Maio 2014 vol. 1 num. 1 - 10th World Congress on Computational Mechanics
Full Article - Open Access.
A COMPUTATIONAL MODEL FOR STOCHASTIC WAVE PROPAGATION IN LONG STRUCTURES
Zhang, Ruichong ; Gargab, Lotfi ;
Full Article:
This paper introduces a computational model for stochastic wave propagation in long structures of civil and mechanical engineering systems, exemplified as towers and pipelines, and characterized with one-dimensional waveguide materials inter-connected with lumped mass. The model can be used for predictive wave response analysis as well as for system identification and damage diagnosis in structural health monitoring. In this study, wave response at one location of the structure is derived to an impulsive motion at another location in time and frequency domains, termed here as wave-based or generalized impulse and frequency response functions. Not only does this study show vibration features in wave responses with the hybrid model, typically explainable and usable with discrete or multi-degree-of-freedom modeling. The model based responses also capture wave scattering features traditionally comprehensible with continuous modeling. The latter plays a major role in effectively detecting structural damage crack, stiffness degradation, and/or material non-linearity. Two examples are presented with the use of the modeling. One is wave-based characterization of ten-story Millikan Library in Pasadena, California with the recordings of Yorba Linda earthquake of September 3, 2002. The other is analysis for influence of stochastic material/geometrical features in wave responses.
Full Article:
Palavras-chave: Wave-based approach, Seismic responses of buildings, System identification.,
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DOI: 10.5151/meceng-wccm2012-16767
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Como citar:
Zhang, Ruichong; Gargab, Lotfi; "A COMPUTATIONAL MODEL FOR STOCHASTIC WAVE PROPAGATION IN LONG STRUCTURES", p. 351-369 . In: In Proceedings of the 10th World Congress on Computational Mechanics [= Blucher Mechanical Engineering Proceedings, v. 1, n. 1].
São Paulo: Blucher,
2014.
ISSN 2358-0828,
DOI 10.5151/meceng-wccm2012-16767
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