Technology for condition and performance evaluation of highway bridges

• Published in: Journal of civil structural health monitoring 2020-09, Vol.10 (4), p.573-594
• Main Authors: Ye, Shi, Lai, Xiangang, Bartoli, Ivan, Aktan, A. Emin
• Format: Article
• Language: English
• Subjects: Asset management; Bridge loads; Civil Engineering; Computer simulation; Control; Destructive testing; Dynamical Systems; Engineering; Finite element method; Highway bridges; Impact damage; Inspection; Measurement Science and Instrumentation; Monitoring; Nondestructive testing; Original Paper; Parameter identification; Performance evaluation; Proof testing; Root cause analysis; Systems analysis; Vibration
• ISSN: 2190-5452; 2190-5479
• DOI: 10.1007/s13349-020-00403-6

Today, bridge owners must consider increasing traffic demands (in both volume and weight) and also face concerns related to sustainability, resilience and liveability which were virtually unknown in the 1950s. Furthermore, legislators demand data-driven asset management decisions based on objective, quantitative and reliable bridge condition and performance evaluation. To explore the current state-of-the-art in objective performance and condition evaluation of constructed systems by leveraging technology, a 30-year old freeway bridge in New Jersey, exhibiting multiple complex performance deficiencies, was transformed into a field laboratory. To identify the root causes of performance concerns, Visual Inspection, Operational Monitoring, Forced Excitation Testing, Controlled Load Testing, Non-destructive Probes, Long-term Monitoring, Finite Element Modelling and Parameter Identification were conducted within a Structural Identification framework. The results showed that root causes of some performance deficiencies of the test bridge were identified definitively only through the application of field measurements and analyses integrated by following a scientific approach—i.e. Structural Identification. Controlled Proof-Load Testing was especially useful in demonstrating the location and impacts of damage and the remaining capacity although such an approach can only be considered for the most critical cases due to its high cost and disruption to operations. Operational monitoring was shown as a sufficient and much cheaper alternative for structural identification permitting the development of a 3D digital twin of the bridge, which proved critical in identifying the root causes of its deficiencies and formulating meaningful interventions. Without an a-priori model used for designing the experiments as well as a model (i.e. a digital twin) calibrated by parameter identification and used for simulations, it was not possible to offer options for corrective measures confidently. The study demonstrated the challenges in relying only on visual inspection when a multitude of interdependent mechanisms lead to damage and deterioration, and the information value of different experimental methods such as vibration testing, proof load testing, wide-area NDE scans and multi-year SHM in being able to understand the root causes of various damages.