System Identification of Fei-Tsui Arch Dam From Forced Vibration and Seismic Response Data

Loh, Chin‐Hsiung; Wu, Tsu-Chiu

doi:10.1080/13632460009350381

Cited by 36 publications

(16 citation statements)

References 9 publications

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“…Ground motions recorded at arch dams exhibit spatial variation (or non-uniformity) along the dam-rock interface. Such data include records obtained at three dams: (1) Pacoima Dam (CA, U.S.A.) during the magnitude 4.3 earthquake on January 13,2001, and the magnitude 6.9 Northridge earthquake on January 17, 1994 [5]; (2) Mauvoisin Dam (Switzerland) during the magnitude 4.6 Valpelline earthquake on March 31, 1996 [6]; and (3) Fei-Tsui Dam (Taiwan) during the magnitude 7.3 Chi-Chi earthquake on September 21, 1999 [7], and the magnitude 6.8 Hualien offshore earthquake on March 31, 2002.…”

Section: Introductionmentioning

confidence: 99%

Linear analysis of concrete arch dams including dam–water–foundation rock interaction considering spatially varying ground motions

Wang

Chopra

2009

Earthq Engng Struct Dyn

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SUMMARYThe available substructure method and computer program for earthquake response analysis of arch dams, including the effects of dam-water-foundation rock interaction and recognizing the semi-unbounded size of the foundation rock and fluid domains, are extended to consider spatial variations in ground motions around the canyon. The response of Mauvoisin Dam in Switzerland to spatially varying ground motion recorded during a small earthquake is analyzed to illustrate the results from this analysis procedure.

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Section: Introductionmentioning

confidence: 99%

Linear analysis of concrete arch dams including dam–water–foundation rock interaction considering spatially varying ground motions

Wang

Chopra

2009

Earthq Engng Struct Dyn

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“…accelerometers [Loh and Wu 2000]; (d) statical overall inverse analyses under loading due to ad hoc changes of water level in the reservoir, with measurements of consequent displacements by means of pendulums, collimators and/or interferometric radar [Fedele et al 2006]; (e) same as (d), but with loading provided by seasonal, in-service variation of reservoir level (such alternative is much more economical than (d), however it requires more complex inverse analyses taking into account thermal effects as well [Ardito et al 2008]). Diagnostic procedures (c), (d) and (e) lead to the assessment of Young modulus only.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of concrete dams by flat-jack tests and inverse analyses based on proper orthogonal decomposition

Garbowski

Maier

Novati

2011

J. Mech. Mater. Struct.

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Dedicated to the memory of Marie-Louise Steele and to Charles Steele.Flat-jack tests have been employed for decades for the assessment of stresses and Young moduli in possibly deteriorated concrete dams and masonry structures. We propose a procedure for such tests that includes several innovations: identification of Young moduli and shear modulus in the presence of orthotropy, of pre-existing normal and shear stresses, and of tensile and compressive strength and fracture energy; use of full-field displacement measurements by digital image correlation (instead of extensometers); computer simulations performed once-and-for-all and productive of results which are subsequently processed out by proper orthogonal decomposition and its truncation; and identification of parameters in situ, soon after the tests, by portable computer with software able to perform inverse analyses by mathematical tools newly introduced into this context. The proposed procedure is validated by means of pseudoexperimental numerical exercises, by employing comparatively, as central computational tools, artificial neural networks and a trust region algorithm implying only first-order derivatives (with respect to the sought parameters) of the discrepancy function to minimize.

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“…As mentioned previously, earthquake records are non-stationary signals and have relatively short duration; therefore, parametric time-domain methods such as time series models are often used. The autoregressive model with exogenous input (ARX) method is adopted herein because of its good performance in such situations, as reported in the literature [28][29][30]. Consider an LTI system with input x(t) and output y(t), the input-output relationship can be described in the following linear difference equation (Ljung, 1999):…”

Section: Arx-era Methods For System Identificationmentioning

confidence: 99%

Parametric time‐domain identification of multiple‐input systems using decoupled output signals

Ruiz-Sandoval

Spencer

et al. 2013

Earthq Engng Struct Dyn

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SUMMARYCivil engineering structures are often subjected to multidirectional actions such as earthquake ground motion, which lead to complex structural responses. The contributions from the latter multidirectional actions to the response are highly coupled, leading to a MIMO system identification problem. Compared with single‐input, multiple‐output (SIMO) system identification, MIMO problems are more computationally complex and error prone. In this paper, a new system identification strategy is proposed for civil engineering structures with multiple inputs that induce strong coupling in the response. The proposed solution comprises converting the MIMO problem into separate SIMO problems, decoupling the outputs by extracting the contribution from the respective input signals to the outputs. To this end, a QR factorization‐based decoupling method is employed, and its performance is examined. Three factors, which affect the accuracy of the decoupling result, including memory length, input correlation, and system damping, are investigated. Additionally, a system identification method that combines the autoregressive model with exogenous input (ARX) and the Eigensystem Realization Algorithm (ERA) is proposed. The associated extended modal amplitude coherence and modal phase collinearity are used to delineate the structural and noise modes in the fitted ARX model. The efficacy of the ARX‐ERA method is then demonstrated through identification of the modal properties of a highway overcrossing bridge. Copyright © 2013 John Wiley & Sons, Ltd.

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System Identification of Fei-Tsui Arch Dam From Forced Vibration and Seismic Response Data

Cited by 36 publications

References 9 publications

Linear analysis of concrete arch dams including dam–water–foundation rock interaction considering spatially varying ground motions

Linear analysis of concrete arch dams including dam–water–foundation rock interaction considering spatially varying ground motions

Diagnosis of concrete dams by flat-jack tests and inverse analyses based on proper orthogonal decomposition

Parametric time‐domain identification of multiple‐input systems using decoupled output signals

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