Modeling Error Uncertainty Characterization for Reliability-Based Fatigue Assessment in Sign Support Structures
Publication: Journal of Structural Engineering
Volume 142, Issue 7
Abstract
Sign and luminaire support structures are prevalent throughout the transportation infrastructure network. Collapse and inspection of these signs pose hazards to the motoring public and the inspection personnel charged with their maintenance. There is a need to develop inspection protocols and understand variability in their performance to ensure public safety and to rationally disperse limited fiscal and personnel resources. This paper outlines a methodology that enables simulated and easured time histories of wind speed and resulting bending stress to be used in establishing parameters defining lognormal statistical models for modeling error that can be included in reliability-based assessment of structures subject to the tendency toward fatigue-induced crack initiation. Rainflow cycle counting is used to generate expected stress ranges from simulated and measured bending stress signals. The ratio of simulated expected stress range to measured expected stress range is defined as the modeling error bias factor. Statistical analysis of this factor at various magnitudes of wind speed is then used to formulate lognormal modeling error parameters suitable for implementation into a reliability-based assessment of fatigue-induced crack initiation risk for sign support structures.
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Acknowledgments
This research was funded through the Wisconsin Highway Research Program by the Wisconsin DOT and the Federal Highway Administration under Projects 0092-08-14 and 0092-09-07. The contents of this report reflect the views of the authors who are responsible for the facts and accuracy of the data presented in this paper. The contents do not necessarily reflect the official views of the Wisconsin DOT or the Federal Highway Administration at the time of publication.
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© 2016 American Society of Civil Engineers.
History
Received: Aug 29, 2013
Accepted: Jan 12, 2015
Published online: Mar 18, 2016
Published in print: Jul 1, 2016
Discussion open until: Aug 18, 2016
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