Methods for Improving Comparability of Propeller Acoustic Experiments Conducted at Different Facilities and Scales

Abstract

Development of urban air mobility (UAM) vehicles are on the rise, and their noisy operation near many people can cause negative health effects, so it is important to quickly understand their acoustic behaviors. This is done through many conduits, including computational fluid dynamics (CFD), outdoor field tests, and controlled indoor experiments. Outdoor field tests allow for full-scale vehicle testing, but subjects the test article to uncontrollable, unpredictable variables, whereas indoor experiments are much more controllable and predictable, but such indoor experiments are often constrained by space and are unable to test the full-scale vehicle. Research should develop methods to improve comparability between indoor and outdoor acoustic experiments. The presented work aims to provide such methods with three experiments: one investigating ground board acoustic behavior in an anechoic chamber, one investigating propeller noise in an outdoor facility, and one investigating propeller noise in an indoor facility. Ground boards are thin rigid boards, typically in the shape of a 1m diameter circle a few millimeters thick, and are standardized for use [5] [10] [11] [13] in outdoor acoustic experiments to mount microphones and provide a consistent reflective surface. An experiment was conducted in an anechoic chamber to observe the behavior of a 1m diameter, 6mm thick plywood ground board with the noise source at various incidence angles and with the microphone lain at the center and at three-quarters the radius of the ground board. The configuration of interest is a 23° incidence angle with the microphone at the center since this is the configuration used in the outdoor field test. With this configuration, the behavior of the ground board is similar to that of a perfect reflector (6dB increase in measured sound pressure level (SPL)) within about 200Hz to 10000Hz. Below 2000Hz, the shallower source angles (20°, 23°, and 45°) have a lower SPL magnification; in the 2000Hz to 8000Hz frequency range, there appears to be little dependence of ∆P SD on the source angle; above 8000Hz, the higher source angles (65° and 80°) have a lower SPL magnification. With the microphone lain at three-quarters the radius of the ground board, a similar trend was observed, but its sensitivity to the source angle was lower. A Techsburg Inc. propeller was tested in an outdoor facility at two scales: 0.9144m and 0.4572m diameters. The propeller was mounted with its center 1.905m above the ground, and 13 microphones were placed on top of ground boards in a 4.572m semicircle around the propeller, ranging from upstream to downstream of the propeller. Wind measurements were simultaneously collected from an anemometer a few meters away from the microphone arc. The background noise at this facility was significant up to about 800Hz, and motor noise was significant around 5000Hz to 9000Hz. Wind velocity data was collected simultaneously to acoustics, and a relationship was found between broadband noise and inflow velocity. The total propeller noise was decomposed into broadband and tonal components through phase averaging methods, and it was found that the overwhelming majority of the noise was dominated by the broadband component. Generally, when the inflow velocity was about −1m/s to 0.5m/s, the broadband noise within 2000Hz to 5000Hz was about 1dB to 2dB louder than when the inflow velocity was about 0.5m/s to 3m/s. Furthermore, the spectra calculated from when the inflow velocity was between −1m/s and 0.5m/s was much more comparable to the Gill-Lee Spectrum Model (GLSM), a trailing edge noise prediction model trained on hundreds of propeller noise datasets primarily at a hover condition. To compare the two scales, the tip Mach number was held constant, so the 0.9144m diameter propeller rotated half as fast as the 0.4572m diameter propeller, resulting in half the blade passage frequency (BPF) and twice the harmonics. The broadband noise of the larger propeller peaked around 2000Hz, whereas the smaller propeller's broadband curve peaked around 4500Hz. This relative peak behavior is reflected in the GLSM, although the GLSM generally overpredicts both scales. The expected difference in tones between the two scales was calculated from the thrust squared to be approximately 11dB, and the observed difference in tones was observed to be approximately 7dB at most. However, these thrust measurements were averaged over the entire sampling period, so the absolute magnitude of this calculation should be considered with reasonable skepticism. The reduction in pitch angle resulted in quieter broadband noise, which is expected since this would reduce thrust and therefore reduce noise. The addition of turbulence trips did not result in the expected consistent increase in broadband noise, but this may be due to the inherent difficulty of outdoor acoustic experiments: the environmental conditions in field tests are uncontrollable, and sequestration was unable to isolate period of similar wind velocities, so the two datasets were not entirely comparable. A similar experiment was performed in an anechoic wind tunnel, the Virginia Tech Subsonic Modular Anechoic Research Tunnel (VTSMART), to observe the effects of test facility. Five microphones were mounted at the same height as the propeller 1.016m away from the propeller, evenly spaced by 10° between each, starting from 10° upstream to 30° downstream. A sixth microphone was mounted further downstream closer to the axis of rotation. Due to size constraints of the wind tunnel, only the 0.4572m diameter propeller was tested at this facility. Background noise was much quieter and more consistent than the outdoor facility, and the SNR was positive throughout 100Hz to 20000Hz. Spectrograms were generated for both background and propeller noise measurements, and both were found to be relatively constant in time, so the background noise was directly subtracted from the propeller noise measurements. Again, the total propeller noise was broken into broadband and tonal components, and the majority of the noise was still composed of the broadband component. The tunnel was operated at two conditions: one without flow and one with 4m/s flow. Between the two tunnel conditions, the broad spectral features did not change significantly, and the largest differences were observed in the tonal features. With 4m/s flow, the tones at the BPF were quieter than without flow by approximately 5dB. The GLSM generally captured the broad spectral features at the indoor facility better than at the outdoor facility, typically within about 3dB of the experimental data. The data from both experiments were compared to each other after a correction to account for the difference in distance. The outdoor broadband noise with an inflow velocity of about 0.5m/s to 3m/s was similar to the indoor broadband noise with 4m/s flow in the 2000Hz to 6000Hz range within about 2dB, and a similar result is seen when comparing the outdoor broadband noise with an inflow velocity of −1m/s and 0.5m/s to the indoor broadband noise with no flow. All configurations were again compared to each other at this facility, but much smaller differences were observed. This is likely due to the confinement of the wind tunnel facility and the inability of the wake to be convected far enough downstream of the propeller, causing these broadband noise sources to dominate over changes in pitch and turbulence trips. In each experiment, there are many limitations and possible improvements with further research. For the ground board experiment, more source incidence angles, microphone orientations, and surrounding substrates could be tested, which would improve the understanding of ground board response. Such research has been done in the past [2] [4] [14] [22]. For the outdoor Drone Park experiment, the ground boards could have been calibrated before collecting propeller acoustics so that measurements could be properly corrected for the effects of the ground board in the field. Wind anemometer data could also be fully synchronized to the propeller acoustics such that direct correlations would be more meaningful. Similarly, synchronized performance data should be collected as well, specifically thrust and torque, which would allow for more accurate GLSM calculations, since this model takes thrust into consideration. For the indoor VTSMART experiment, particle imaging velocimetry (PIV) could be conducted to observe the physical phenomena and confirm if the confinement of the wind tunnel is indeed causing the wake to loiter near the propeller.