This synthesis will be of interest to state department of transportation and consulting bridge, structural, and research engineers. The synthesis describes the current state of the practice for determining dynamic impact factors for bridges. Information for the synthesis was collected by surveying U.S. and Canadian transportation agencies and by conducting a literature search using domestic and foreign sources. This report of the Transportation Research Board documents relevant background and recent information with regard to vehicular dynamic load effects on bridges. It provides details on the basic concepts of bridge dynamics, including identification of the main variables affecting bridge dynamic response. In addition, current code provisions for accounting for vehicular dynamic load effects for new bridge design and load evaluation of existing bridges are reported, including a discussion on the background of the provisions. Finally, a discussion of observed field problems associated with vehicular dynamic load effects, as obtained from the survey, are included.

The Dynamic Impact Factor (DIF) is widely employed to account for the dynamic amplification effect of moving trains on railway bridges. An accurate DIF provides a safe yet economical basis for new railway bridges and improves the safety rating assessment for existing railway bridges. This thesis investigates the accuracy, reliability and the underlying influence factors for DIF relationships currently used for short span steel railway bridges. Full-scale field monitoring exercises are conducted to measure the dynamic responses of two railway bridges during various train passages. The monitoring results indicate that both railway bridges satisfy the live load deflection limits recommended for railway bridges subjected to low-speed trains. Three-dimensional Finite Element (FE) models are developed for the each of railway bridges. The models are verified against the monitoring results. The verification results show that the models accurately predict the actual dynamic response of the railway bridges. A series of sensitivity analysis is performed using the verified FE models. The analyses investigate the effects of variation in New Zealand train and bridge dynamic characteristics on the mid-span DIFs of the monitored railway bridges. The trains are simulated as moving constant forces. The analysis results show that the train speeds have the largest influence on the DIFs of the railway bridges. Numbers and axle distances of carriages have some effects on the DIFs which these effects depend on corresponding locomotive axle distances. Bridge damping ratios have some influences, and the train axle loads have no effect on the DIFs. Over 100 different train arrangements corresponding to combinations possible in New Zealand are simulated and applied to the each of the FE modes. The mid-span DIFs are evaluated numerically as the simulated train passes over the bridges with different speeds. It is found that the DIF formulas in New Zealand railway bridge guidelines overestimate the dynamic effects of moving trains on the railway bridges. This overestimation approaches 4.2 times the bridge evaluated DIFs. Data mining techniques are employed to generate predictive models which estimate the medians of the simulated DIFs. These predictive models provide users with a reliable prediction of the DIFs for designing or assessing the short span steel railway bridges subjected to train passages with speeds up to 150 km/h.

Long-haul passenger, commuter, and freight railroads are essential to maintaining a thriving economy and environmentally friendly, efficient and less congested transportation system for people and goods, especially in New England, with its many urban areas, industries, and major national defense activities. On Amtrak’s Northeast Corridor between Washington, D.C. and Boston, MA, the busiest passenger rail corridor in the United Sates, there are over 60 long span steel bridges that are more than 100 years old. This situation presents many structural problems, especially overstress in certain members, as well as fatigue. This research focused primarily on two areas. First, developing a finite element (FE) model that can reliably predict the impact, as derived from other bridge responses (displacement and strain), for trains at speeds higher than that currently allowed on these structures. And second, field research to accumulate data on bridge response from each of the train types at various speeds. The research used as test vehicles, two types of Amtrak train sets, Acela higher speed vehicles, and Amtrak conventional Regional train vehicles, as well as Metro-North Railroad’s M8 MU commuter cars. Specific to this research is the type of bridge structure. The model was based on an open deck, long span through truss. This type of bridge is typical of hundreds still in service around the country, and most appreciably over a hundred years old, especially in the Northeast. Field research was conducted on Devon Bridge, a 115-year-old bridge, opened in 1906, over the Housatonic River between Stratford and Milford, Connecticut, and owned by the Connecticut Department of Transportation. The model was developed using STAAD.Pro software. Using the known physical characteristics (axle loads and axle spacing) of the Amtrak and Metro-North vehicles, field tests verified high correlation between actual bridge responses, measured by displacements and strains at various speeds, and those predicted by the model. Thus, the model can be useful in predicting impact values, derived from displacements and strains, from similar types of vehicles on this and other open deck railroad bridges. Additional study and analysis were performed on bridge response under live load to better understand how the relative old age of the test structure, and its long history from use by steam engines and heavy freight trains, effect certain truss members’ response. Particular investigation was performed on the eyebars, which are used as counter diagonals and lower chord members in the truss. Results from this investigation were compared to tests performed several years earlier, and analysis is presented for why some differences appear. A thorough review was also performed contrasting railroad bridges design impact requirements used in countries around the world. The knowledge gained from this research can be applied to other railroad bridges of this type, carrying comparable conventional passenger cars and MU transit cars.