Robust estimation of coupling loss factors from finite element analysis

There are well-established techniques by which the coupling loss factors (CLFs) of statistical energy analysis (SEA) can be estimated from finite element analysis (FEA). These are typically based on a single, selected system. A slightly different choice of system would give different estimates. Ther...

Full description

Saved in:
Bibliographic Details
Published in:Journal of sound and vibration 2007-06, Vol.303 (3), p.814-831
Main Authors: Thite, A.N., Mace, B.R.
Format: Article
Language:English
Subjects:
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Physics
Solid mechanics
Structural and continuum mechanics
Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:There are well-established techniques by which the coupling loss factors (CLFs) of statistical energy analysis (SEA) can be estimated from finite element analysis (FEA). These are typically based on a single, selected system. A slightly different choice of system would give different estimates. There is a need for robust methods that give good estimates of the SEA average CLFs, independent of the details of the chosen system. Estimates of variance, confidence limits, are also of interest. Two approaches to this problem are discussed. These involve attempts to randomise the properties of the system and averaging the resulting estimates, but without repeating the full FEA. The first involves perturbation of component modal properties which can be related to perturbations in the modes of the assembled structure and hence to the energies and CLFs. In the second approach, it is assumed that the statistics of the modal properties of the system analysed are a fair representation, when taken over a wide enough frequency range, of the statistics of the modes of the SEA ensemble. The modes of the system are then randomly sampled to provide robust estimates. Numerical examples are presented. The methods are computationally very cheap.
ISSN:0022-460X
1095-8568
DOI:10.1016/j.jsv.2007.02.004