Non-negative intensity for planar structures under stochastic excitation

Abstract

Identification of regions on a vibrating structure which radiate energy to the far field is critical in many areas of engineering. Non-negative intensity is a means to visualize contributions of local surface regions to sound power from vibrating structures. Whilst the non-negative intensity has been used for structures under deterministic excitation due to structural forces or harmonic incident acoustic pressure excitation, it has not been considered for analyzing a structure under stochastic excitation. This work analytically formulates non-negative intensity in the wavenumber domain to investigate the surface areas on a vibrating planar structure that are contributing to the radiated sound power in the far field. The non-negative intensity is derived in terms of the cross spectrum density function of the stochastic field and the sensitivity functions of either the acoustic pressure or normal fluid particle velocity. The proposed formulation can be used for both infinite planar structure and finite plate in an infinite baffle. To demonstrate the technique, a simply supported baffled panel excited by a turbulent boundary layer as well as an acoustic diffuse field is considered and those regions contributing to the radiated sound power are identified. It is demonstrated that the nonnegative intensity distribution is dependent on the stochastic excitation. It is also found that for a panel under stochastic excitation the more the nonnegative intensity distribution is concentrated within the panel surface, the

Synthesis of wall pressure fields of non-homogeneous turbulent boundary layers for vibroacoustic simulations

“…For frequencies well above the aerodynamic coincidence frequency, the panel can generally be seen as a low-wavenumber filter and the convective contributions of the WPF have a negligible effect on the plate response. It results that the cutoff wavenumber can be defined according to the flexural wavenumber of the plate k f (see for instance Karimi et al (2020b)):…”