A data-driven two-microphone method for in situ sound absorption measurements of porous materialsa).

This work presents a data-driven approach to estimating the sound absorption coefficient of an infinite porous slab using a neural network and a two-microphone measurement on a finite porous sample. A one-dimensional-convolutional network predicts the sound absorption coefficient from the complex-valued transfer function between the sound pressure measured at the two microphone positions. The network is trained and validated with numerical data generated by a boundary element model using the Delany-Bazley-Miki model, demonstrating accurate predictions for various numerical samples.

Bayesian reconstruction of surface shape from phaseless scattered acoustic data.

The recovery of the properties or geometry of a rough surface from scattered sound is of interest in many applications, including medicine, water engineering, or structural health monitoring. Existing approaches to reconstruct the roughness profile of a scattering surface based on wave scattering have no intrinsic way of predicting the uncertainty of the reconstruction. In an attempt to recover this uncertainty, a Bayesian framework, and more explicitly, an adaptive Metropolis scheme, is used to infer the properties of a rough surface, parameterised as a superposition of sinusoidal components.

Drone noise directivity and psychoacoustic evaluation using a hemispherical microphone array.

This paper proposes an experimental setup for measuring the sound radiation of a quadrotor drone using a hemispherical microphone array. The measured sound field is decomposed into spherical harmonics, which enables the evaluation of the radiation pattern to non-probed positions. Additionally, the measurement setup allows the assessment of noise emission and psychoacoustic metrics at a wide range of angles.

Surface shape reconstruction from phaseless scattered acoustic data using a random forest algorithm.

Recent studies have demonstrated that acoustic waves can be used to reconstruct the roughness profile of a rigid scattering surface. In particular, the use of multiple microphones placed above a rough surface as well as an analytical model based on the linearised Kirchhoff integral equations provides a sufficient base for the inversion algorithm to estimate surface geometrical properties. Prone to fail in the presence of high noise and measurement uncertainties, the analytical approach may not always be suitable in analysing measured scattered acoustic pressure.

Angle-dependent sound absorption estimation using a compact microphone array.

This paper proposes a method for estimating the angle-dependent sound absorption coefficient of a large material sample using a compact microphone array. The method relies on the description of the pressure field as a pair of in-going and out-going waves or using an image source model and stands as a generalization of the classical two-microphone method. The array includes an irregular spacing normal to the surface to avoid spatial aliasing.

Derivation of the state matrix for dynamic analysis of linear homogeneous media.

A method to obtain the state matrix of an arbitrary linear homogeneous medium excited by a plane wave is proposed. The approach is based on projections on the eigenspace of the governing equations matrix. It is an alternative to manually obtaining a linearly independent set of equations by combining the governing equations.

Inverse estimation of the elastic and anelastic properties of the porous frame of anisotropic open-cell foams.

This paper presents a method for simultaneously identifying both the elastic and anelastic properties of the porous frame of anisotropic open-cell foams. The approach is based on an inverse estimation procedure of the complex stiffness matrix of the frame by performing a model fit of a set of transfer functions of a sample of material subjected to compression excitation in vacuo. The material elastic properties are assumed to have orthotropic symmetry and the anelastic properties are described using a fractional-derivative model within the framework of an augmented Hooke's law.