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The work proposes a methodology for the assessment of the performances of Passive Noise Control (PNC) for passenger aircraft headrests with the aim of enhancing acoustic comfort. Two PNC improvements of headrests were designed to reduce the Sound Pressure Level (SPL) at the passengers' ears in an aircraft cabin during flight; the first was based on the optimization of the headrest shape, whereas the second consisted of partially or fully covering the headrest surface with a new highly sound-absorbing nanofibrous textile. An experimental validation campaign was conducted in a semi-anechoic chamber. A dummy headrest was assembled in different configurations of shape and materials to assess the acoustic performances associated to each set up. In parallel, simulations based on the Boundary Element Method (BEM) were performed for each configuration and an acceptable correlation between experimental and numerical results was obtained. Based on these findings, general guidelines were proposed for the acoustical design of advanced headrests. [ABSTRACT FROM AUTHOR]

Characterization of rough surface properties, such as surface shape or surface impedance, is relevant in many applications. Previous work has been done for characterizing these two aspects separately. This paper proposes a framework for characterizing rough surfaces of finite size in terms of their roughness shape and surface impedance in a single setup. The surface properties are estimated indirectly using a superposition of spatial sinusoidal components for the surface shape and a porous material model for the surface impedance. A fast multipole indirect boundary element method is employed to model the acoustic scattering problem. With the modeling flexibility from the indirect formulation, the target geometry can be simplified as a thin shell representation, which significantly improves computational efficiency. A subtraction method is proposed to mitigate the modeling error of this representation and enable the use of low driving frequencies (e.g. acoustic wavelength is comparable to or larger than the roughness scale) in the characterization. Considering the modeling accuracy of surface shape representation, a discretization criterion concerning both acoustic and spatial aspects is defined. The inverse problem is solved by means of a general-purpose optimizer, minimizing the difference between the simulated and reference acoustic field at multiple driving frequencies. Various numerical examples show that by using reference data with sufficient quality, the proposed framework can retrieve the surface shape and impedance separately, and also simultaneously. • A characterization framework estimates rough surface impedance and shape. • A thin shell modeling approach is proposed to solve the surface scattering problem. • A subtraction method is proposed to mitigate the modeling error. • Multiple relatively low driving frequencies are used in the framework. • An adaptive discretization criterion is defined for surface shape characterizations. [ABSTRACT FROM AUTHOR]

• FMBEM and FDTD are benchmarked in room acoustic modelling and simulations. • The model uncertainties of using the two solvers are presented and studied. • The two solvers are evaluated with increasing complexity of material input properties. • Both FMBEM and FDTD can give close predictions in most of the scenarios. • Input material data results in large deviations between simulation and measurement. Compared to geometrical acoustics, wave-based methods which solve the wave equation either in the time domain or in the frequency domain are known for their high accuracy. However, their systematic use as professional room acoustic simulation tools is less popular due to the modelling effort and computational time requirements, especially in the case of complex scenarios. This paper aims at providing guidelines for the use of two wave-based methods in complex room acoustics simulations, namely the finite-difference time-domain (FDTD) method and the fast multipole boundary element method (FMBEM). Numerical experiments are conducted to address the convergence issues of the two solvers, more specifically, the selection of the convergence tolerance of the iterative solver in FMBEM and the temporal sampling frequency in FDTD. To evaluate the capability of the solvers in simulating complex scenarios, five cases with increasing complexity of material input data are presented. The results show that both solvers give close predictions for various room acoustics parameters. In addition, an uncertainty sensitivity study is performed in a case where experimental data is available. Large deviations between measured and simulated reverberation time reveal that typical material data-sets poorly represent the behaviour of real materials in a room acoustics context. Lastly, the efficiency of the two solvers is discussed. With parallelization implemented, both solvers can simulate sizeable room acoustic problems with good accuracy within a reasonable time. [ABSTRACT FROM AUTHOR]