TY - JOUR
T1 - The Properties of Cement-Mortar at Different Cement Strength Classes
T2 - Experimental Study and Multi-objective Modeling
AU - Kazemi, Ramin
AU - Shadnia, Rasoul
AU - Eskandari-Naddaf, Hamid
AU - Zhang, Lianyang
N1 - Publisher Copyright:
© 2022, King Fahd University of Petroleum & Minerals.
PY - 2022/10
Y1 - 2022/10
N2 - A multi-scale experimental study was carried out to investigate the porosity, flexural and compressive strengths of cement-mortar at different cement strength classes (CSCs). Specifically, 54 mix designs (totally 324 specimens) were first defined and then the produced cement-mortar specimens were tested to consider their properties. To identify the microstructure of the specimens at different conditions, scanning electron microscope (SEM) imaging and energy dispersive spectroscopy (EDS) analysis were also performed. The results show that the porosity, and flexural and compressive strengths change significantly at different CSCs. At the same mix proportion, the cement-mortar has lower porosity as well as higher flexural and compressive strengths as the CSC gets higher. Considering the combined effects of various parameters on the mentioned properties, a new multi-objective model using artificial neural network (ANN) was proposed to analyze the experimental data of porosity, and flexural and compressive strengths. The results show that the proposed model is able to provide predictions with good accuracy.
AB - A multi-scale experimental study was carried out to investigate the porosity, flexural and compressive strengths of cement-mortar at different cement strength classes (CSCs). Specifically, 54 mix designs (totally 324 specimens) were first defined and then the produced cement-mortar specimens were tested to consider their properties. To identify the microstructure of the specimens at different conditions, scanning electron microscope (SEM) imaging and energy dispersive spectroscopy (EDS) analysis were also performed. The results show that the porosity, and flexural and compressive strengths change significantly at different CSCs. At the same mix proportion, the cement-mortar has lower porosity as well as higher flexural and compressive strengths as the CSC gets higher. Considering the combined effects of various parameters on the mentioned properties, a new multi-objective model using artificial neural network (ANN) was proposed to analyze the experimental data of porosity, and flexural and compressive strengths. The results show that the proposed model is able to provide predictions with good accuracy.
KW - Cement strength class
KW - Cement-mortar
KW - Multi-objective model
KW - Multi-scale study
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U2 - 10.1007/s13369-022-06820-7
DO - 10.1007/s13369-022-06820-7
M3 - Article
AN - SCOPUS:85128811291
SN - 1319-8025
VL - 47
SP - 13381
EP - 13396
JO - Arabian Journal for Science and Engineering
JF - Arabian Journal for Science and Engineering
IS - 10
ER -