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Nonlinear analysis of load-deflection testing of reinforced one-way slab strengthened by carbon fiber reinforced polymer (CFRP) and using artificial neural network (ANN) for prediction

机译:碳纤维增强聚合物(CFRP)增强的单向板的载荷挠度测试的非线性分析,并使用人工神经网络(ANN)进行预测

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摘要

Load-deflection curve is the most important part of the structural analysis of RC beam and slab. The load-deflection analysis of the RC one-way slab strengthened by CFRP using experimental work, finite element analysis (FEA), artificial neural network (ANN), and a comparison of them together are the important objective of this study. The dimension of the one-way slab was 1800�400�120 mm which was strengthened by different length and width of carbon fiber reinforced polymer (CFRP). The experimental results sufficiently adapted with FEA and ANNs output. The feed forward back-propagation (FFB) was the best ANN for prediction of load-deflection curve with minimum error below 1, and maximum correlation coefficient close to 1.
机译:荷载-挠度曲线是RC梁和楼板结构分析中最重要的部分。本研究的重要目的是通过实验工作,有限元分析(FEA),人工神经网络(ANN)将CFRP加固的RC单向板的荷载-挠度分析。单向板的尺寸为1800×400×120 mm,这通过碳纤维增强聚合物(CFRP)的不同长度和宽度得到加强。实验结果足以适应FEA和ANN的输出。前馈反向传播(FFB)是预测载荷-挠度曲线的最佳ANN,其最小误差小于1,最大相关系数接近1。

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