2017 Annual Stability Conference Presentation

Session S3 – Advances in Stability Bracing
Wednesday, March 22, 2017
3:15 pm

Experimental Study of Steel Tub Girders with Partial Top Lateral Bracing

Steel box girder systems, which consist of steel tub girders with a cast in-place concrete deck on top, are a popular alternative for straight and horizontally curved bridges due to their high torsional stiffness and aesthetic appearance. However, steel tub girders possess a relatively low torsional stiffness during transport, erection and construction because of the thin-walled open section. Additionally, during the casting of concrete, the top flanges of the tub girder are in compression in the positive moment region and they are susceptible to lateral torsional buckling (LTB). Usually, top flange lateral bracing, in the form of a horizontal truss, is fully installed along the steel tub girder to prevent flanges from buckling and to increase the torsional stiffness of the girder. However, the horizontal truss is mainly effective near the ends of the girders where the shear deformations are the largest.  The contribution of the top lateral bracing to control lateral torsional buckling is notably reduced at the mid-span region. This paper provides an overview of on an ongoing research study focused on improving the efficiency of steel tub girders by investigating the impact of the girder geometry and bracing details on the behavior of the girders.  The study includes large-scale experimental tests and parametric finite element analytical (FEA) studies.   This paper highlights the experimental tests.  The efficiency of the horizontal truss is assessed by conducting multiple elastic-buckling tests on a steel tub girder with different amounts of top lateral bracing along the girder. A tub girder is subjected to combined bending and torsion using eccentric loads applied by gravity load simulators.  The goal of the study is to improve the efficiency of steel tub girders by defining adequate amounts of bracing without undermining their structural performance.

Stalin Armijos Moya, Yang Wang, Todd A. Helwig, Michael D. Engelhardt, Patricia Clayton and Eric Williamson, University of Texas at Austin, Austin, TX