Multiple Tests for Dynamic Identification of a Reinforced Concrete Multi-Span Arch Bridge
Author(s): |
Vincenzo Gattulli
Francesco Potenza Giulio Piccirillo |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 7 June 2022, n. 6, v. 12 |
Page(s): | 833 |
DOI: | 10.3390/buildings12060833 |
Abstract: |
This paper presents the results of an experimental dynamic campaign carried out on a reinforced concrete multi-span arch bridge. Five expeditious ambient vibration tests were conducted separately on five spans (one test in each span) of the bridge using only six piezoelectric uniaxial accelerometers. Modal parameters were identified through the well-known Enhanced Frequency Domain Decomposition (EFDD) procedure developed using Matlab R2021b software. At the same time, a finite element model was accurately implemented through a commercial software (Midas Civil) to evaluate the main modal features. A manual model update was successively pursued varying the elastic modulus of the reinforced concrete to make the identified and numerical modes as close as possible. A complete and suitable instrumentation to perform global experimental dynamic tests is not always available. Recursive/Multiple tests have different advantages: handy, easily executable, and could provide a more robust identification thanks to a statical characterization. The paper aims to highlight the peculiarities of recursive/multiple dynamic tests on multi-span arch bridges. The procedure also provides useful suggestions for designing a permanent and continuous vibration-based monitoring system. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
8.67 MB
- About this
data sheet - Reference-ID
10679405 - Published on:
17/06/2022 - Last updated on:
10/11/2022