Abstract
Damage modeling techniques are essential tools for revealing the impact pattern of damage on structural responses. Currently, different damage level parameters are defined for different damage modeling techniques, but there is no established equivalence among them. This might plague researchers in their selection of damage modeling techniques for theoretical and numerical studies. To address this challenge, comparative studies of different damage modeling techniques for beam-like structures were conducted, and their impact on vehicle-bridge-interaction (VBI)-based structural health monitoring was analyzed. First, the theoretical basis of four damage modeling techniques, that is, element stiffness loss, element mass increase, cracked beam element, and crack spring element, were analyzed, and equivalent damage level relationships were established based on beam frequencies. Then, a finite element simulation of the VBI system consisting of a two-axle vehicle and a beam-like structure with damage was formulated and verified. Finally, the impacts of different damage modeling techniques with unified damage levels on the dynamic responses were studied, and the feasibilities of damage identification using vehicle and bridge responses under different damage modeling techniques were compared. The results indicated that the dynamic responses generated by different damage modeling techniques varied under the same damage level. The damage modeling technique using the crack spring element posed the most significant impact on the VBI responses, the cracked beam element and element stiffness loss techniques had the equivalent impact, but the element mass increase technique showed a negligible impact. Damage location and severity could be well detected by the cracked beam element and element stiffness loss techniques. However, the dynamic responses generated by the element mass increase technique could not be used to identify the damage. Vehicle responses were more useful than bridge responses for damage identification, demonstrating the advancement of indirect monitoring of bridge health conditions using an instrumented passing vehicle.
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