Non-stationary response of MDOF dynamical systems under combined Gaussian and Poisson white noises by the generalized cell mapping method

Xiaole Yue; Wei Xu; Yong Xu; Jian Qiao Sun

doi:10.1016/j.probengmech.2019.01.001

Non-stationary response of MDOF dynamical systems under combined Gaussian and Poisson white noises by the generalized cell mapping method

Xiaole Yue, Wei Xu, Yong Xu, Jian Qiao Sun

School of Mathematics and Statistics

Research output: Contribution to journal › Article › peer-review

34 Scopus citations

Abstract

A block matrix analysis procedure of the generalized cell mapping (GCM) method is proposed in this paper. The proposed method solves the storage problem in the response analysis of nonlinear stochastic dynamical system with the GCM method, and makes it possible to compute the non-stationary and stationary probability density functions (PDFs) of multi-degree-of-freedom (MDOF) nonlinear systems without using supercomputing. Two examples of two-degree-of-freedom systems under external or parametric excitations of combined Gaussian and Poisson white noises are presented to demonstrate the efficiency of the proposed method. Monte Carlo (MC) simulations are used to verify the accuracy of the solutions obtained with the proposed method.

Original language	English
Pages (from-to)	102-108
Number of pages	7
Journal	Probabilistic Engineering Mechanics
Volume	55
DOIs	https://doi.org/10.1016/j.probengmech.2019.01.001
State	Published - Jan 2019

Keywords

Block matrix analysis
Cell mapping method
MDOF dynamical system
Non-stationary response
Poisson white noise

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10.1016/j.probengmech.2019.01.001

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title = "Non-stationary response of MDOF dynamical systems under combined Gaussian and Poisson white noises by the generalized cell mapping method",

abstract = "A block matrix analysis procedure of the generalized cell mapping (GCM) method is proposed in this paper. The proposed method solves the storage problem in the response analysis of nonlinear stochastic dynamical system with the GCM method, and makes it possible to compute the non-stationary and stationary probability density functions (PDFs) of multi-degree-of-freedom (MDOF) nonlinear systems without using supercomputing. Two examples of two-degree-of-freedom systems under external or parametric excitations of combined Gaussian and Poisson white noises are presented to demonstrate the efficiency of the proposed method. Monte Carlo (MC) simulations are used to verify the accuracy of the solutions obtained with the proposed method.",

keywords = "Block matrix analysis, Cell mapping method, MDOF dynamical system, Non-stationary response, Poisson white noise",

author = "Xiaole Yue and Wei Xu and Yong Xu and Sun, {Jian Qiao}",

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier Ltd",

year = "2019",

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doi = "10.1016/j.probengmech.2019.01.001",

language = "英语",

volume = "55",

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journal = "Probabilistic Engineering Mechanics",

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TY - JOUR

T1 - Non-stationary response of MDOF dynamical systems under combined Gaussian and Poisson white noises by the generalized cell mapping method

AU - Yue, Xiaole

AU - Xu, Wei

AU - Xu, Yong

AU - Sun, Jian Qiao

PY - 2019/1

Y1 - 2019/1

N2 - A block matrix analysis procedure of the generalized cell mapping (GCM) method is proposed in this paper. The proposed method solves the storage problem in the response analysis of nonlinear stochastic dynamical system with the GCM method, and makes it possible to compute the non-stationary and stationary probability density functions (PDFs) of multi-degree-of-freedom (MDOF) nonlinear systems without using supercomputing. Two examples of two-degree-of-freedom systems under external or parametric excitations of combined Gaussian and Poisson white noises are presented to demonstrate the efficiency of the proposed method. Monte Carlo (MC) simulations are used to verify the accuracy of the solutions obtained with the proposed method.

AB - A block matrix analysis procedure of the generalized cell mapping (GCM) method is proposed in this paper. The proposed method solves the storage problem in the response analysis of nonlinear stochastic dynamical system with the GCM method, and makes it possible to compute the non-stationary and stationary probability density functions (PDFs) of multi-degree-of-freedom (MDOF) nonlinear systems without using supercomputing. Two examples of two-degree-of-freedom systems under external or parametric excitations of combined Gaussian and Poisson white noises are presented to demonstrate the efficiency of the proposed method. Monte Carlo (MC) simulations are used to verify the accuracy of the solutions obtained with the proposed method.

KW - Block matrix analysis

KW - Cell mapping method

KW - MDOF dynamical system

KW - Non-stationary response

KW - Poisson white noise

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U2 - 10.1016/j.probengmech.2019.01.001

DO - 10.1016/j.probengmech.2019.01.001

M3 - 文章

AN - SCOPUS:85060459847

SN - 0266-8920

VL - 55

SP - 102

EP - 108

JO - Probabilistic Engineering Mechanics

JF - Probabilistic Engineering Mechanics

ER -

Non-stationary response of MDOF dynamical systems under combined Gaussian and Poisson white noises by the generalized cell mapping method

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Keywords

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