Title: Exploring Effects of Freight and Emergency Vehicles on Distribution Factors of Concrete T Beam Bridges Using Refined Analysis and Machine Learning

Author(s): Abdou Ndong

Publication: Web Session

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Date: 10/17/2021

Abstract:
Recent revisions to federal guidelines require state departments of transportation (DOTs) to rate bridges in their inventory with special hauling vehicles (SHVs) and emergency vehicles (EVs). SHVs refers to single unit trucks with closely spaced multiple axles, typically ranging from four to seven. EVs 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 rating 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 rating vehicles. This presents a challenge to state DOTs as some bridges may require posting when rated with these specialized vehicles. This research evaluates the distribution factors for concrete T-beam bridges under different truck loads using refined analysis. In particular, a total of 25 in-service T-beam bridges are modeled and analyzed to compute the moment and shear load distribution factors for exterior and interior girders under one-lane and multiple-lane loaded conditions, and the results are compared with those computed from the code-specified equations. In addition, a support vector machine (SVM) was trained using numerical data to identify the governing truck type for distribution factor based on bridge parameters such as span length and spacing. Using the data obtained from these numerical simulations, a series of multi-parameter linear regression models are also developed to predict the percent change in distribution factor for T-beam bridges with different geometrical characteristics if a refined method analysis is implemented.