How do you take a reliable measurement of a material whose microstructure is random? When using wave scattering, the answer is often to take an ensemble average (average over time or space). By ensemble averaging we can calculate the average scattered wave and the effective wavenumber. To date, the literature has focused on calculating the effective wavenumber for a plate filled with particles. One clear unanswered question was how to extend this approach to a material of any geometry and for any source. For example, does the effective wavenumber depend on only the microstructure, or also on the material geometry?
Materials comprising randomly distributed particles, or inclusions, occur frequently in the world around us. Common examples include composites, emulsions, suspensions, complex gases, etc... This paper is the first to clearly prove that, contrary to the belief of most in the community, multiple effective waves propagate in particulate materials (in an ensemble-average sense).
We show that in general there is not only one effective wave, but there is a series of effective waves in an ensemble averaged particulate material. By particulate material we mean a medium filled with randomly placed particles and consider waves …
[MultipleScattering.jl](https://github.com/jondea/MultipleScattering.jl): a Julia library for simulating, processing, and plotting multiple scattering of acoustic waves.
To what extent can particulate random media be characterised using direct wave backscattering from a single receiver/source? Here, in a two-dimensional setting, we show using a machine learning approach that both the particle radius and concentration …
We formally deduce closed-form expressions for the transmitted effective wavenumber of a material comprising multiple types of inclusions or particles (multi-species), dispersed in a uniform background medium. The expressions, derived here for the …
The aim is to understand how waves (like sound, radio, light, and vibrations) behave in materials with random microstructure.