A New Formula for Predicting Lateral Distortional Buckling Strength of I-Beams Subjected to Different Loading Conditions

Abstract

Lateral distortional buckling (LDB) mode has been investigated as one of the failure modes in steel I-beams. The LDB mode in such beams is known by simultaneous lateral deflection, twist, and cross-sectional change due to web distortion. However, many studies have been conducted to investigate the behavior of this failure mode; so far, no formula has been found to calculate the ultimate LDB resistance of I-beams, which also takes into account the effect of different loading conditions. Consequently, in the current paper, by conducting an extensive parametric study, it was tried to investigate the effect of all main parameters as well as the effect of different loading conditions on the ultimate LDB resistance of I-shaped beams. Then, based on the provided database, the artificial neural network (ANN) method was employed, and based on it, a high-precision formulation was proposed to predict the ultimate LDB strength of steel I-beams. In addition to the ANN method, a regression-based formula was also developed as a classical method to examine the differences between the two methods. Finally, the proposed formulas were compared with other existing formulas for estimating the LDB strength. The results showed that the proposed formula based on ANN not only presents a reasonable accuracy compared to the existing formulations but also can be used by engineers as practical equations in the design of I-beams.