Reduced Order Models in Analysis of Stochastically Parametered Linear Dynamical Systems

被引：1
|
作者：
Lal, Hridya P. [1 ]
Godbole, Siddhesh M. [1 ]
Dubey, Jainendra K. [1 ]
Sarkar, Sunetra [2 ]
Gupta, Sayan [1 ]
机构：
[1] Indian Inst Technol, Dept Appl Mech, Madras 600036, Tamil Nadu, India
[2] Indian Inst Technol, Dept Aerosp Engn, Madras 600036, Tamil Nadu, India
来源：
INTERNATIONAL CONFERENCE ON VIBRATION PROBLEMS 2015 | 2016年 / 144卷
关键词：
Reduced order modelling; SEREP; PCE; PETSc; RANDOM EIGENVALUE PROBLEM;
D O I：
10.1016/j.proeng.2016.05.161
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
This study focusses on the development of reduced order models, which minimize the computational costs without compromising on the accuracy in the numerical analysis of stochastically parametered linear dynamical systems. A scheme based on polynomial chaos expansion (PCE) and system equivalent reduction expansion process (SEREP) has been developed that enable formulation of reduced order models. Further measures for enhancing the computational efficiency include using sparse grids in conjunction with code parallelization. Interfacing algorithms have been developed that enable finite element (FE) modeling of complex systems using commercial FE softwares and the developed codes. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：1325 / 1331
页数：7
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