Design of fly ash geopolymer concrete mix proportions using Multivariate Adaptive Regression Spline model

被引:111
作者
Lokuge, Weena [1 ]
Wilson, Aaron [1 ]
Gunasekara, Chamila [2 ]
Law, David W. [2 ]
Setunge, Sujeeva [2 ]
机构
[1] Univ Southern Queensland, Sch Civil Engn & Surveying, Springfield, Qld 4300, Australia
[2] RMIT Univ, Sch Engn, Civil & Infrastruct Engn, 124 La Trobe St, Melbourne, Vic 3000, Australia
关键词
Fly ash; Geopolymer concrete; Multivariate Adaptive Regression Spline model; Mix design; Compressive strength; MECHANICAL-PROPERTIES; COMPRESSIVE STRENGTH; NEURAL-NETWORK; BEHAVIOR; EMISSIONS; OPC;
D O I
10.1016/j.conbuildmat.2018.01.175
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Many research studies have been conducted during recent years on the topic of geopolymer materials based on the engineering performance of the concrete. What has been missing is the combination of this research in a way that would provide a simple to use design tool for geopolymer concrete as a replacement to concrete based on Portland Cement. This research paper addresses this requirement for developing a standard mix design method for Class F, low calcium fly ash based geopolymer concrete using Multivariate Adaptive Regression Spline (MARS) model. Published geopolymer concrete research data was combined into a database and analysed to give the ratios of water/solid, alkaline activator/fly ash, Na2SiO3/NaOH, and NaOH molarity. Targeted compressive strengths ranging from 30 MPa to 55 MPa at 28 days were achieved with laboratory experiments, using the proposed MARS mix design methodology. Thus, this tool has the capability to provide a novel approach for the design of geopolymer concrete mixes to achieve the desired compressive strength appropriate for the construction requirement. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:472 / 481
页数:10
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