Identification of flutter derivatives by forced vibration tests

Glumac, Anina Šarkić; Höffer, Rüdiger; Brčić, Stanko

doi:10.14256/jce.1504.2015

Cited by 1 publication

(1 citation statement)

References 11 publications

(16 reference statements)

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“…However, beyond this wind speed, vertical frequency sharply increased and reached the value of torsional frequency as also reported in literature. This is typical behavior observed in case of coupled flutter (Bartoli and Righi, 2006;Glumac et al, 2017;Gao et al, 2020).…”

Section: Measured Responsessupporting

confidence: 63%

Signal complexity approach based investigation of flutter instability in sectional models of bridges in wind tunnel

Keerthana

Harikrishna

2023

Advances in Structural Engineering

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Signal complexity analysis based entropy measure has been used to propose a model-free approach towards assessment of flutter critical wind speed and identification of the type of flutter in wind tunnel testing of long span bridges. The approach is based only on the measured output responses from the structure, which accounts for appropriate effects that stem from the non-linearity of the structure and fluid structure interaction. The usefulness of the proposed approach has been demonstrated with dynamic sectional models of two deck cross-sections in wind tunnel. The gain in regularity of responses on approaching the flutter critical wind speed, demonstrated with time history of responses and recurrence quantification plots, has been quantified using sample entropy. Based on the sensitivity of the sample entropy values on the embedding dimension, it has been suggested to adopt embedding dimension in the range of 2 and 5, to obtain a swift estimate of the state of the dynamic system. The proposed approach has shown potential to provide valuable insight about the flutter instability and distinguish between different types of flutter without requiring prior knowledge about the system under consideration. The study offers a promising complementary methodology to the conventional model-based approaches for evaluating flutter critical wind speed.

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Section: Measured Responsessupporting

confidence: 63%