期刊
JOURNAL OF MATERIALS IN CIVIL ENGINEERING
卷 33, 期 11, 页码 -出版社
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)MT.1943-5533.0003944
关键词
Dolomite powder; Pore structure; Segmented fractal dimension; Compressive strength; Critical diameter
资金
- National Key Research and Development Program of China [2019YFC1906203]
This study utilized fractal geometry to characterize the complex pore structure of cement-based materials more accurately. The relationship between segmented fractal dimension and compressive strength was found to vary for different pore ranges, with positive and negative linear functions for gel pores and large pores, respectively. The proposed strength equations based on segmented fractal dimension showed high prediction accuracy according to regression analysis.
The macroscopic property of cement-based materials depends on their pore structure. Due to the complex and disordered pore structure of cement-based materials, traditional parameters like porosity and mean distribution radius are not accurate enough for strength predictions. Fractal geometry was employed to characterize the complexity of pore structure more accurately than existing parameters, especially the scale-dependent fractal properties, which are more dependent on the pore ranges. In this study, the pore size range of cement-based materials containing dolomite powder was regularly segmented to characterize the scale-dependent fractal nature of the pore structure. The relationship between the segmented fractal dimension and the compressive strength was discussed. Results based on the mercury intrusion porosimetry (MIP) and mechanical property tests showed that the difference existed in the relationship between segmented fractal dimension and dolomite powder content under various pore ranges. The relationships between compressive strength and fractal dimension of gel pores and fractal dimension of large pores presented positive and negative linear function, respectively. The strength equations expressed in terms of the segmented fractal dimension were proposed. Regression analysis proved that the equations in this study had high prediction accuracy.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据