On practical integration of semi-discretized nonlinear equations of motion. Part 1: Reasons for probable instability and improper convergence

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  • University of Tehran
  • Tehranpars
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OriginalspracheEnglisch
Seiten (von - bis)705-731
Seitenumfang27
FachzeitschriftJournal of sound and vibration
Jahrgang284
Ausgabenummer3-5
PublikationsstatusVeröffentlicht - 21 Juni 2005

Abstract

Time integration is the most versatile method for analyzing the general case of nonlinear semi-discretized equations of motion. However, the approximate responses of such analyses generally do not converge properly, and might even display numerical instability. This is a very significant shortcoming especially in practical time integration. Herein, after illustrating that this phenomenon is viable even for very simple nonlinear dynamic models, sources of the shortcoming are discussed in detail. The conclusion is that in time integration of nonlinear dynamic mathematical models of physically stable structural systems, responses may converge improperly for three major reasons. These reasons are: (1) inadequate number of iterations before terminating nonlinearity solutions; (2) deficiencies in the formulation of some time integration methods; and (3) the inherent behaviour of the models of some special dynamic systems. In addition, limitations on computational facilities and improper consideration of these limitations may impair the numerical stability and convergence of the computed responses. The differences between static and dynamic analyses are also discussed from the viewpoint of the numerical errors induced by nonlinearity.

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On practical integration of semi-discretized nonlinear equations of motion. Part 1: Reasons for probable instability and improper convergence. / Soroushian, Aram; Wriggers, Peter; Farjoodi, Jamshid.
in: Journal of sound and vibration, Jahrgang 284, Nr. 3-5, 21.06.2005, S. 705-731.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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abstract = "Time integration is the most versatile method for analyzing the general case of nonlinear semi-discretized equations of motion. However, the approximate responses of such analyses generally do not converge properly, and might even display numerical instability. This is a very significant shortcoming especially in practical time integration. Herein, after illustrating that this phenomenon is viable even for very simple nonlinear dynamic models, sources of the shortcoming are discussed in detail. The conclusion is that in time integration of nonlinear dynamic mathematical models of physically stable structural systems, responses may converge improperly for three major reasons. These reasons are: (1) inadequate number of iterations before terminating nonlinearity solutions; (2) deficiencies in the formulation of some time integration methods; and (3) the inherent behaviour of the models of some special dynamic systems. In addition, limitations on computational facilities and improper consideration of these limitations may impair the numerical stability and convergence of the computed responses. The differences between static and dynamic analyses are also discussed from the viewpoint of the numerical errors induced by nonlinearity.",
author = "Aram Soroushian and Peter Wriggers and Jamshid Farjoodi",
note = "Funding information: The authors gratefully acknowledge the helpful discussions they had on different parts of this paper with Prof. Arthur R. Robinson, Dr. K. Ghayour, and Mr. K. Arzhangi. The first and third authors also express their sincere appreciation to the financial assistance of the Research Council of the University of Tehran for the research report in correspondence to this paper. In addition, the last but by no means the least thanks are given to Prof. A. Der Kiureghian and Prof. J. Retief who caused the need to such a study come into the view of the first author.",
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AU - Wriggers, Peter

AU - Farjoodi, Jamshid

N1 - Funding information: The authors gratefully acknowledge the helpful discussions they had on different parts of this paper with Prof. Arthur R. Robinson, Dr. K. Ghayour, and Mr. K. Arzhangi. The first and third authors also express their sincere appreciation to the financial assistance of the Research Council of the University of Tehran for the research report in correspondence to this paper. In addition, the last but by no means the least thanks are given to Prof. A. Der Kiureghian and Prof. J. Retief who caused the need to such a study come into the view of the first author.

PY - 2005/6/21

Y1 - 2005/6/21

N2 - Time integration is the most versatile method for analyzing the general case of nonlinear semi-discretized equations of motion. However, the approximate responses of such analyses generally do not converge properly, and might even display numerical instability. This is a very significant shortcoming especially in practical time integration. Herein, after illustrating that this phenomenon is viable even for very simple nonlinear dynamic models, sources of the shortcoming are discussed in detail. The conclusion is that in time integration of nonlinear dynamic mathematical models of physically stable structural systems, responses may converge improperly for three major reasons. These reasons are: (1) inadequate number of iterations before terminating nonlinearity solutions; (2) deficiencies in the formulation of some time integration methods; and (3) the inherent behaviour of the models of some special dynamic systems. In addition, limitations on computational facilities and improper consideration of these limitations may impair the numerical stability and convergence of the computed responses. The differences between static and dynamic analyses are also discussed from the viewpoint of the numerical errors induced by nonlinearity.

AB - Time integration is the most versatile method for analyzing the general case of nonlinear semi-discretized equations of motion. However, the approximate responses of such analyses generally do not converge properly, and might even display numerical instability. This is a very significant shortcoming especially in practical time integration. Herein, after illustrating that this phenomenon is viable even for very simple nonlinear dynamic models, sources of the shortcoming are discussed in detail. The conclusion is that in time integration of nonlinear dynamic mathematical models of physically stable structural systems, responses may converge improperly for three major reasons. These reasons are: (1) inadequate number of iterations before terminating nonlinearity solutions; (2) deficiencies in the formulation of some time integration methods; and (3) the inherent behaviour of the models of some special dynamic systems. In addition, limitations on computational facilities and improper consideration of these limitations may impair the numerical stability and convergence of the computed responses. The differences between static and dynamic analyses are also discussed from the viewpoint of the numerical errors induced by nonlinearity.

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