Bridge model updating using distributed sensor data
Loading...
Authors
Bentz, Evan C.
Hoult, Neil A.
Date
2016-03-23
Type
journal article
Language
en
Keyword
Alternative Title
Abstract
One of the challenges of managing bridge infrastructure is developing numerical models that can be usedto accurately assess highly redundant bridge systems. One way to refine the model is to use sensor data to performmodel updating. However, conventional sensors provide limited data with which to update the model, given themany degrees of freedom associated with indeterminate structures, resulting in a large potential error. Distributedsensing technologies such as digital image correlation and fibre optic strain sensors have the potential to providemore extensive data sets for model updating. This paper presents a case study of a reinforced concrete bridge thatwas modelled numerically to predict the bridge performance. The bridge was then load tested, and distributedsensor data were acquired. Using the sensor data, the numerical model was updated and refined estimates of thebridge behaviour were obtained. The initial and final models produced estimates of bridge behaviour that differedby an order of magnitude, illustrating the importance of sensor data for some bridge assessments. Additionally, themodel indicated that the stiffness of the bridge had increased with time owing to an increase in the elastic modulusof the concrete and the development of compressive stresses.
Description
©ICE Publishing: All rights reserved. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher.
Citation
Bentz, E. C., & Hoult, N. A. (2017, March). Bridge model updating using distributed sensor data. In Proceedings of the Institution of Civil Engineers-Bridge Engineering (Vol. 170, No. 1, pp. 74-86). Thomas Telford Ltd.
Publisher
Emerald ICE Publishing