Prediction and reduction of aircraft noise in outdoor environments

Bao N Tong, Purdue University


This dissertation investigates the noise due to an en-route aircraft cruising at high altitudes. It offers an improved understanding into the combined effects of atmospheric propagation, ground reflection, and source motion on the impact of en-route aircraft noise. A numerical model has been developed to compute pressure time-histories due to a uniformly moving source above a flat ground surface in the presence of a horizontally stratified atmosphere. For a moving source at high elevations, contributions from a direct and specularly reflected wave are sufficient in predicting the sound field close to the ground. In the absence of wind effects, the predicted sound field from a single overhead flight trajectory can be used to interpolate pressure time histories at all other receiver locations via a simplified ray model for the incoherent sound field. This approach provides an efficient method for generating pressure time histories in a three-dimensional space for noise impact studies. A variety of different noise propagation methods are adapted to a uniformly moving source to evaluate the accuracy and efficiency of their predictions. The techniques include: analytical methods, the Fast Field Program (FFP), and asymptotic analysis methods (e.g., ray tracing and more advanced formulations). Source motion effects are introduced via either a retarded time analysis or a Lorentz transform approach depending on the complexity of the problem. The noise spectrum from a single emission frequency, moving source has broadband characteristics. This is a consequence of the Doppler shift which continuously modifies the perceived frequency of the source as it moves relative to a stationary observer on the ground. Thus, the instantaneous wavefronts must be considered in both the frequency dependent ground impedance model and the atmospheric absorption model. It can be shown that the Doppler factor is invariant along each ray path. This gives rise to a path dependent atmospheric absorption mechanism due to the source's motion. To help mitigate the noise that propagates to the ground, multi-layered acoustic treatments can be applied to provide good performance over a wide range of frequencies. An accurate representation of material properties for each of the constituent layers is needed in the design of such treatments. The parameter of interest is the specific acoustic impedance, which can be obtained via inversion of acoustic transfer function measurements. However, several different impedance values can correspond to the same sound field predictions. The boundary loss factor F (associated with spherical wave reflection) is the source of this ambiguity. A method for identifying the family of solutions and selecting the physically meaningful branch is proposed to resolve this non-uniqueness issue. Accurate deduction of the acoustic impedance depends on precise measurements of the acoustic transfer function. However, measurement uncertainties exists in both the magnitude and the phase of the acoustic transfer function. The ASA/ANSI S1.18 standard impedance deduction method uses phase information, which can be unreliable in many outdoor environments. An improved technique which only relies on magnitude information is developed in this dissertation. A selection of optimal geometries become necessary to reduce the sensitivity of the deduced impedance to small variations in the measured data. A graphical approach is provided which offers greater insight into the optimization problem. A downhill simplex algorithm has been implemented to automate the impedance deduction procedure. Physical constraints are applied to limit the search region and to eliminate rogue solutions. Several case studies consisting of both indoor and outdoor acoustical measurements are presented to validate the proposed technique. The current analysis is limited to locally reacting materials where the acoustic impedance does not depend on the incidence angle of the reflected wave.




Li, Purdue University.

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