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Matthew A Boucher

Publications and source records attributed to Matthew A Boucher.

Introduction to the Special Issue on Advanced Air Mobility Noise: Predictions, Measurements and Perception

This Special Issue focuses on noise associated with Advanced Air Mobility (AAM), an emerging class of predominantly electric distributed-propulsion aircraft designed for urban and regional transportation. As these vehicles move toward certification and deployment, noise has become a central challenge for regulatory approval and public acceptance, particularly due to operations in densely populated areas and at low altitudes. The 24 contributions in this issue address three key aspects of AAM noise: prediction, measurement, and human perception. Prediction studies span a wide range of modeling fidelities, from high-resolution simulations to improved semi-analytical approaches, and examine complex aeroacoustic mechanisms including rotor interactions, turbulence ingestion, and broadband noise generation. Measurement studies, largely at model scale, provide new insights into tonal and broadband noise characteristics across configurations and operating conditions, while supporting model validation. Perception-focused contributions investigate annoyance, sound quality metrics, and auralization, emphasizing the role of context and operational factors in shaping human response. Together, these works highlight the interdisciplinary nature of AAM noise research and the need for integrated approaches to enable quieter vehicle design.

Perception↗

Toward a Psychoacoustic Annoyance Model for Urban Air Mobility Vehicle Noise

A psychoacoustic test was performed to obtain annoyance responses to noise from a quadrotor Urban Air Mobility (UAM) vehicle to aid in the development of a model of annoyance to UAM vehicle noise. Previous analysis of that test concluded that a psychoacoustic annoyance (PA) model, including the effects of loudness, sharpness, fluctuation strength and roughness, correlated well with the collected annoyance responses. This motivated the assessment of other PA models available in the literature, as well as the development of a new PA model based on the previously collected annoyance responses to UAM noise. To build the PA model for UAM noise, annoyance ratings to individual sounds and annoyance comparisons between pairs of sounds are first combined into a latent annoyance scale that has a correlation coefficient of 0.98 with the raw responses and that is based on just-noticeable-differences (JNDs) in annoyance. Examples for two sounds that differ in annoyance by 1 JND show when there is 75% agreement about which sound is more annoying. This latent annoyance (JND) scale also gives insight into the interplay of various perceptual components, such as overall loudness, temporal effects and spectral effects. The proposed PA model for UAM noise is fit to the latent annoyance scale, includes the sound quality effects mentioned above, as well as a term for tonality, and offers a step forward in the prediction of annoyance to UAM vehicle noise.

Urban Air Mobility↗

Perceptual Evaluation of Sound Exposure Level in Annoyance Ratings to Helicopter Noise

A psychoacoustic test was performed to assess the effectiveness of Sound Exposure Level (SEL) for indicating changes in annoyance to helicopter noise. SEL was evaluated for flyover auralizations of optimized rotor designs and for flyover recordings of different helicopters and maneuvers. The test used paired comparisons of flyovers within 10 dB of the maximum A-weighted sound pressure level. For stimuli of equal SEL, annoyance responses showed whether or not SEL is a good indicator of annoyance. While this work does not seek to determine specific attributes contributing to annoyance that are not included in SEL, the magnitude of this offset is of primary interest. Specifically, annoyance responses to relative differences in SEL allowed the calculation of an Equal Annoyance Point. Reductions in SEL lead to reductions in annoyance as expected, but for certain cases, SEL can fail to capture perceptually significant features such as audible differences due to changes in tail rotor design or unsteadiness in the sound of the helicopter.

Sound Exposure Level↗

Dose Error Correction Using Simulation Extrapolation for Community Noise Dose-Response Modeling

The objective of this work is to provide a framework to account and correct for dose error in dose-response modeling due to measurement uncertainty. Error in noise measurements, especially in the case of limited monitoring locations in a community, can lead to an attenuation or misestimation of parameters in dose-response models. This error can result in overpredicted annoyance at lower doses and underpredicted annoyance at higher doses. Simulated data in the present work are based on previous NASA community studies and incorporate a notional design for future studies with the X-59 aircraft. Several populations of different annoyance response sensitivities are included. Simulation extrapolation (SIMEX, Cook and Stefanski 1994) is used to correct for the dose error in a simple, fully pooled logistic regression. Results indicate the negative impact of attenuation is greatly diminished for all amounts of dose error considered, regardless of a population’s annoyance sensitivity. Therefore, SIMEX can help produce a more accurate dose-response relationship.

SIMEX↗