Exploring concrete slump model using artificial neural networks

被引：57
|
作者：
Yeh, IC [1 ]
机构：
[1] Chung Hua Univ, Dept Civil Engn, Hsinchu 30067, Taiwan
来源：
JOURNAL OF COMPUTING IN CIVIL ENGINEERING | 2006年 / 20卷 / 03期
关键词：
concrete; fly ash; material properties; models; mixtures; neural networks;
D O I：
10.1061/(ASCE)0887-3801(2006)20:3(217)
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Fly ash and slag concrete (FSC) is a highly complex material whose behavior is difficult to model. This paper describes a method of modeling slump of FSC using artificial neural networks. The slump is a function of the content of all concrete ingredients, including cement, fly ash, blast furnace slag, water, superplasticizer, and coarse and fine aggregate. The model built was examined with response trace plots to explore the slump behavior of FSC. This study led to the conclusion that response trace plots can be used to explore the complex nonlinear relationship between concrete components and concrete slump.
引用
收藏
页码：217 / 221
页数：5
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