Prediction of properties of the cement incorporated with nanoparticles by principal component analysis (PCA) and response surface regression (RSR)

被引:9
作者
Patil, Hiteshkumar [1 ]
Dwivedi, Arunkumar [2 ]
机构
[1] KBC North Maharashtra Univ, Jalgaon 425001, Maharashtra, India
[2] Sandip Univ, Sch Engn & Technol, Nasik 422002, India
关键词
Cement paste; Compressive strength; Nano-particles; Principal component analysis; Response surface regression; SELF-COMPACTING CONCRETE; MECHANICAL-PROPERTIES; STRENGTH; MORTAR;
D O I
10.1016/j.matpr.2020.09.170
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The present work plans to mix the Zinc oxide (ZnO) nanoparticles with Portland Pozzolana Cement (PPC) mortar and assessing the imaginable enhancements for their mechanical and physical properties. The current research study will also be helpful in the hereafter for the successful use of ZnO as a sustainable construction material in the building industry. The amount of ZnO differing from 0%, 0.25%, 0.5% & 0.75% by a weight of cement. The properties of cement-like consistency, setting time of cement, Soundness, and Compressive strength were tested. At the end of the research work, it was discovered that all properties of PPC were improved as an increase in the level of ZnO, anyway, perfect test results are procured on the addition of 0.5% ZnO. As compared to reference mix the compressive strength increases by 5%, Initial and final setting time are reduced by 4%, water requirement for making cement paste is reduced by 1%, expansion by cement is reduced by 9%. The incorporation of ZnO quickens the cement hydration responses, decreases the volume of voids, and increases the compressive strength of the cement. In actual practice, the merging of ZnO in cement is suitable for the up-gradation of mechanical properties of cement and also aids in attaining sustainable development. The research work results are validated by using Principal Component Analysis (PCA) and Response Surface Regression (RSR) analysis. PCA describes the correlation and necessity of dependent and independent variables in the research work and mathematical model developed by RSR analysis predict the results very closer to the experimental values. So RSR gives the best-fitted model for the experimentation as the residuals by the model are very few with value near to zero. (C) 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Advanced Materials Behavior and Characterization.
引用
收藏
页码:1358 / 1367
页数:10
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