Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods

P. S. Skjærbæk; Poul Henning Kirkegaard; G. N. Fouskitakis; S. D. Fassois

Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods

P. S. Skjærbæk, Poul Henning Kirkegaard, G. N. Fouskitakis, S. D. Fassois

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

2 Citations (Scopus)

Abstract

This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modeling and simulation of this behaviour is of crucial importance in the design of flexible structures and other applications. This paper examines three approaches for the modelling and simulation of non-stationary nearsource ground accelerograms: The first one makes use of
ARMA models combined with frequency and variance "stabilization". The second is based upon inherently nonstationary Time-dependent ARMA (TARMA) models, the parameters and variance of which are allowed to be explicit functions of time. The third approach is based on Neural Networks. The three approaches are used for the modelling and simulation of an accelerogram characterized by an epicentral distance of 16 km and measured during the 1979 Imperial Valley earthquake in California (U .S .A.). The results of the study indicate that while all three approaches can successfully predict near-source ground motions, the Neural Network based
one gives somewhat poorer simulation results.

Original language	English
Title of host publication	Proceedings of the 15th International Modal Analysis Conference : February 3-6, 1997, Orlando, Florida
Number of pages	7
Volume	2
Place of Publication	Bethel, Connecticut
Publisher	Society for Experimental Mechanics
Publication date	1997
Pages	1904-1910
ISBN (Print)	0-912053-53-4
Publication status	Published - 1997
Event	The International Modal Analysis Conference - Orlando, Florida, United States Duration: 3 Feb 1997 → 6 Feb 1997 Conference number: 15

Conference

Conference	The International Modal Analysis Conference
Number	15
Country/Territory	United States
City	Orlando, Florida
Period	03/02/1997 → 06/02/1997

Series	IMAC
Volume	2
ISSN	1046-6770

Keywords

Earthquakes
New-Source Areas
Non-Stationary Signals
Stochastic Signals
ARMA
TARMA

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Skjærbæk, P. S. ; Kirkegaard, Poul Henning ; Fouskitakis, G. N. et al. / Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion : ARMA and neural network methods. Proceedings of the 15th International Modal Analysis Conference: February 3-6, 1997, Orlando, Florida. Vol. 2 Bethel, Connecticut : Society for Experimental Mechanics, 1997. pp. 1904-1910 (IMAC, Vol. 2).

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title = "Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods",

abstract = "This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modeling and simulation of this behaviour is of crucial importance in the design of flexible structures and other applications. This paper examines three approaches for the modelling and simulation of non-stationary nearsource ground accelerograms: The first one makes use ofARMA models combined with frequency and variance {"}stabilization{"}. The second is based upon inherently nonstationary Time-dependent ARMA (TARMA) models, the parameters and variance of which are allowed to be explicit functions of time. The third approach is based on Neural Networks. The three approaches are used for the modelling and simulation of an accelerogram characterized by an epicentral distance of 16 km and measured during the 1979 Imperial Valley earthquake in California (U .S .A.). The results of the study indicate that while all three approaches can successfully predict near-source ground motions, the Neural Network basedone gives somewhat poorer simulation results.",

keywords = "Earthquakes, New-Source Areas, Non-Stationary Signals, Stochastic Signals, ARMA, Tarma, Earthquakes, New-Source Areas, Non-Stationary Signals, Stochastic Signals, ARMA, TARMA",

author = "Skj{\ae}rb{\ae}k, {P. S.} and Kirkegaard, {Poul Henning} and Fouskitakis, {G. N.} and Fassois, {S. D.}",

note = "Accepted for presentation at the 15th Int. Conference on Modal Analysis, Orlando, Florida, February 3-6, 1997 PDF for print: 16; The International Modal Analysis Conference ; Conference date: 03-02-1997 Through 06-02-1997",

year = "1997",

language = "English",

isbn = "0-912053-53-4",

volume = "2",

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Skjærbæk, PS, Kirkegaard, PH, Fouskitakis, GN & Fassois, SD 1997, Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods. in Proceedings of the 15th International Modal Analysis Conference: February 3-6, 1997, Orlando, Florida. vol. 2, Society for Experimental Mechanics, Bethel, Connecticut, IMAC, vol. 2, pp. 1904-1910, The International Modal Analysis Conference, Orlando, Florida, United States, 03/02/1997.

Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods. / Skjærbæk, P. S.; Kirkegaard, Poul Henning; Fouskitakis, G. N. et al.
Proceedings of the 15th International Modal Analysis Conference: February 3-6, 1997, Orlando, Florida. Vol. 2 Bethel, Connecticut: Society for Experimental Mechanics, 1997. p. 1904-1910 (IMAC, Vol. 2).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion

T2 - The International Modal Analysis Conference

AU - Skjærbæk, P. S.

AU - Kirkegaard, Poul Henning

AU - Fouskitakis, G. N.

AU - Fassois, S. D.

N1 - Conference code: 15

PY - 1997

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N2 - This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modeling and simulation of this behaviour is of crucial importance in the design of flexible structures and other applications. This paper examines three approaches for the modelling and simulation of non-stationary nearsource ground accelerograms: The first one makes use ofARMA models combined with frequency and variance "stabilization". The second is based upon inherently nonstationary Time-dependent ARMA (TARMA) models, the parameters and variance of which are allowed to be explicit functions of time. The third approach is based on Neural Networks. The three approaches are used for the modelling and simulation of an accelerogram characterized by an epicentral distance of 16 km and measured during the 1979 Imperial Valley earthquake in California (U .S .A.). The results of the study indicate that while all three approaches can successfully predict near-source ground motions, the Neural Network basedone gives somewhat poorer simulation results.

AB - This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modeling and simulation of this behaviour is of crucial importance in the design of flexible structures and other applications. This paper examines three approaches for the modelling and simulation of non-stationary nearsource ground accelerograms: The first one makes use ofARMA models combined with frequency and variance "stabilization". The second is based upon inherently nonstationary Time-dependent ARMA (TARMA) models, the parameters and variance of which are allowed to be explicit functions of time. The third approach is based on Neural Networks. The three approaches are used for the modelling and simulation of an accelerogram characterized by an epicentral distance of 16 km and measured during the 1979 Imperial Valley earthquake in California (U .S .A.). The results of the study indicate that while all three approaches can successfully predict near-source ground motions, the Neural Network basedone gives somewhat poorer simulation results.

KW - Earthquakes

KW - New-Source Areas

KW - Non-Stationary Signals

KW - Stochastic Signals

KW - ARMA

KW - Tarma

KW - Earthquakes

KW - New-Source Areas

KW - Non-Stationary Signals

KW - Stochastic Signals

KW - ARMA

KW - TARMA

M3 - Article in proceeding

SN - 0-912053-53-4

VL - 2

T3 - IMAC

SP - 1904

EP - 1910

BT - Proceedings of the 15th International Modal Analysis Conference

PB - Society for Experimental Mechanics

CY - Bethel, Connecticut

Y2 - 3 February 1997 through 6 February 1997

ER -

Skjærbæk PS, Kirkegaard PH, Fouskitakis GN, Fassois SD. Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods. In Proceedings of the 15th International Modal Analysis Conference: February 3-6, 1997, Orlando, Florida. Vol. 2. Bethel, Connecticut: Society for Experimental Mechanics. 1997. p. 1904-1910. (IMAC, Vol. 2).

Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion: ARMA and neural network methods

Abstract

Conference

Keywords

AUB Link

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