Use of Refined Analysis Methods for Improved Estimation of Live Load Demands in Load Rating of Girder and Slab Bridges
Ndong, Abdou, Civil Engineering - School of Engineering and Applied Science, University of Virginia
Ozbulut, Osman, EN-Engr Sys & Environment, University of Virginia
Bridge load rating assesses the safe live load carrying capacity of an existing or newly designed bridge structure. In addition to load rating with previously defined standard legal-load rating vehicles, the Federal Highway Administration has required states to rate all the bridges with specialized hauling vehicles (SHVs) and emergency vehicles (EVs) by the end of 2022. SHVs refers to single unit trucks with closely spaced multiple axles, typically ranging from four to seven. They meet the axle and gross weight limits defined by Federal Formula B, but they have axle configurations that are different than those of standard legal vehicles. Emergency vehicles are designed for use under emergency conditions such as fires or other hazardous conditions. They can have considerably higher axle weight and gross weight than standard legal vehicles. It is recognized that the load effects (bending moment and shear) produced by SHVs and EVs on certain bridge types and spans might be greater than those caused by the previous legal loads. Therefore, a number of bridges within VDOT’s inventory may require posting when they are rated with these specialized vehicles.
The goal of this study is to assess the likelihood of an increase in load rating factor through refined analysis methods for the bridge classes potentially vulnerable to load ratings under consideration of the new federal regulations. Typically, live load effects on bridges are estimated using live load distribution factor equations in load rating of bridges. Refined methods of analysis can more accurately describe the distribution of load sharing with a bridge and possibly improve the overall load ratings. This study focused on the evaluation of live load distribution factors for girder bridges and live load resisting effective bridge widths for slab bridges through refined analysis. Considering the population of bridges affected by the SHV ratings and route importance, three bridge classes (simple span steel girder bridges, reinforce concrete T-beam bridges, and concrete slab bridges) were selected for the refined analysis. Girder bridges were modeled using the plate with an eccentric beam analysis approach, while plate elements were used to model slab bridges using a structural analysis software package. The selected modeling approaches were validated through the simulation of the bridge structures with available field-testing results from the literature. A total of 71 in-service bridges belonging to the three selected bridge classes were then modeled and analyzed to compute the load distribution factors for girder bridges or effective widths for slab bridges, and the results were compared with those obtained from the code-specified equations. Using the data obtained from these numerical simulations, a series of multi-parameter linear regression models were developed to predict the percent change in distribution factor and effective width, respectively for girder and slab bridges with different geometrical characteristics. For girder bridges, the results indicate that moment distribution factors obtained from refined analysis will likely improve rating factors for SHVs, while the shear distribution factors will likely be larger. For the slab bridges, refined analysis tends to result in a higher effective slab width when compared to the AASHTO LRFD approach. The developed regression equations can be used as screening tools to provide guidance on the use of refined methods of analysis to improve the load ratings of bridges vulnerable to posting from previously existing load rating classifications as well as the recently introduced vehicles.
PHD (Doctor of Philosophy)
Refined Analysis, Rating Factors, Load Distribution, Effective Width, T-Beam Bridges, Girder Bridges, Slab Bridges, Special Hauling Vehicles, Emergency Vehicles, Finite Element Modelling
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