Highway agencies are responsible for the optimal expenditure of taxpayer dollars allocated to highway infrastructure. Truck size and weight are regulated by federal legislation, and every state highway agency has its own legal load limits. In addition, state agencies issue permits for trucks with gross vehicle weights that are above legal load limits. However, the effect of overweight trucks on the service life of bridge structures, especially concrete decks, is not explicitly quantified. Detailed research on deterioration models for bridge decks was conducted. Condition ratings of bridge decks in New Jersey from the National Bridge Inventory were used to derive the deterioration of decks over time, and the expected service lives of decks on different highways were obtained. Weigh-in-motion data from stations in New Jersey were used to extract two data sets: “all trucks” and “legal trucks.” The “all trucks” data set was used to develop a deck deterioration model as a function of equivalent wheel load that could be used to estimate expected service life. Finally, bridge life-cycle cost analysis was conducted under two scenarios, one with and the other without overweight trucks, to quantify the economic impact of such trucks on bridge decks. The results indicate that overweight trucks caused more damage on New Jersey state highways than on Interstate highways because of a larger proportion of overweight trucks, heavy wheel loads from overweight trucks, and fewer axles per truck.
State agencies are responsible for making major decisions on allocating the available but limited funds for the maintenance and rehabilitation of bridges. Over the past two decades, the frequency of overweight trucks has kept increasing. Although the AASHTO load and resistance factor design specifications mandate a design life of 75 years, the actual service life will be affected by site-specific loading; local environmental attack, including the application of deicing salts; each agency’s bridge preservation strategy; the funding situation; and routine maintenance. Nowadays, agencies issue more permits for trucks with gross vehicle weights that exceed legal load limits. There is a need, therefore, to quantify the impact of overweight trucks on the service life of bridge girders. This study presents a procedure for investigating the impact of truck loads on bridges in New Jersey through the utilization of bridge inspection reports, truck weigh-in-motion data, and the National Bridge Inventory database. Actual bridge deterioration modes in New Jersey were identified from the bridges’ respective inspection reports, and the expected bridge service life was successfully correlated with truck loading from weigh-in-motion data. The deterioration mode of prestressed concrete (PC) girders was found to be the corrosion of prestressing tendons near the beam ends induced by cracking and spalling of enclosing concrete. The maintenance of deck joints is a major factor that affects the deterioration of PC girders. Additionally, a strong correlation was found between the expected service life of PC girders and overweight truck counts.
The AASHTO LRFD Bridge Design Specifications defines Strength II limit state for agencies to consider the load combination by owner-specified special design vehicles, evaluation permit vehicles, or both. The configuration and characteristics of permit vehicles vary from state to state. In addition, the code calibration process performed in 1994 for the development of the live load factors was applied only to the Strength I limit state. In New Jersey, the design permit vehicle was not developed based on actual permit records or weigh-in-motion (WIM) data. Recently, with the development of permit-issuing management and WIM technology, there is a need to evaluate the effectiveness of design permit vehicles. This study aims to develop a live load model for the assessment of Strength II limit state for New Jersey Department of Transportation (NJDOT). Five years of permit vehicle records are provided by NJDOT for the development of the live load model. The distribution of Gross Vehicle Weight is best described as the Generalized Extreme Value distribution. Load effects are simulated for different span lengths. The mean and standard deviation (SD) of the 75-year maximum loads are predicted using different extrapolation approaches. The results show that NJDOT Design Permit Vehicle provides stable mean and SD of bias ratios at 75-year level. In comparison with the current AASHTO live load factor of 1.35, the averages of the bias ratios at the 75-year level are found to be 1.31, 1.23, and 1.16 for the positive moment, shear, and negative moment, respectively.
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