Artificial Intelligence Approach in Predicting the Effect of Elevated Temperature on the Mechanical Properties of PET Aggregate Mortars: An Experimental Study
Küçük Resim Yok
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Heidelberg
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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 degrees 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%.
Açıklama
Anahtar Kelimeler
Waste PET aggregate, Flexural strength, Compressive strength, Elevated temperature, Artificial neural network
Kaynak
Arabian Journal For Science and Engineering
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
46
Sayı
5
