Analytical model for compressive strength, elastic modulus and peak strain of structural lightweight aggregate concrete

被引:62
作者
Cui, H. Z. [2 ]
Lo, Tommy Yiu [1 ]
Memon, Shazim Ali [1 ]
Xing, F. [2 ]
Shi, X. [3 ]
机构
[1] City Univ Hong Kong, Dept Civil & Architectural Engn, Hong Kong, Hong Kong, Peoples R China
[2] Shenzhen Univ, Guangdong Prov Key Lab Durabil Marine Civil Engn, Coll Civil Engn, Shenzhen, Guangdong, Peoples R China
[3] Shenzhen Univ, Dept Civil Engn, Coll Civil Engn, Shenzhen, Guangdong, Peoples R China
关键词
Lightweight aggregate; Lightweight aggregate concrete; Compressive strength; Modulus of elasticity; Peak strain;
D O I
10.1016/j.conbuildmat.2012.06.034
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In lightweight aggregate concrete (LWAC), the constituent lightweight aggregates (LWAs) may have a lower strength and elastic modulus than the mortar matrix, and thus the properties of the LWA are the most important determinants of the properties of the resulting concrete. In this research, the influence of volume fraction and properties of five different types of LWA on the mechanical performance of LWAC were studied. Analytical models for predicting the compressive strength, elastic modulus and peak strain of LWAC are proposed by taking into account the effect of volume content, particle density, crushing strength and shape index of LWA. Compressive strength of mortar was also taken into account. Based on the significance of the independent variables, it was concluded that the volume content, crushing strength and shape index of LWA showed more influence on the prediction model for compressive strength of LWAC. For the prediction model of elastic modulus of LWAC, the effect of volume content, particle density and shape index of LWA was more pronounced while the crushing strength and shape index of LWA showed more influence on the prediction model for peak strain of LWAC. The validation of models showed that the maximum difference between the experimental and predicted results to be less than 1.5%. Thus, the precision of prediction model demonstrated the effectiveness of the method and the potential application of the models for LWAC. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1036 / 1043
页数:8
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