Automatic Flexibility Identification and Rapid Load-Carrying Capacity Evaluation of Highway Bridges with Impact Testing Data

Bridges are crucial components of transportation networks; however, their structural performance deteriorates over time due to increasing traffic loads, material deterioration, and natural disasters. Rapid assessment of the load-carrying capacity of highway bridges is important for maintenance planning and rescue route management after natural disasters. Conventional load-test-based performance evaluation methods are labor-intensive, expensive, and potentially hazardous. To overcome these challenges, this paper proposes a rapid load-carrying capacity evaluation method for highway bridges using impact testing data and virtual load testing. The contributions of this study include (1) the development of an automated bridge flexibility identification method that employs impact testing data and a multi-scale peak extraction algorithm; and (2) the development of a multi-point deflection prediction and load-carrying capacity assessment method using identified modal flexibility and virtual load testing. Validation through experimental validation of a simply supported T-shaped beam bridge and field testing on a three-span continuous concrete box-girder bridge confirms the effectiveness and robustness of the developed method. This approach significantly simplifies the load-carrying capacity assessment process, offering a practical solution for the rapid evaluation of numerous highway bridges.