11:40
Session 11: Experimental Aeroacoustic Measurements – Laboratory 2
Chair: Damiano Casalino
11:40
20 mins
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Psychoacoustic Assessment of Small-Scale Propeller Noise Generation Mechanisms
Isaac Bensignor, Roberto Merino-Martinez, 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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12:00
20 mins
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Mitigation of UAV Airframe Interaction Noise Using Porous Coatings
Craig Gillespie, Matthew Mulcahy, Gareth Bennett, John Kennedy
Abstract: Rapid growth of unmanned aerial vehicles (UAVs) in the last-mile delivery sector has raised concerns over the emission of noise into urban and suburban settings. This is due to the distinct character of the noise which features both tonal components and high frequency broadband noise. In the Irish context commercial drone operations have completed over 200,000 deliveries to date. This scale of commercial operations of commercial deliveries has led to noise complaints despite levels significantly below urban traffic noise. Commercial operators require low-cost, off the shelf solutions to mitigate the noise of operations and increase societal acceptance of drone operations. This project investigated the viability of using a porous mesh applied to the rotor arm/boom supporting the rotor system (motor + propeller) with the intention of reducing airframe interaction noise.
The coatings are additively manufactured with low-cost MSLA printers. The coatings are designed as a custom sleeve that slides onto the boom. The coating consists of a lattice structure of Kelvin cells selected for printability using MSLA processes giving repeatable pore geometry. The porosity of the coating is controlled through a combination of cell size and cell strut thickness. The parameters of the coating are empirically optimised through a cycle of rapid manufacture and testing. The noise reduction is evaluated on both single and coaxial contra-rotating rotor setups with 406 mm diameter rotors in compliance with ISO 3744 sound power measurements. Comparison is made to a control with no coating and several coating types varying coating depth, fairing shape, porosity and unit cell dimensions are tested. The impact of the coatings on thrust performance and aerodynamics is also evaluated. The flow field around the rotor is measured with a hot-wire anemometry probe mounted on a robotic traversing arm to measure the flow field upstream, downstream and inter-rotor. Flow field tests are also conducted with a crossflow of up to 16m/s, a common speed for a commercial delivery drone. It is planned that the optimised coating will be utilised for a flight test study on a commercial drone to assess the noise reduction achieved in the field.
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12:20
20 mins
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Characterisation of Drone Noise in Complex Airflow
Philip McCarthy, Sean McTavish, Hali Barber
Abstract: Operational concepts for Advanced Air Mobility (AAM) vehicles typically consists of extended flights within or in close proximity to urban environments. The airflow present in these environments is often complex, exhibiting localised spatial and temporal variations in wind speed, wind direction, and turbulence levels. Within the broader AAM class of vehicles, the smaller size of drones makes them particularly vulnerable to these complex flow structures; altering the overall levels and sound characteristics, as well influencing the broader noise-propagation from the vehicles into the urban landscape.
When modelling populations noise exposure associated with these operations, the effects of the complex urban airflow are often neglected and instead the noise emissions associated with steady or benign flight conditions are assumed. While in many cases this is adequate, when highly accurate levels are required or human perception is being considered, time-variant sound characteristics must be properly modelled. This study provides an initial attempt to experimentally characterise the noise from a drone flying within this complex airflow, specifically flying in a wind tunnel under controlled turbulence representative of that measured in urban environments.
Wind tunnel testing has been performed using a DJI Matrice 300 drone at the Honda Aerodynamic Laboratories of Ohio (HALO) wind tunnel (See Figure 1). The drone was flown in wind speeds up to 15m/s and turbulence intensities up to approximately 20% of the freestream velocity. Acoustics measurements were conducted using a sideline microphone array, a forward microphone array, and flush mounted floor microphones. Initial spectral analysis from select individual microphones show that turbulent airflow causes a spread in the tonal peaks associated with the fundamental Blade Passage Frequency and its lower order harmonics. This primarily results from the RPM oscillations required to maintain stability within the unsteady flow. Further analysis, including acoustic beamforming and calculation of the psychoacoustic metrics, is currently underway to identify the significant impacts of turbulence on the drone acoustic characteristics that are relevant for noise exposure modelling.
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