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An efficient probabilistic approach to vibro-acoustic analysis based on the Gaussian orthogonal ensemble
Edwin Reynders1, Julien Legault2, Robin S Langley2
1Department of Civil Engineering, KU Leuven, Kasteelpark Arenberg 40, B-3001 Leuven, Belgium.
The Journal of the Acoustical Society of America
|July 5, 2014
Summary
This study presents a new vibro-acoustic analysis method to efficiently compute responses and quantify uncertainties in complex systems. The approach overcomes limitations of statistical energy analysis for wave scattering effects.
Area of Science:
- Computational mechanics
- Vibro-acoustic analysis
- Wave scattering phenomena
Background:
- Higher frequency vibro-acoustic analysis of complex systems presents challenges in managing degrees of freedom (DOFs) and quantifying response uncertainty due to wave scattering.
- Existing methods like statistical energy analysis have limitations in addressing these challenges effectively.
Purpose of the Study:
- To develop a general method for vibro-acoustic analysis that efficiently computes system responses and quantifies uncertainties.
- To overcome the limitations of statistical energy analysis in handling wave scattering effects in complex systems.
Main Methods:
- Numerically compute an artificial ensemble of realizations for system components sensitive to random wave scatterers.
- Utilize the properties of Gaussian orthogonal ensemble spacings and Gaussian random fields for efficient computation.
- Limit the degrees of freedom (DOFs) to deterministic components and interface DOFs of random components.
Main Results:
- The method effectively computes vibro-acoustic responses and quantifies uncertainties in complex systems.
- Validated on plate structures, showing good agreement with detailed parametric probabilistic models.
- Demonstrated accuracy even in cases with low modal overlap, single point loading, and strong subsystem coupling.
Conclusions:
- The presented method offers a robust solution for high-frequency vibro-acoustic analysis of complex systems.
- It efficiently manages computational complexity and accurately quantifies uncertainties arising from wave scattering.
- The approach provides a significant advancement over existing methods like statistical energy analysis.
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