A Simplified Model of a Reinforced Square Hollow Section (SHS) T-Joint for Stress Evaluation in Bus Superstructures

This study aims to create a simplified model of a reinforced square hollow section (SHS) T-joint found in bus superstructures. The approach is to use a combination of one- and two-dimensional finite element models to represent a reference three-dimensional finite element (solid) model of the joint and determine stress concentration factors (SCFs) as functions of the geometrical variables of the joint. This approach requires the stiffness of the simplified model to be equivalent to the stiffness of the reference solid model. Trial models, therefore, must be proposed and their stiffnesses must be evaluated against the stiffness of the reference solid model. The best trial model is then selected based on the stiffness error function defined to represent the deviation of the simplified model's stiffness from the reference model's stiffness. After a trial model with minimum stiffness error is selected, its SCFs, relating the maximum stress in the simplified model to the maximum stress in the reference solid model, are determined. Since the maximum stress is assumed to be at the weld toe where structural discontinuity exists, the maximum stresses on both simplified model and reference solid model are evaluated based on a hot spot stress (HSS) method. In this study, three trial models, namely Model A, Model B, and Model C, were investigated. Model B, consisting of beam and shell elements with particular constraints on the joint-reinforcement geometry, was found to provide the minimum stiffness errors of 8.09%, 6.87%, and 6.44% for three different joint dimensions. The SCFs were then determined as a function of the thickness-to-width ratio of the joint under static in-plane bending load. The resulting simplified model allows the stress evaluation on the bus superstructures to be done more quickly compared to a solid model while maintaining the accuracy of the solutions. Consequently, the designs of bus superstructures can be explored more thoroughly, leading to a better design.