Neural networks for lateral torsional buckling strength assessment of cellular steel I-beams

2019 ◽  
Vol 22 (9) ◽  
pp. 2192-2202 ◽  
Author(s):  
Yasser Sharifi ◽  
Adel Moghbeli ◽  
Mahmoud Hosseinpour ◽  
Hojjat Sharifi
Keyword(s):  
Neural Networks ◽  
Lateral Torsional Buckling ◽  
Torsional Buckling ◽  
Strength Assessment ◽  
Buckling Strength

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

2022 ◽  
Vol 170 ◽  
pp. 108592
Author(s):  
Felipe Piana Vendramell Ferreira ◽  
Rabee Shamass ◽  
Vireen Limbachiya ◽  
Konstantinos Daniel Tsavdaridis ◽  
Carlos Humberto Martins
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prediction Model ◽  
Lateral Torsional Buckling ◽  
Torsional Buckling ◽  
Buckling Resistance ◽  
Resistance Prediction ◽  
Artificial Neural

scholarly journals Analytical Solution for Lateral-Torsional Buckling of Concrete-Filled Tubular Flange Girders with Torsional Bracing

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yingchun Liu ◽  
Zhaoming Hang ◽  
Wenfu Zhang ◽  
Keshan Chen ◽  
Jing Ji
Keyword(s):  
Analytical Solution ◽  
Lateral Displacement ◽  
Data Sets ◽  
Torsional Angle ◽  
The Finite Element Method ◽  
Lateral Torsional Buckling ◽  
Torsional Buckling ◽  
Concentrated Load ◽  
Buckling Strength ◽  
Parametric Studies

Concrete-filled tubular flange girders have been used in bridges, and torsional bracings are widely used in them to increase the lateral-torsional buckling strength. This article proposes an analytical solution for the lateral-torsional buckling (LTB) of concrete-filled tubular flange steel girders with torsional bracing under a concentrated load. The modal trial functions of lateral displacement and the torsional angle are expressed by the first six terms of the trigonometric function. By introducing dimensionless parameters, the variational solution of energy for the buckling equation of the LTB of the girders is obtained, and the formula for the dimensionless critical moment of its LTB is derived using 1stOpt based on 32,550 data sets. Compared with the finite element method, the proposed critical formula is highly accurate and can be applied to engineering design. Finally, parametric studies were conducted on the effects of the stiffness of torsional bracing, the span of the girder, and the flange steel ratio.

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