<  Back to the Polytechnique Montréal portal

Improving fatigue evaluations of structures using in-service behavior measurement data

Romain Pasquier, James-A. Goulet, Claire Acevedo and Ian F. C. Smith

Article (2014)

[img]
Preview
Accepted Version
Terms of Use: All rights reserved.
Download (2MB)
Cite this document: Pasquier, R., Goulet, J.-A., Acevedo, C. & Smith, I. F. C. (2014). Improving fatigue evaluations of structures using in-service behavior measurement data. Journal of Bridge Engineering, 19(11), p. 1-10. doi:10.1061/(asce)be.1943-5592.0000619
Show abstract Hide abstract

Abstract

Conservative models and code practices are usually employed for fatigue-damage predictions of existing structures. Direct inservice behavior measurements are able to provide more accurate estimations of remaining-fatigue-life predictions. However, these estimations are often accurate only for measured locations and measured load conditions. Behavior models are necessary for exploiting information given by measurements and predicting the fatigue damage at all critical locations and for other load cases. Model-prediction accuracy can be improved using system identification techniques where the properties of structures are inferred using behavior measurements. Building upon recent developments in system identification where both model and measurement uncertainties are considered, this paper presents a new data-interpretation framework for reducing uncertainties related to prediction of fatigue life. An initial experimental investigation confirms that, compared with traditional engineering approaches, the methodology provides a safe and more realistic estimation of the fatigue reserve capacity. A second application on a full-scale bridge also confirms that using load-test data reduces the uncertainty related to remaining-fatigue-life predictions.

Uncontrolled Keywords

Remaining fatigue life; Model-based data interpretation; Population of models; Uncertainty; Conservatism

Open Access document in PolyPublie
Subjects: 1000 Génie civil > 1000 Génie civil
Department: Département des génies civil, géologique et des mines
Research Center: Non applicable
Funders: Swiss National Science Foundation
Grant number: 200020-144304
Date Deposited: 17 Jan 2018 12:30
Last Modified: 24 Oct 2018 16:12
PolyPublie URL: https://publications.polymtl.ca/2893/
Document issued by the official publisher
Journal Title: Journal of Bridge Engineering (vol. 19, no. 11)
Publisher: ASCE
Official URL: https://doi.org/10.1061/(asce)be.1943-5592.0000619

Statistics

Total downloads

Downloads per month in the last year

Origin of downloads

Dimensions

Repository Staff Only