Abstract
Effective flange width is widely used in bridge design to consider the effect of shear lag. The simplified formula for the effective flange width of box girder bridges of variable depth in existing codes and studies may not be conservative, and accurate methods, such as the finite element method, are time‐consuming. The purpose of this research is to develop a method that uses a convolutional neural network (CNN) to predict the effective width of box girder bridges of varying depths. These models have been trained, validated, and tested on datasets generated from thousands of finite element models. The lower error in the test set indicates that the CNN model can be used to predict the effective width. In addition, the impact of different architectures is also studied. The proposed method makes real‐time analysis possible and has a wide range of applications in the analysis and design of box‐girder bridges at different depths.
Highlights
Introduction1. Introduction e shear-lag effect is a phenomenon of uneven distribution of normal stress, which exists in various civil engineering structures, such as box-girder bridges
Introduction e shear-lag effect is a phenomenon of uneven distribution of normal stress, which exists in various civil engineering structures, such as box-girder bridges. is phenomenon can lead to erroneous estimations of displacement and stress in extreme fibers based on beam bending theory [1–3]
It is used to replace the actual width in a simplified analysis based on the elementary beam theory, and the normal stress within the effective flange width must be the maximum normal stress, which likely occurs near the web-flange interaction at the critical sections with peak moments to satisfy strength-design requirements [9]. is concept is recommended by various codes and standards, including AASHTO LRFD Bridge Design Code, British Standards Institution (BSI) BS 5400, and so on. ese codes provide some formulas and empirical curves for different support conditions to simplify calculations by considering only the section width (b) and beam span width (L)
Summary
1. Introduction e shear-lag effect is a phenomenon of uneven distribution of normal stress, which exists in various civil engineering structures, such as box-girder bridges. Ese codes provide some formulas and empirical curves for different support conditions to simplify calculations by considering only the section width (b) and beam span width (L). Take the AASHTO LRFD Bridge Design Specifications as representative of these It provides two empirical curves of effective flange width coefficients, which are equal to the effective width divided by the physical width. Besides the AASHTO LRFD specifications, the Specifications for the Design of Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts (JTG 3362-2018) and the Steel, Concrete, and Composite Bridges (Part 5) considered the section width and beam span width alone. Calculating effective width from formulas or curves is still time-consuming. e design efficiency can be improved if the effective width can be predicted rapidly
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