Lessons Learned from Data Fusion of Structural Health Monitoring (SHM), Digital Twin Simulation

Lessons Learned from Data Fusion of Structural Health Monitoring (SHM), Digital Twin Simulation, and Weigh-In-Motion (WIM) Sensors for Evaluation Concrete Bridges
Presented By: Chaekuk Na, Rutgers University
Structural Health Monitoring (SHM) systems were implemented on various bridges for assessing their structural integrity and predicting their future performance. While the SHM system would provide the status of the structure, finite element analysis (FEA) from digital twin simulation would be able to predict the future conditions and remaining service life. Data from the SHM sensors were used to calibrate the bridge’s digital twin simulation model to provide high accuracy. Moreover, weigh-in-motion (WIM) sensors and data collection system were installed near the bridge approach to collect truck weight spectra and develop site-specific live load models. The fusion of data from the SHM, FEA, and WIM systems helped the agency to establish maintenance and repair (M&R) plans until the next rehabilitation project. The SHM system consists of accelerometers, tiltmeters, and strain gauges with the latest generation of Wi-Fi to eliminate the hassle of cable installation. The accelerometers were initially set to collect data in short sampling bursts at periodic intervals so the structural response under the same traffic could be compared. During this monitoring phase, the appropriate thresholds were established for the long-term event-triggered data collection. The global behavior of the bridge could be assessed with the acceleration data correlated to the structural stiffness. The short-term strain data collection correlated with the truck's gross vehicle weight. The strain gauges were successfully used to calibrate the FE model. Various case studies on bridges with different geometry were considered. WIM piezoelectric sensors were installed in pavement near the bridge approach. Inspection reports for rebar corrosion, petrographic analysis, and concrete cores provided input to update the FE model's material properties and predict the structure's future conditions and remaining service life.