Vol.39, No.1, 2021, pp.121-131, doi:10.32604/csse.2021.014464
Quantifying the Mechanical Properties of White Sandstone Based on Computer Fractal Theory
  • Yong Wang, Yongyan Wang*, Nan Qin, Sa Huang, Le Chang, Shunzheng Hou
School of Mechanical and Electrical Engineering, Qingdao University of Science and Technology, Qingdao, 266061, China
* Corresponding Author: Yongyan Wang. Email:
Received 22 September 2020; Accepted 27 October 2020; Issue published 10 June 2021
The work presented in this paper was conducted to quantify the relationship between the pore characteristics and mechanical properties of white sandstone. The study include tests carried out under the coupling effects of chemical corrosion, temperature, nuclear magnetic resonance, and mechanical tests. Computer fractal theory was employed to describe and quantify the characteristics of the growth of pores in white sandstone under the same coupling effect. A custom developed program code, in the MATLAB software platform, was used for calculating the growths of the pores in white sandstone when subjected to coupling effects. The correlation between the computer fractal dimension of the growth of the pores in rock and characteristics of mechanical damage was accordingly analyzed. The results showed that when the temperature was set at a level lower than 100°C, it caused damage to the rock and strength reduction, primarily due to the rates of chemical reactions, the generation, and evolution of pores in the rock mass under the coupling effects of chemical corrosion and temperature. Overall, it was observed that the higher the value of the computer fractal dimension, the higher the growth of the pores, and the lower the uniaxial compressive strength of the white sandstone.
White sandstone; pore characteristics; mechanical properties; MATLAB; chemical corrosion; temperature; fractal dimension; nuclear magnetic resonance
Cite This Article
Y. Wang, Y. Wang, N. Qin, S. Huang, L. Chang et al., "Quantifying the mechanical properties of white sandstone based on computer fractal theory," Computer Systems Science and Engineering, vol. 39, no.1, pp. 121–131, 2021.
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