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A new formulation for distortional buckling stress in cold-formed steel members

机译:冷弯型钢构件屈曲变形的新公式

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摘要

Distortional buckling of compression members usually comprises rotation and translation of each flange and lip about the flange-web connection in opposite directions. The present procedures for the calculation of elastic distortional buckling stress in the literature are very complex, cumbersome and have long expressions. In this paper a new neural network (NN) based formula is proposed for the determination of the elastic distortional buckling stress of cold-formed steel C-sections with both end sections pinned. The focus of this study is on the distortional buckling, for which existing results are for sections subjected to pure compression and/or pure bending only. The data used for training and testing NNs is taken from Schafer's report. The NN-based estimates are compared with the experimental, numerical and analytical results of different researchers and methods. It was found that the proposed NN based-formula is practical in predicting the elastic distortional buckling stress of cold formed steel C-sections.
机译:压缩构件的变形屈曲通常包括使每个凸缘和唇沿凸缘-腹板连接件沿相反方向旋转和平移。文献中用于计算弹性变形屈曲应力的当前程序非常复杂,麻烦并且具有长表达式。本文提出了一种新的基于神经网络的公式,用于确定两端固定的冷弯C型钢的弹性变形屈曲应力。这项研究的重点是变形屈曲,对于变形屈曲,现有结果仅针对纯压缩和/或纯弯曲的截面。用于训练和测试NN的数据取自Schafer的报告。将基于神经网络的估计与不同研究人员和方法的实验,数值和分析结果进行比较。已经发现,所提出的基于NN的公式可用于预测冷弯型钢C型截面的弹性变形屈曲应力。

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