Speaker
Description
Predicting high-frequency noise and vibration in complex structures is a challenging task where standard numerical methods for wave-based models struggle with the rapid oscillations involved, leading to prohibitive computational costs. While methods like Statistical Energy Analysis (SEA) or ray tracing are popular alternatives, Dynamical Energy Analysis (DEA) offers a more robust approach by using a transfer operator to track ray densities in phase-space. The result is a high-frequency modelling tool that is neither subject to SEA’s strong restrictions on the wave behaviour within carefully chosen sub-structures, nor restricted by the reflection order. This research introduces a data-driven version of DEA based on Extended Dynamic Mode Decomposition. Here, the data driven construction of the transfer operator facilitates a division of the phase-space into clusters where the ray flow map is locally smooth. The accuracy may then be further enhanced by using Legendre polynomial basis expansions within these clusters and/or the further sub-division of the phase-space.