An Autonomous Bridge Load Rating Framework Using Digital Twin

Abstract

Load rating of bridges is used to understand the working status and carrying capacity of bridge structures and components and is necessary to the safety of transportation. The current manual load rating procedure is, however, time-consuming. An intelligent and automatic load rating approach can be beneficial to supplement or eventually perhaps replace the current manual procedures. The innovation of this paper lies in developing an autonomous load rating framework by leveraging Digital Twin (DT) techniques. Full-scale laboratory testing of a bridge slab was conducted to verify the efficiency of the proposed framework. The ultimate moment capacity of the slab was obtained by carrying out four-point bending test. The testing procedure was monitored in real-time with multiple strain gauges. A real-scale finite element model of the slab was developed and calibrated with the testing results. The proposed DT framework of the bridge slabs was developed by integrating the numerical modeling and the strain monitoring. The proposed DT framework is intended for field application, and field results will be discussed.