impact to the already existing noise situation. Those were based on current flight noise regulations with necessary alterations regarding VTOLs. Because air taxi noise is expected to be more annoying than regular traffic noise, the possible application of flight noise indexes such as the “Frankfurt flight noise index FFI 2.0” shall be reviewed. Based on the results of the previous examinations, possible noise protection measures shall be developed.

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A machine learning-based methodology for computational aeroacoustics predictions of multi-propeller drones
Time: 8:20 pm

Author: Cesar Legendre

Abstract ID: 2415

The rapid progress in technological developments of small Unmanned Aircraft Systems (sUAS) or simply "drones" has produced a significant proliferation of this technology. From multinational businesses to drone enthusiasts, such a technology can offer a wide range of possibilities, i.e., commercial services, security, and environmental applications, while placing new demands in the already-congested civil airspace. Noise emission is a key factor that is being addressed with high-fidelity computational fluid dynamics (CFD) and aeroacoustics (CAA) techniques. However, due to uncertainties of flow conditions, wide ranges of propellers' speed variations, and different payload requirements, a complete numerical prediction varying such parameters is unfeasible. In this study, a machine learning-based approach is proposed in combination with high-fidelity CFD and CAA techniques to predict drone noise emission given a wide variation of payloads or propellers’ speeds. The transient CFD computations are calculated using a time-marching LES simulation with a WALE sub-grid scale. In contrast, the acoustic propagation is predicted using a finite element method in the frequency domain. Finally, the machine learning strategy is presented in the context of fulfilling two goals: (i) real-time noise prediction of drone systems; and (ii) determination of propeller’s rotation speeds leading to a noise prediction matching experimental data.

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A Hybrid and Efficient Low-noise assessment Platform for Urban aerial mobility (HELPU)
Time: 6:00 am

Author: Siyang Zhong

Abstract ID: 2509

Urban aerial mobility (UAM) is a promising approach to improve the traffic situation in gigantic cities, which, however, may encounter significant noise pollution issues. An integrated research platform, which is being established at HKUST, to include noise generation, long-distance propagation, and perception at the observers is timely to assess the environmental impact of UAM noise and to develop low-noise designs and flight planning. A high-quality test rig in the anechoic aerodynamic facility at HKUST is employed to measure the propeller aeroacoustics and aerodynamics, and to enable the innovative noise control device and design studies. The measurements and high-fidelity simulations using an in-house computational aeroacoustics solver can lead to comprehensive databases to facilitate and validate the development of physics-oriented noise prediction models. Also, high-efficient implementation of the boundary element method is conducted to account for the noise scattering due to the fuselage and then to evaluate the impact of UAM layout on the directivity patterns, which will then be efficiently projected to the far-field observers using the advanced Gaussian beam tracing with the effects due to moving source, atmospheric attenuation, and refraction, complex boundary absorption and reflection incorporated. Low-noise flight planning is then be made accordingly.

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Noise simulation of multi-rotor equipped urban aerial mobility vehicle for environmental assessment
Time: 6:00 am

Author: Qichen TAN

Abstract ID: 2541

The operation of the rapidly growing unmanned aerial vehicles (UAV) and the promising urban aerial mobility (UAM) could have a significant noise impact on the environment. In this work, we developed a cloud-based noise simulator to efficiently assess the environmental impact of UAM and UAV. The noise sources and long-distance propagation are computed by the propeller noise prediction models and an advanced Gaussian beam tracing method, respectively, in local high-performance computers. Users can define the working conditions and vehicle layer through a platform with a user-friendly graphical interface. In addition, the noise level distribution at the observers of interest such as the buildings can be visualized. By employing advanced interpolation methods or autonomous learning algorithms, the computations are efficiently accelerated such that the noise distributions are simultaneously displayed during flights of the vehicles. To better measure the noise impact on human perception, various noise metrics will be output for further analysis. By conducting the virtual flights using the simulator, the noise impact in each flight state and atmospheric condition of different vehicles can be predicted, which will then facilitate the low-noise flights for both UAV and UAM.

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Towards predicting noise-power-distance curves for propeller and rotor powered aircraft
Time: 11:00 am

Author: Daniel Amargianitakis

Abstract ID: 2555

Propeller and rotor based propulsion systems are the dominating choice of power delivery system in the upcoming Urban Air Mobility market. Fully electric air-taxis (car sized vehicles with Vertical Take-off and Landing, VTOL, capabilities) concepts are using the benefits of the scalable properties of electric motors to distribute propulsor units all over the airframe. The large variety of concepts and configurations of these vehicles poses a serious issue in predicting noise generated on the ground. The need for a high-level model to aid in acoustic decision making is evident. Through the demonstrated methodology of computationally deriving Noise – Power – Distance curves for conventional turbo fan aircraft, this paper delivers the capability of dealing with propeller propulsion systems and the associated propeller tonal noise sources to generate the NPDs and therefore noise exposure maps. The aims can be broken down into two objectives: a) demonstrate the capabilities of the proposed propeller harmonics noise scaling laws to calculate noise variation from a baseline scenario and b) incorporate the scaling components into the larger capability of producing noise exposure contours, by the means of computationally deriving NPD curves for propeller powered aircraft. Preliminary NPD curves for General Aviation sized propeller power aircraft are generated and discussed.

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