H-Matrix BEM and FEM AO solvers for large professional audio system simulation

Nowadays the effectiveness of computational codes is indeed recognized in a variety of scientific and industrial applications. In particular, analysis pertinent to multibody systems, multiphysics and multiobjective optimization could not be dealt without computational codes support. The possibility of designing components and/or whole assemblies in an efficient and cost-effective way will call for reliable simulation methods to tackle real industrial cases. The acoustic analysis has to satisfy quite challenging requirements as being able both to span the large audio frequency range and to model large problems in a reasonable calculation time. This article documents the progress of commercially available computational methodologies to predict large professional arrayable audio system's far field behaviour. The very last techniques developed by LMS's Virtual Lab Rev12, i.e. the H-Matrix boundary element (H-Matrix BEM) and the FEM Adaptive Order (FEM AO) solvers, have been thoroughly tested to efficiently simulate the far field acoustic directional characteristics of an Arrayable Loudspeaker's Horn in comparison with the full space far field measured Acoustic Balloon. The whole simulation model is solved up to high audio frequencies (12 kHz) in a far field's Balloon grid of virtual microphones. Precise angular far field directivity measurements have been carried out by means of a state-of-the-art testing experimental set-up. Full results comparison is shown by frequency and angle. Cluster loudspeaker arrays configurations have been also simulated and the results in the far field are compared to measurements to evaluate the impact of this streamlined approach to large problems. Along with other advanced analysis techniques such as Fast Multipole BEM and FEM AML, H-Matrix and FEM AO help the designer by reducing CAE complexity and simplifying remarkably the initial finite element meshes. These efficient solvers allow to drastically speed-up computation time and reduce memory consumption.