Nondestructive Assessment of Elastomeric Bridge Bearings Using 3D Digital Image Correlation

Soleimani, Saleh Ahmadi; Konstantinidis, Dimitrios; Balomenos, Georgios P.

doi:10.1061/(asce)st.1943-541x.0003200

Cited by 4 publications

(1 citation statement)

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“…Researchers have therefore proposed alternative monitoring schemes. Soleimani et al [ 9 ] proposed three−dimensional digital image correlation coupled with finite element analysis to identify internal defects in bearings, whereas Topkaya and Akbari [ 10 , 11 ] proposed non−destructive test methods to determine the shear modulus of steel reinforced elastomeric bearings. Attempts have also been made to develop “smart” elastomeric bearings, i.e., bearings equipped with internal sensing systems, capable of providing continuous information on bearing reactions and displacements.…”

Section: Introductionmentioning

confidence: 99%

Self-Sensing Rubber for Bridge Bearing Monitoring

Orfeo

Tubaldi

McAlorum

et al. 2023

Sensors

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Elastomeric bearings are widely used in bridges to support the superstructure, to transfer loads to substructures, and to accommodate movements induced by, for example, temperature changes. Bearing mechanical properties affect the bridge’s performance and its response to permanent and variable loadings (e.g., traffic). This paper describes the research carried out at Strathclyde towards the development of smart elastomeric bearings that can be used as a low−cost sensing technology for bridge and/or weigh−in−motion monitoring. An experimental campaign was performed, under laboratory conditions, on various natural rubber (NR) specimens enhanced with different conductive fillers. Each specimen was characterized under loading conditions that replicated in−situ bearings to determine their mechanical and piezoresistive properties. Relatively simple models can be used to describe the relationship between rubber bearing resistivity and deformation changes. Gauge factors (GFs) in the range between 2 and 11 are obtained, depending on the compound and the applied loading. Experiments were also carried out to show that the developed model can be used to predict the state of deformation of the bearings under random loadings of different amplitudes that are characteristic of the passage of traffic over a bridge.

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Section: Introductionmentioning

confidence: 99%