Title: An extension to random point process theory for predictiong the vibration response of uncertain structures
Authors: Langley, Robin S.
Cicerello, Alice
Deckers, Elke
Issue Date: Sep-2014
Host Document: Proceedings of the 26th International Conference on Noise and Vibration Engineering (ISMA2014) pages:2293-2304
Conference: International Conference on Noise and Vibration Engineering location:Leuven, Belgium date:15-17 September 2014
Abstract: In the high-frequency range, there have been advances in the use of non-parametric uncertainty models to predict the vibration response of uncertain structures. In particular, the Statistical Energy Analysis (SEA) approach has been combined with the Random Point Process Theory (RPPT) to yield the non-parametric ensemble variance of the subsystem energies without requiring Monte Carlo Simulations (MCS) to be performed to propagate the uncertainty. The assumptions behind the RPPT are that the generalised forces acting on a single subsystem and the mode shapes (computed at the points where the forces are applied) are statistically independent and identically distributed. These assumptions are valid for a large variety of cases; however, it has been found that correlation effects can have a significant effect on the response variance in some cases, particularly when the modal overlap is high. In this paper, the correlation effects are quantified for the case of a system driven by multiple random point loads. It is then shown how these correlation effects can be accounted for in response predictions: closed form analytical solutions are derived for the case of a single random point load, and an efficient numerical method is derived for multiple point loads. The approach is illustrated by application to a randomly driven plate system.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Production Engineering, Machine Design and Automation (PMA) Section

Files in This Item:
File Description Status SizeFormat
isma2014_0348.pdfpaper Published 217KbAdobe PDFView/Open Request a copy

These files are only available to some KU Leuven Association staff members


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science