Journal ArticleDOI
Dynamic identification of a masonry façade from seismic response data based on an elementary Ordinary Least Squares approach
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TLDR
In this article, a low magnitude seismic response of a historical masonry structure, the Santa Maria di Collemaggio basilica, was acquired by a complex monitoring system, where ten FBA accelerometers, nine placed on the basilica facade and one on the ground level, recorded respectively the base accelerogram (Input) and the structural response (Output).About:
This article is published in Engineering Structures.The article was published on 2019-10-15. It has received 35 citations till now.read more
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Journal ArticleDOI
Homogenization of Ancient Masonry Buildings: A Case Study
Simona Di Nino,Daniele Zulli +1 more
TL;DR: In this article, a homogeneous structural model is proposed to evaluate local and global dynamic mechanisms of a vast and historical masonry building, with the assembly of othotropic plates and Timoshenko and pure shear beams as well.
Journal ArticleDOI
An improved time-frequency analysis method for structural instantaneous frequency identification based on generalized S-transform and synchroextracting transform
TL;DR: In this article , an improved synchroextracting generalized S-transform (ISEGST) is proposed to improve the accuracy of structural instantaneous frequency (IF) identification, and the performance of ISEGST in numerical signals has been significantly improved, especially in the presence of noise.
Journal ArticleDOI
Segmented modeling method of dam displacement based on BEAST time series decomposition
TL;DR: In this article , a principal component analysis is used to extract the comprehensive displacement of multiple measuring points; then, the comprehensive displacements are decomposed into seasonal and trend parts by using the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) method, and the change of its change law is quantitatively analyzed.
Journal ArticleDOI
Government–business relations, environmental information transparency, and Hu-line-related factors in China
Rui Yang,Yingwen Chen,Yiqun Liu,Yuchen Feng,Jianwan Ji,Christina W.Y. Wong,Xin Miao,Yanhong Tang +7 more
Journal ArticleDOI
The Timber-Framed (TF) Masonries in L’Aquila: The baraccato Aquilano
TL;DR: In this paper, the authors attempt to classify the traditional T-Framed structures found in a limited area of the city centre, providing simple descriptions of their geometrical and functional features.
References
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Book
Dynamics of Structures: Theory and Applications to Earthquake Engineering
TL;DR: In this paper, the authors present a single-degree-of-freedom (SDF) system, which is composed of a mass-spring-damper system and a non-viscous Damping Free Vibration (NFV) system.
Journal ArticleDOI
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
TL;DR: Two new N4SID algorithms to identify mixed deterministic-stochastic systems are derived and these new algorithms are compared with existing subspace algorithms in theory and in practice.
Journal ArticleDOI
Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima
Ole Sigmund,Joakim Petersson +1 more
TL;DR: The current knowledge about numerical instabilities such as checkerboards, mesh-dependence and local minima occurring in applications of the topology optimization method are summarized and the methods with which they can be avoided are listed.
Journal ArticleDOI
Modal identification of output-only systems using frequency domain decomposition
TL;DR: By introducing a decomposition of the spectral density function matrix, the response spectra can be separated into a set of single degree of freedom systems, each corresponding to an individual mode, and close modes can be identified with high accuracy even in the case of strong noise contamination of the signals.
Journal ArticleDOI
Reference-based stochastic subspace identification for output-only modal analysis
Bart Peeters,Guido De Roeck +1 more
TL;DR: In this paper, a novel approach of stochastic subspace identification is presented that incorporates the idea of the reference sensors already in the identification step: the row space of future outputs is projected into the rowspace of past reference outputs.