Ambient vibration modal identification, also known as Operational Modal Analysis, aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures.
However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on applying the Hilbert Transform, to obtain the analytical representation of the system response in terms of the correlation function. In particular, it is worth stressing that the analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. A 3DOF numerical example will be presented to show the accuracy of the proposed procedure, and comparisons with data from other methods assess the reliability of the approach. Finally, the identification method will be extended to the real case study of the Chiaramonte Palace, a historic building located in Palermo and known as “Steri”.
In this paper an innovative and simple Operational Modal Analysis (OMA) method for structural dynamic identification is proposed. It combines the recently introduced Time Domain–Analytical Signal Method (TD–ASM) with the Genetic Algorithm (GA). Specifically, TD–ASM is firstly employed to estimate a subspace of candidate modal parameters, and then the GA is used to identify the structural parameters minimizing the fitness value returned by an appropriately introduced objective function. Notably, this method can be used to estimate structural parameters even for high damping ratios, and it also allows one to identify the Power Spectral Density (PSD) of the structural excitation. The reliability of the proposed method is proved through several numerical applications on two different Multi Degree of Freedom (MDoF) systems, also considering comparisons with other OMA methods. The results obtained in terms of modal parameters identification, Frequency Response Functions (FRFs) matrix estimation, and structural response prediction show the reliability of the proposed procedure.
The Atlantic blue crab Callinectes sapidus Rathbun, 1896 is included among the worst invasive alien species in the Mediterranean Sea. Here, we report the finding of the species in two Sicilian rivers, the Irminio and the Imera Meridionale, where it was collected up to 6 km from the river mouths. Although several records of the species are already available from Italy, this is the first evidence of the occurrence of this invasive crab so far from the coastline in the whole country. In the light of the well-known impact of the Atlantic blue crab on the invaded water bodies, the monitoring of the species and appropriate mitigation strategies should be implemented in order to protect the threatened native biota of Sicilian inland waters.
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