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Strength and strain modeling of CFRP-confined concrete cylinders using ANNs

机译:CFRP限制混凝土缸使用ANN的强度和应变模型

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摘要

Carbon fiber reinforced polymer (CFRP) has extensive use in strengthening reinforced concrete structures due to its high strength and elastic modulus, low weight, fast and easy application, and excellent durability performance. Many studies have been carried out to determine the performance of the CFRP confined concrete cylinder. Although studies about the prediction of confined compressive strength using ANN are in the literature, the insufficiency of the studies to predict the strain of confined concrete cylinder using ANN, which is the most appropriate analysis method for nonlinear and complex problems, draws attention. Therefore, to predict both strengths and also strain values, two different ANNs were created using an extensive experimental database. The strength and strain networks were evaluated with the statistical parameters of correlation coefficients (R2), root mean square error (RMSE), and mean absolute error (MAE). The estimated values were found to be close to the experimental results. Mathematical equations to predict the strength and strain values were derived using networks prepared for convenience in engineering applications. The sensitivity analysis of mathematical models was performed by considering the inputs with the highest importance factors. Considering the limit values obtained from the sensitivity analysis of the parameters, the performances of the proposed models were evaluated by using the test data determined from the experimental database. Model performances were evaluated comparatively with other analytical models most commonly used in the literature, and it was found that the closest results to experimental data were obtained from the proposed strength and strain models.
机译:碳纤维增强聚合物(CFRP)由于其高强度和弹性模量,低重量,快速且易于应用,以及出色的耐用性能而广泛使用加强钢筋混凝土结构。已经进行了许多研究以确定CFRP限制混凝土圆筒的性能。虽然关于使用ANN的狭窄抗压强度预测的研究是在文献中,研究的功能不全,以预测密集混凝土圆筒的菌株使用ANN,这是非线性和复杂问题的最合适的分析方法,引起了注意力。因此,为了预测两个强度和应变值,使用广泛的实验数据库创建了两种不同的ANN。使用相关系数(R2)的统计参数,根均方误差(RMSE)和平均误差(MAE)评估强度和应变网络。发现估计值接近实验结果。使用为工程应用方便的方便准备的网络来推导数学方程来预测强度和应变值。通过考虑具有最重要因素的输入来执行数学模型的敏感性分析。考虑到从参数的灵敏度分析获得的限制值,通过使用从实验数据库确定的测试数据来评估所提出模型的性能。与文献中最常用的其他分析模型相对评估模型性能,发现从提出的强度和应变模型获得最接近实验数据的结果。

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