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• W3091290410 abstract "Damage localization/quantification through vibration-based Structural Health Monitoring (SHM) is commonly performed by inverse calibration of a numerical model. Nevertheless, the numerous simulations required in the associated optimization problem pose a daunting obstacle when applied to real-time SHM. Particularly critical are heritage buildings, whose complex geometries often require computationally intensive modellings. In this light, this paper presents a novel earthquake-induced damage identification approach for historic masonry structures. This relies upon the use of a computationally efficient meta-model suited for real-time system identification. The optimization problem is formulated accounting for discrepancies between numerical and experimental resonant frequencies and mode shapes. Damage localization/quantification is enabled by multivariate analyses of continuously identified model parameters. A real medieval tower is presented as a case study, and several damage scenarios are simulated and used for validation. The reported results pave the way for the development of next-generation long-term vibration-based SHM systems with real-time damage identification capabilities." @default.
• W3091290410 created "2020-10-08" @default.
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• W3091290410 date "2020-12-01" @default.
• W3091290410 modified "2023-10-18" @default.
• W3091290410 title "Metamodel-based pattern recognition approach for real-time identification of earthquake-induced damage in historic masonry structures" @default.
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• W3091290410 doi "https://doi.org/10.1016/j.autcon.2020.103389" @default.
• W3091290410 hasPublicationYear "2020" @default.
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