Bridge inspection standards in the United States require routine visual inspections to be conducted on most bridges at a maximum interval of two years regardless of the bridge condition. Limitations of this uniform calendar-based approach have been reported in the literature. Accordingly, the objective of this study is to provide a new systematic approach for inspection planning that integrates information from bridge condition prediction models, inspection data, and expert opinion using Bayesian analysis to enhance inspection efficiency and maintenance activities. The uncertainty-based inspection framework proposed in this study can help bridge owners avoid unnecessary or delayed inspections and repair actions, determine the inspection method, and consider more than one deterioration process or bridge component during the inspection planning process. The inspection time and method are determined based on the uncertainty and risks associated with the bridge condition. As uncertainty in the bridge condition reaches a defined threshold, an inspection is scheduled utilizing nondestructive techniques to reduce the uncertainty level. The framework is demonstrated on a new and on an existing reinforced concrete bridge deck impacted by corrosion deterioration. The results show that the framework can reduce the number of inspections by 50% compared to conventional scheduling methods, and the uncertainty regarding the bridge maintenance time is reduced by 16%.
The limitations of the standard two-year interval for the visual inspection of bridges required by the U.S. National Bridge Inspection Standards have been well documented, and alternative approaches to bridge inspection planning have been presented in recent literature. This paper explores a different strategy for determining the interval between inspections and the type of inspection technique to use for bridges. The foundational premise of the proposed approach is that bridge inspections are conducted to increase knowledge about the bridge’s current condition, and therefore, are only required when uncertainty about the knowledge of the bridge condition is too high. An example case of a reinforced concrete bridge deck was used to demonstrate how this approach would work. The method utilized deterioration models for predicting corrosion and crack initiation time, considering the uncertainty in the models’ parameters. Bridge inspections were used to update the current condition information and model parameters through Bayesian updating. As this paper presents a new idea for inspection planning, not all of the data or models necessary to fully develop and validate the approach currently exist. Nonetheless, the method was applied to a simulated example which demonstrates how the timing and means of bridge inspection can be tailored to provide the required data about individual bridges needed for effective bridge management decision making.
Reinforced concrete bridges are a critical component within the transportation infrastructure. These bridges are facing continuous deterioration due to increasing traffic loads and aggressive environmental conditions [1]. Regular inspections and maintenance actions are required to keep these bridges capable of carrying out its intended function at a satisfactory level. The main challenge in making accurate maintenance and inspections decisions is due to funding constraints on bridge managers. A proactive approach to bridge management is likely to provide optimal economical and effective management decisions [2]. The quality of these decisions depends on successful prediction of civil infrastructure's future condition state. Many researches has proposed different types of deterioration models to predict the condition of concrete bridges at different stages during its life span [3,4] Stochastic models, have been used in predicting the deterioration process of reinforced concrete bridges. One of the main advantages of stochastic models is their ability to capture the uncertainty when predicting the condition of a reinforced concrete bridge at different time periods [5]. Chloride-induced corrosion of steel in reinforced concrete structures is one of the major causes of reinforced concrete deterioration over time. In the winter season deicing salts are spread on roads to keep them safe and to avoid traffic collision. However deicing salts are considered one of the main sources of chloride accumulation on the bridge deck. Chlorides from de-icing salts or marine breeze penetrate through the concrete cover affecting the protective oxide layer formed around the reinforcements [6]. As the chloride content reaches the threshold level at the rebar level, the protective film surrounding the rebar fails and corrosion initiates. Due to the This work is licensed under Creative Commons Attribution 4.0 License CTCSE.MS.ID.000634.
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