Fully probabilistic analysis of FRP-to-concrete bonded joints considering model uncertainty

Fully probabilistic analysis of FRP-to-concrete bonded joints considering model uncertainty This work presents a full reliability-based analysis framework for fiber-reinforced polymer (FRP)-to-concrete bonded joints considering model uncertainty. Eight frequently used bond strength models for FRP-to-concrete bonded joints were calibrated by defining a model factor. A total of 641 well-documented tests were considered. Four of the eight models had model factors that correlated with input design parameters and the systematic part of the model factor was removed by a regression equation f. By doing this type of characterization, all eight model factors could be comparatively uniform and described by lognormally distributed random variables. The merit of the uniform model uncertainties after calibration for the eight models was established by the reliability analysis. This study improves the predictability of concrete strengthened with fiber composites and provides useful suggestions on their model uncertainties in engineering practice. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Composite Structures Elsevier

Fully probabilistic analysis of FRP-to-concrete bonded joints considering model uncertainty

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0263-8223
eISSN
1879-1085
D.O.I.
10.1016/j.compstruct.2017.11.058
Publisher site
See Article on Publisher Site

Abstract

This work presents a full reliability-based analysis framework for fiber-reinforced polymer (FRP)-to-concrete bonded joints considering model uncertainty. Eight frequently used bond strength models for FRP-to-concrete bonded joints were calibrated by defining a model factor. A total of 641 well-documented tests were considered. Four of the eight models had model factors that correlated with input design parameters and the systematic part of the model factor was removed by a regression equation f. By doing this type of characterization, all eight model factors could be comparatively uniform and described by lognormally distributed random variables. The merit of the uniform model uncertainties after calibration for the eight models was established by the reliability analysis. This study improves the predictability of concrete strengthened with fiber composites and provides useful suggestions on their model uncertainties in engineering practice.

Journal

Composite StructuresElsevier

Published: Feb 1, 2018

References

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