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The United States has over 600,000 bridges, nearly 40% of which are 50 years old or older. Additionally, over 46,000 bridge structures in the country were evaluated to be structurally deficient according to the National Bridge Inventory (NBI) 2019. The average age of America’s bridges keeps increasing and many of these bridges are approaching the end of their design life. Therefore, evaluating the existing condition and predicting the remaining service life of these bridges is of vital importance to agencies making the decisions to maintain, repair, or replace bridge structures based on their present and future expected conditions. Several models are available to predict the service life of new concrete structures. However, very few models are available to estimate the remaining service life of existing concrete structures. This paper presents a comparative study between two service life prediction models (Life-365 and NCHRP report 558). The service life prediction analysis was performed on bridge substructures (two abutments, namely North Abutment and South Abutment) subjected to corrosion-induced deterioration. Constructed in 1958, this bridge is located in Northern New Jersey and was 60 years old at the time this study was conducted. Review of the existing bridge documents, visual inspection, and concrete damage survey, field sampling and testing, and lab tests were performed to evaluate the existing condition of the structure and to obtain the parameters required for analysis. A good agreement between the analysis results of Life-365 and NCHRP report 558 models was obtained.

Traditionally, a time-varying mass system is viewed as the motion of moving bodies exiting or colliding with the system, such as rockets. A standing structure is not typically considered a time-varying mass system, but a silo during discharge of the infill is a subtle time-varying mass structure. Slender silos and silos with insufficiently stiffened supports are vulnerable to excessive vibration (silo quaking) and loud disruptive noises (silo honking) caused by the flow of the exiting masses. Using principles of mechanics and conservation of momentum, the equation of motion of such systems can be formulated to incorporate the discharge rate, material properties and the time-dependent characteristics of the system (mass, damping and stiffness). In this paper, the acceleration and mass flow of granular fill in a perspex tubing during discharge have been reproduced to simulate silo honking. By controlling the majority of influential factors, the replication of a small-scale silo design was possible with the repeatability of silo honking achieved in a controlled environment. A comparative study between discharge testing results of the sand fill with 0% (control), 5% and 10% moisture content shows that increasing the moisture content of the fill reduces the vibrational effect on the silo walls, and in turn reduces the magnitude of silo honking. Further, the effect of the sudden mass loss on a system of reinforced concrete columns depicting that of silo supports is investigated. The results show the exponential changes in the acceleration and velocity responses of the structure when subjected to a sudden mass loss. Finally, notes on how to consider the system of the forces in the silo structure based on the existing silo theory are provided.

This paper presents a preliminary study on the durability of a bridge column under typical marine environments consisting of atmospheric, splash, and submerged conditions. To predict the migration of chlorides across the column, a simulation is conducted using a mathematical method, called cellular automata. Because chloride concentrations and the corrosion current density at the surface level of reinforcing steel can lead to the deterioration of a column over 100 years, they are of particular interest. The highest chloride concentrations are observed under the splash exposure, followed by the submerged and atmospheric conditions.

This paper proposes that Unmanned Aerial System (UAS) technologies integrated with image visibility enhancement algorithms and machine learning are an efficient yet supplementary concrete bridge inspection tool. Two different image enhancement algorithms, i.e., denoise algorithm and image property adjustment, were considered in this study. To assess the adequacy of the proposed UAS technologies in the bridge inspections, the technologies were applied to identify and quantify defects on an existing concrete double-tee bridge located in the state of South Dakota using a Matrice 210 unit. During the inspections, Matrice 210 recorded videos to extract numerous UAS inspection images throughout the bridge. Machine learning was applied to categorize each of the UAS inspection images into certain defect types such as rust and spalling. The denoise algorithm was used to reduce the noise on the categorized defect images based on the pretrained denoising neural network, while the image property adjustment algorithm was employed to improve the visibility of the images by filtering the images’ brightness, contrast, and sharpness. Through these algorithms, defects on the filtered images initially presented with low visibility, were detected. Furthermore, quantification of the defects was able to be completed using pixel-based image analysis with the filtered images. From the UAS-assisted inspections, concrete spalling and rust on railings of the bridge were observed, detected, and quantified successfully. The quantification of spalling showed only a 6.00% difference compared against the inspection report data provided by the South Dakota Department of Transportation (SDDOT).

Major bridges are requiring extended service lives of 100 years or more. This requires the use of high performance concretes and often enhanced corrosion protection provided by improved corrosion resistance of the reinforcing bars by using alloying, coatings, and/or corrosion inhibitors. Producing the entire bridge deck out of high performance concrete can lead to excessive cracking due to autogenous and drying shrinkage. Though this can be reduced by using shrinkage reducing admixtures or lightweight fines, the cost to implement these techniques for a full deck is high. However, a high performance concrete overlay uses considerably less high performance concrete, and as such can reduce the overall cost of the bridge deck and potentially allow for use of a more user friendly, less costly base concrete. This paper models the service life of a bridge deck using a high performance overlay. A probabilistic approach is used and the effect of cracking is included.