Technical Papers
Feb 16, 2018

Regression-Based Adjustment Factor to Better Estimate Shear Capacity for Load-Rating Simple Span PC Girders

Publication: Journal of Bridge Engineering
Volume 23, Issue 5

Abstract

In this study, an adjustment factor was developed to better estimate the shear capacity of simple span prestressed concrete (PC) girders, for intended use in load rating. The adjustment factor is expressed as a function of several critical girder parameters including concrete strength, prestress level, stirrup spacing, and girder height. The adjustment factor was determined from a regression analysis of over 200 shear capacity results. The database was obtained from a parametric analysis conducted with a finite-element model validated with experimental data. Three different code methods were considered for comparison. Generally, code results were found to be inconsistently conservative. Application of the adjustment factor to an established procedure produced improvement in the accuracy and consistency of shear capacity estimation over existing code methods for the range of girder parameters considered. In addition, potential effects on rating factors for inventory and operational levels were quantified.

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Acknowledgments

This research was partially funded by the MDOT through Grant 2010-0298-Z5. The authors would like to thank the editors and reviewers for their time and effort in reviewing the current manuscript.

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Go to Journal of Bridge Engineering
Journal of Bridge Engineering
Volume 23Issue 5May 2018

History

Received: Jun 7, 2017
Accepted: Oct 31, 2017
Published online: Feb 16, 2018
Published in print: May 1, 2018
Discussion open until: Jul 16, 2018

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Authors

Affiliations

Alaa I. Chehab, M.ASCE [email protected]
Postdoctoral Research Associate, Dept. of Civil and Environmental Engineering, Wayne State Univ., Detroit, MI 48202 (corresponding author). E-mail: [email protected]
Christopher D. Eamon, M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Wayne State Univ., Detroit, MI 48202. E-mail: [email protected]

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