Browsing by Author "Boscato, Giosuè"

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    Recursive partitioning and Gaussian process regression for the detection and localization of damages in pultruded glass fiber reinforced polymer material
    (Wiley, 2021-06-16) Boscato, Giosuè; Civera, Marco; Zanotti Fragonara, Luca
    In this paper, a methodology for the detection and localization of damages in composite pultruded members is proposed. This is particularly relevant to thin-walled pultruded members, which are typically characterized by orthotropic behavior, anisotropic along the fibers and isotropic in the cross section. Hence, a method to detect and localize damage, and the influence these might have on the performance of thin-walled Glass Fiber Reinforced Polymer (GFRP) members, is proposed and applied to both numerical and experimental data. Specifically, the numerical and experimental modal shapes of a narrow flange pultruded profile are analyzed. The reliability of the proposed semiparametric statistical method, which is based on Gaussian Processes Regression and Bayesian-based Recursive Partitioning, is analyzed on a narrow flange profile, artificially affected by sawed notches with incremental depth. The numerical investigation is carried out via finite element models (FEMs) of the cracked beam, where the dynamic parameters and the modal shapes are computed. In total, three different crack sizes are investigated, to compare the results with the experimental ones. Finally, the proposed approach is further extended and validated on numerically simulated frame structures.
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    Structural health monitoring through vibration-based approaches
    (Hindawi, 2019-02-17) Boscato, Giosuè; Fragonara, Luca Zanotti; Cecchi, Antonella; Reccia, Emanuele; Baraldi, Daniele
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    Treed gaussian process for manufacturing imperfection identification of pultruded GFRP thin-walled profile
    (Elsevier, 2020-08-28) Civera, Marco; Boscato, Giosuè; Fragonara, Luca Zanotti
    The process of manufacturing pultruded FRP (Fiber Reinforced Polymers) profiles involves unavoidable imperfections that affect their structural performances. This is is even more relevant for the stability of axially loaded slender elements, due to the importance of imperfections and notches to initiate the buckling phenomenon. Thus, they become a predominant factor for the design of lightweight FRP beam-like structures. A Bayesian approach is proposed to estimate the presence and location of manufacturing imperfections in pultruded GFRPs (Glass Fiber Reinforced Polymers) profiles. Specifically, the Treed Gaussian Process (TGP) procedure is applied. This approach combines regression Gaussian Processes (GP) and Bayesian-based Recursive Partitioning. The experimental and numerical modal shapes of wide flange pultruded profile were investigated. The experimental data were compared with the numerical results of several Finite Element Models (FEM) characterised by different crack sizes