Abstract

Load rating describes the processing of quantifying the safe live load carrying capacity of an existing bridge. For most bridges, this load rating is derived as an analytical solution based on the structural design details and operational condition state. However, for structures without plans or insufficient structural details available it is difficult to formulate an analytical solution, especially for concrete structures where internal reinforcement details are needed to determine section capacity. For structures within this category, the potential solutions involve destructive evaluation to characterize the materials and components, proof load testing, or engineering judgement-based characterization. In this paper, a nondestructive method for load rating of reinforced concrete (RC) slab bridges without structural plans is proposed. To determine a bridge’s load rating factor, the capacity as well as dead load and live load effects need to be determined. In the proposed approach, a series of finite element analyses were conducted to describe the modal properties of a large population of bridges with different geometric characteristics. Results and geometric inputs were then used to develop an artificial neural network model that predicts the flexural rigidity of a bridge based on the measured modal frequencies derived from vibration testing. Due to the uncertainty in internal geometry of concrete, nondestructive approaches are presented to obtain the cross-section dimensions of bridge as well as the elastic modulus and compressive strength of concrete. Next, the cross-sectional area of the internal reinforcing steel is estimated through a quasi-static load test coupled with an optimization approach. These structural and material properties are then used to determine load effects and ultimately the bridge’s capacity. As a validation of the proposed approach, a skewed RC slab bridge with structural plans was tested and analyzed as if plans were not available. The bridge was instrumented with accelerometers and strain gages to record its response under ambient vibration, impact excitation, and quasi-static live load testing. Results show that the proposed nondestructive approach can be used to satisfactorily determine the load rating factor of the test bridge and can ultimately be used for load rating of concrete slab bridges without structural information.

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