13:30
Community Impact, Engagement, and Perception 1
13:30
20 mins
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Psychoacoustic Assessment of Small-Scale Propeller Noise Generation Mechanisms
Isaac Bensignor, Roberto Merino-Martinez, Camillo I. Andino Cappagli, Lourenço Lima Tercio Pereira
Abstract: State-of-the-art propeller noise modeling tools can isolate the separate contributions of individual noise-generation mechanisms. However, the extent to which each mechanism shapes perceived sound quality remains poorly quantified. This paper presents a preliminary psychoacoustic study of the noise emissions from an isolated propeller tested in the anechoic wind tunnel of the Delft University of Technology. The experimental setup employs the newly developed TUC-TUC (TU delft Characterization model for oTor aerocoUstiCs) modular test bench, which enables a complete assessment of the aerodynamic characteristics and the acoustic emissions of a rotor under different flight-like operating conditions. The setup supports parametric investigations of low-Reynolds-number propeller aeroacoustics using a 360 mm diameter two-bladed rotor with adjustable blade pitch. The blade is a straight (zero-twist) NACA 0018 profile. Systematic variations in blade pitch shift the relative dominance of different noise-generation mechanisms; this investigation focuses on thickness noise (predominant at lower pitch angles) and loading noise (predominant at higher pitch angles). The noise emissions in each test case are recorded using a directivity arc composed of 12 microphones and evaluated using psychoacoustic sound-quality metrics computed with the open-source Sound Quality Analysis Toolbox (SQAT). The goal is to support perception-informed design by prioritizing mitigation of the mechanisms that most influence perceived sound quality.
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13:50
20 mins
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Context Matters: Public Response to Delivery Drone Noise in Quiet vs Noisy Areas
Alexandra Duffy, Henry Rice, Marco Oliveira, John Kennedy
Abstract: As drone delivery expands, its acoustic impact in residential areas remains poorly understood and often unregulated. This study examines how community perception of drone noise varies across urban soundscapes with differing background noise levels. Using GIS-based route data and noise modelling, we overlaid drone flight paths on road-traffic noise maps. Residential zones were then classified by background noise level and by whether drone noise exceeded traffic noise. A structured public survey was distributed across these zones to assess the annoyance and perceived loudness of the drone operations. The study considered 21,643 commercial delivery operations in a suburb of Dublin, Ireland. Population statistics estimate 94,737 residents live within the delivery area. The data was used to identify residents under the most frequently flown routes. Round 3 noise mapping data reported under the EU Environmental Noise Directive was used to evaluate traffic noise levels under these most flown routes. A total of 332 valid survey responses (out of over 600 surveyed houses) were collected from residents within the targeted exposure zone. The survey consisted of 12 structured questions designed to explore the relationship between drone noise exposure and public perception. Question formats followed international standards for environmental noise assessment, including ISO, ICBEN and WHO guidelines. Survey responses were grouped into three categories: Group A (Quiet background, n = 89): low-noise areas (LAeq < 55 dB); Group B (Loud background, n = 104): high-noise areas (LAeq ≥ 60 dB); and Group C (Unverified, n = 139): respondents whose locations could not be matched to specific delivery routes. Findings show that annoyance is driven more by contrast with ambient sound than absolute noise level. Findings indicate that annoyance is driven primarily by noise contrast with the local soundscape rather than absolute sound pressure level. Participants in Group A reported more frequent drone exposure than Group B (46.67% noticing drones daily vs 35.45%). The integration of perceptual data with spatial noise modelling reveals a potential need for spatially varying drone noise policy and the protection of quiet areas. This research presents a scalable framework for assessing UAV noise impacts using perception analysis and supports context-sensitive planning for urban drone deployment.
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14:10
20 mins
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Drone noise impact in urban environment, from drone trajectory to noise maps
Elise Ruaud, Ingrid LeGriffon
Abstract: As drones might become a reality in cities, with various types of applications such as medical deliveries, commercial goods deliveries, or even surveillance and monitoring missions, it is essential to assess their potential impact on citizens’ quality of life. To this end, an acoustic modeling chain has been implemented to evaluate drone noise impact in urban environment. Starting from a drone model and scenario information, one can compute drone noise generation and propagation in the city. The impact is analysed via acoustic indicators, which can be processed into acoustic noise maps but also correlated to the corresponding temporal and geographical variations in population presence throughout the day. The work presented in this paper is part of the European MUSE project which aims to develop a performance framework, indicators, and tools to measure the social and environmental impacts of Urban Air Mobility (UAM). More particularly, this paper presents the acoustic analysis realized by applying the proposed approach to a case study simulating commercial drone deliveries in Madrid city center. Eight acoustic indicators (maximum and equivalent sound pressure level, day-evening-night equivalent level, sound exposure level, time above, emergence, number of event and intermittency ratio) are used to characterize and interpret the acoustic impact of this scenario. The overall analysis is complemented by targeted comparisons between specific flights. Their interpretation allows for conclusions both on necessary methodological improvements to the toolchain and on key phenomena of interest in the assessment of drone noise within complex urban environments.
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14:30
20 mins
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Comparison of sound evaluations obtained in laboratory experiments vs. remote tests via app
Susanne Bartels, Stephen Schade, Rahman Al Mahmudur, David Straub, Carla Bubeck, Clémence Dubois
Abstract: The assessment of aircraft sounds through listening experiments conducted with human subjects in a controlled laboratory setting is a time-consuming and expensive process. Current research is now exploring alternative methods for conducting these experiments in more natural environments, such as the homes of test subjects, further allowing studies to include more participants and collect a greater number of assessments.
One of the main challenges of conducting remote listening tests is to establish standardized testing procedure and equipment that are comparable to the controlled conditions of a laboratory. This includes, for instance, accurately calibrating the output levels of headphones used in the tests and the adaptation of response scales and instructions for the sound evaluations. Additionally, there is a lack of data on whether subjects evaluate sounds in remote tests in a similar manner to laboratory experiments.
In the ongoing VIRLWINT-project, the German Aerospace Center has developed an interactive App enabling test subject to configure novel aircraft with electrified distributed propulsion, to listen to the resulting fly-over sounds, and to evaluate the unpleasantness and annoyance induced by the sounds. The present study investigates the extent to which the sound perceptions in conventional listening experiments in the laboratory differ from results obtained via the App in less controlled environments. For this purpose, 18 test subjects went through the following test sections in a balanced order and evaluated the same sounds: a) highly controlled laboratory environment + standard equipment, b) highly controlled laboratory environment + App, c) less controllable home environment + App.
The presentation provides a detailed overview of the methodology and research questions, as well as initial findings from the comparison of test environments and equipment.
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14:50
20 mins
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Scenarios for proactive planning of implementation of UAM in Stockholm
Pernilla Ulfvengren
Abstract: In this paper we will present our methods for preparing relevant scenarios for traffic from drone services. With these we can work with both normative and explorative scenarios. With these scenarios integrated in our traffic model and noise prognosis we may answer questions like: How much traffic will the threshold be for health effects? How much traffic are we talking about in a near worst case scenario given drones service concepts discussed currently?
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