Peng Lou

Effect of Overweight Trucks on Bridge Deck Deterioration Based on Weigh-in-Motion Data

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.

Development of Live Load Model for Strength II Limit State in AASHTO LRFD Design Specifications

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.

Dynamic Modeling of Train and Bridge with Stepped-Beam Cross-Sections

Railway systems are critical in many regions and facilitate large volume of freight movement cost-effectively. In North America, the majority of railway bridges were built at the beginning of the twentieth century. With the recent increase of railcar weight limits from 1170 kN to 1272 kN, concerns are raised regarding the condition and dynamic behavior of these bridges. This study focuses on the dynamic response of stepped beam under moving trains. The train is composed of a certain number of railcars, and each railcar is consisted of oscillators with three masses representing the railcar body, bogie and wheel sets, respectively. The connects among components is simulated by spring and dashpot units. Meanwhile, finite element method with Euler-Bernoulli beam element is used to model the stepped beam with variational sections. The contact force between the wheel and rail is simulated by the Hertzian spring. The interaction of train-bridge system is assumed to be nonlinear and is solved by an iterative algorithm. At last the developed model is verified using the data from field testing.

Dynamic Modeling and Field Testing of Railroad Bridges

In this paper, results for a study to investigate the impact of increasing the weight of freight railcar from 1,170 kN (263 kips) to 1,272 kN (286 kips) on typical bridges that are part of the New Jersey rail network are presented. Based on the field inspection reports, a number of critical bridges on New Jersey’s rail lines were selected and load-rated based on the current American Railway Engineering and Maintenance-of-Way Association (AREMA) specifications. Two-Dimensional (2D) dynamic models and field instrumentation and testing were adopted for the more accurate assessment of these bridges and to develop a refined methodology for evaluating and load-rating railroad bridges. The field study included instrumentation and testing under moving freight and passenger railcars. The steel bridge is simulated as a Bernoulli-Euler beam and the moving train is modeled using rigid-body dynamics. The method of modal superposition is adopted to compute the dynamic effects of the train-bridge interaction system. The dynamic model was validated with results from the field tests. The impact factor for fatigue of the bridge under moving freight and passenger train were compared with AREMA Mean Impact Factor. Results show that the impact factor for bridge fatigue is increased by the free vibration component. Moreover, for passenger car, when the running speed is above 170 km/h, the impact factor for fatigue is slightly larger than the AREMA Mean Impact Factor.