Reinforcing steel fracture identification for a high-performance bridge system. (June 2019)

• Record Type: Journal Article
• Authors: Mantawy, Islam M.; Thonstad, Travis; Sanders, David H.; Stanton, John F.; Eberhard, Marc O.
• Is Part Of: Structures. Volume 19(2019)
• Page Start: 58
• Page End: 67
• Publication Date: 2019-06
• Subjects: Bridges -- Shaking table -- Reinforcing steel -- Rocking columns -- Precast concrete -- Seismic -- Low-cycle fatigue -- Bar fracture; Structural engineering -- Periodicals; 624.1
• DOI: 10.1016/j.istruc.2018.11.017
• Languages: English
• ISSNs: 2352-0124

Abstract

Abstract: In high-performance bridge systems that inhibit concrete spalling in the columns, bar buckling is suppressed, and bar fracture is delayed. However, bar fracture can still occur due to low-cycle, axial fatigue. If bar fractures cannot be identified visually, a method is needed to identify these fractures indirectly to ensure that the bridge can remain in service. This paper describes an investigation of reinforcing bar fractures that occurred during shaking table tests of a two-span bridge with armored rocking columns. During the test, it was difficult to identify the timing and location of bar fractures, because the lack of spalling made visual inspection impossible and gauges monitoring strains in the reinforcement reached their deformation capacity long before the bars fractured. The number and timing of bar fractures were estimated: (1) by the visual identification of fractures during the demolition of the specimen; (2) from the audible fractures that were recorded by video cameras during each test; and (3) using estimates of the strain histories of the bars, computed from rigid-body mechanics of the columns. Two types of fracture strain criteria were considered to identify bar fractures from the estimated strain data. A strain threshold criterion tended to underestimate the number of bars that fractured in later tests. A low-cycle fatigue criterion, which reflected the full strain histories for the longitudinal bars, correlated much better with bar fractures identified from the audio recordings and visual observations. The proposed methods, using existing models for low-cycle fatigue, can be used to evaluate and improve the performance of similar systems for which axial fatigue fracture is a concern during large earthquake motions.