Bibliographic Details
| Title: |
Soil--Bridge System Stiffness Identification through Field and Laboratory Measurements. |
| Authors: |
Sextos, Anastasios1,2 asextos@bristol.ac.uk, Faraonis, Periklis3 pfaraonis@civil.auth.gr, Zabel, Volkmar4 volkmar.zabel@uni-weimar.de, FrankWuttke5 fw@gpi.uni-kiel.de, Arndt, Tobias6 tobias.arndt@uni-weimar.de, Panetsos, Panagiotis7 ppane@egnatia.gr |
| Source: |
Journal of Bridge Engineering. Oct2016, Vol. 21 Issue 10, p1-13. 13p. |
| Subjects: |
Dynamic stiffness, Structural engineering, Soil science, Bridge design & construction, Building foundations |
| Abstract: |
Despite the major advances in finite-element (FE) modeling and system identification (SI) of extended infrastructures, soil compliance and damping at the soil--foundation interface are not often accurately accounted for due to the associated computational demand and the inherent uncertainty in defining the dynamic stiffness. This paper aims to scrutinize the effect of soil conditions in the SI process and to investigate the efficiency of advanced FE modeling in representing the superstructure--soil--foundation stiffness. For this purpose, measured, computed, and experimentally identified natural frequencies of a real bridge were used. Field measurements obtained during construction were reproduced both in the laboratory and by refined FE modeling. In addition, to understand the physical problem more thoroughly, three alternative soil conditions were examined: rock, stabilized soil, and Hostun sand. Discrepancies on the order of 3-13% were observed between the identified and the numerically predicted natural frequencies. These discrepancies highlight the importance of reliable estimation of soil properties and compliance with the SI framework for extended bridges under ambient and low-amplitude vibrations. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Bridge Engineering is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |