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Artificial Intelligence Approach in Predicting the Effect of Elevated Temperature on the Mechanical Properties of PET Aggregate Mortars: An Experimental Study
Arabian Journal for Science and Engineering ( IF 2.6 ) Pub Date : 2021-01-05 , DOI: 10.1007/s13369-020-05280-1
Andaç Batur Çolak , Kubilay Akçaözoğlu , Semiha Akçaözoğlu , Gülhan Beller

In this study, the effect of high temperature on the flexural and compressive strength of mortars containing waste PET aggregates was investigated experimentally. The mortar samples prepared in 5 different concentrations with a total of 2.5%, 5%, 10%, 20% and 30% PET aggregate substitution were heated up to 100, 150, 200, 250, 300 and 400 °C. After waiting for 1, 2 and 3 h at these temperatures, flexural and compressive strength tests were performed. It was observed that flexural strength and compressive strength values decreased with increasing temperature and PET aggregate amounts in all mixtures. An artificial neural network was designed to estimate flexural and compressive strength values using experimental data. It has been observed that the developed artificial neural network can predict flexural and compressive strengths with an average error of − 0.51%.



中文翻译:

人工智能方法预测高温对PET骨料砂浆力学性能的影响:一项实验研究

在这项研究中,实验研究了高温对含废PET骨料的砂浆的抗折强度和抗压强度的影响。将以5种不同浓度制备的砂浆样品加热至100、150、200、250、300和400°C,以总计2.5%,5%,10%,20%和30%的PET集料替代。在这些温度下等待1、2和3小时后,进行了抗弯强度和抗压强度测试。观察到,在所有混合物中,抗弯强度和抗压强度值均随着温度的升高和PET聚集量的增加而降低。设计了一个人工神经网络,以使用实验数据估算抗弯强度和抗压强度。

更新日期:2021-01-05
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