New formulas for predicting the lateral–torsional buckling strength of steel I-beams with sinusoidal web openings. (December 2022)

• Record Type: Journal Article
• Authors: de Carvalho, Adriano Silva; Hosseinpour, Mahmoud; Rossi, Alexandre; Martins, Carlos Humberto; Sharifi, Yasser
• Is Part Of: Thin-walled structures. Volume 181(2022)
• Publication Date: 2022-12
• Subjects: Lateral torsional buckling -- Finite element modeling -- Sinusoidal web openings -- Artificial neural network -- Stepwise regression; Thin-walled structures -- Periodicals; 690.1
• DOI: 10.1016/j.tws.2022.110067
• Languages: English
• ISSNs: 0263-8231

Abstract

Abstract: Lateral torsional buckling (LTB) of steel I-beams is characterized by simultaneous lateral deflection and twist. LTB is an instability failure mode that has been intensively investigated. However, existing standard procedures and formulations still have limitations in determining the LTB ultimate moment, especially when considering the use of perforated beams. 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 LTB resistance of steel I-beams with sinusoidal web openings. 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 LTB 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 LTB strength. The results showed that the proposed formula based on ANN not only present a reasonable accuracy compared to the existing formulations but also can be used by engineers as practical equations in the design of I-beams with sinusoidal web openings. Highlights: The LTB strength of 357 finite element model of steel I-beams with sinusoidal web openings were analyzed. The ANN and SR have been used to predict the formulae for better LTB strength prediction. The accuracy of the developed formula is verified versus the FE data using several suitable criteria. The existing predictions given by the researchers were compared with the formula obtained from the SR, and ANN.