Lateral–torsional buckling resistance prediction model for steel cellular beams generated by Artificial Neural Networks (ANN)

The present paper aims to develop an Artificial Neural Network (ANN) formula to predict the lateral-torsional buckling (LTB) resistance of slender steel cellular beams. A finite element model is developed and validated through experimental tests followed by a parametric study. 768 models are employed to train the ANN formula. The results are compared with the analytical models as well as the equation predicted by ANN. It was concluded that the ANN model with seven neurons can accurately predict the LTB resistance of cellular beams as well as the LTB combined with web-post buckling or web distortional buckling modes. Hence, the ANN-based formula can be adopted as design tool. •Finite element results are employed to train the ANN.•Neutral and destabilising effects of loading are also modelled.•ANN-based formula for lateral–torsional buckling resistance of cellular beams is developed•ANN predictions are more in-line with FE results that those obtained analytically.