Fractal analysis of relation between strength and pore structure of hardened mortar

Document Type

Article

Publication Date

3-15-2017

Abstract

© 2016 Elsevier Ltd The pore structure is the fatal factor which influences the strength of cement mortar and concrete. A lot of researches on the relationship between the strength and the pore structure were developed. Initially, porosity is the only factor in the strength models. As the development of research, it is illustrated that the pore size distribution also has significant effect on the strength. The pore size distribution is taken into consideration in the strength model in different forms. However, these models are still unavailable to simulate the relationship between strength and pore structure, because the parameters used for representing the pore size distribution are not accurate enough. In the present research, strength and pore structure were tested on thirteen Portland cement mortar mixtures to collect the original data of the strength and pore structure. In order to enhance the reliability of the strength model, the pore volume and the pore size distribution were all considered. The fractal theory was employed to characterize the pore size distribution more accurately than ever used parameters. According to the regression analysis results, the fractal dimension of pore surface and the capillary pore volume were respectively selected as representative parameters of pore size distribution and pore volume. The research results indicate that the relations between strength and fractal dimension and capillary pore volume present positive power function and negative power function respectively. The ratio of fractal dimension to capillary pore volume is addressed as the new parameter for strength model. Finally, relational expression of power function is proposed between the compressive strength and the ratio of fractal dimension to capillary pore volume. Regression analysis indicates that the strength model relative to pore structure addressed in this study has high prediction accuracy.

Publication Title

Construction and Building Materials

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