Model uncertainties in computational viscoelastic linear structural dynamics

被引：3
作者：
Capillon, R. [1 ]
Desceliers, C. [1 ]
Soize, C. [1 ]
机构：
[1] Univ Paris Est, Lab Modelisat & Simulat Multiechelle, MSME, CNRS,UMR 8208, 5 Bd Descartes, F-77454 Marne La Vallee, France
来源：
X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017) | 2017年 / 199卷
关键词：
Uncertainty quantification; Viscoelastic; Nonparametric probabilistic approach; Structural dynamics; Hilbert transform; Kramers-Kronig relations; Reduced-order model;
D O I：
10.1016/j.proeng.2017.09.250
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
This paper deals with the analysis of the propagation of uncertainties in computational linear dynamics for linear viscoelastic composite structures in the presence of uncertainties. In the frequency domain, the generalised damping matrix and the generalised stiffness matrix of the stochastic computational reduced-order model are random frequency-dependent matrices. Due to the causality of the dynamical system, these two frequency-dependent random matrices are statistically dependent and their probabilistic model involves a Hilbert transform. In this paper, a computational analysis of the propagation of uncertainties is presented for a composite viscoelastic structure in the frequency range. (C) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：1210 / 1215
页数：6
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