非线性局部剪力交互作用下的开裂组合梁长期变形神经网络研究

结合有限元分析和人工神经网络,提出一种新的思路,研究简支组合梁的短期和长期变形。本文建立两个神经网络模型,采用相关论文中有限元模型的结果进行样本训练。有限元模型考虑了抗剪连接件的非线性荷载-滑移关系,以及蠕变、收缩和混凝土板的裂缝。而对没开裂的混凝土只考虑了蠕变、收缩的影响。为训练及验证两个神经网络模型,建立了一个包括不同设计参数的大数据库。研究发现,两个神经网络模型均能预测组合梁的变形。因此,神经网络模型可用以评估非几何设计参数对简支组合梁的短、长期变形影响。最后,根据AISC规范和欧洲规范4方法计算简支组合梁的短、长期变形,并与有限元模型结果进行比较。结果表明,与有限元方法相比,AISC方法低估了短期变形而高估了长期变形。

Long-Term Deflection of Cracked Composite Beams with Nonlinear Partial Shear Interaction:A Study Using Neural Networks

A new study of the short-and long-term deflections of simply-supported composite beams using finite element analysis and artificial neural networks (ANNs) is presented.In this study,two ANN models are developed and trained using the results of a finite element model developed by the authors in a companion paper.The finite element model accounted for the nonlinear load-slip relationship of shear connectors as well as the creep,shrinkage,and cracking of concrete slabs.The effects of creep and shrinkage of the...