TBL-induced energy transmission into a double wall backed enclosure system computed in a cloud-based Python-FE environment

Abstract

We propose a fully coupled numerical model to predict turbulent boundary layer (TBL) induced energy transmission behavior for a double-wall backed enclosure system in a finite element (FE) framework computed in cloud-based Python environment. Goody single point wall-pressure spectrum and Corcos spatial correlation function are used to generate the TBL cross-power spectra. Mindlins first order shear deformation model is considered for the panels and a fully coupled TBL-structure-acoustic model is developed using the FE approach to predict the acoustic power level inside the enclosure for variable gap distance between the panels. The model is developed in a way to capture the contribution of orthotropic lamina sequence, frequency-dependent structural damping, and stiffening orientation in predicting the energy transmission into a double-wall backed enclosure. Thus, a new numerical model is presented that enables the designers with more precise energy transmission quantification with greater flexibility in terms of the number of panel leaves, geometry, and boundary conditions of the enclosure system, backed by double wall made of isotropic or orthotropic laminates.