Document Type : Original Research Paper
Author
Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran
Abstract
Understanding the link between rock microstructure and macroscopic physicomechanical behavior remains a central challenge in rock mechanics due to the intrinsic heterogeneity and discontinuity of geomaterials. This study presents an experimental investigation into the relationships between fractal dimension, determined using the box-counting method on thin-section microphotographs, and key physicomechanical properties of rocks through statistical analysis. A total of 40 rock samples representing a wide range of lithologies were collected from different mines in Iran. Standardized laboratory tests were conducted to determine Brazilian tensile strength, Schmidt rebound hardness, density, and porosity. High-resolution microphotographs were obtained from polished thin sections under controlled optical conditions and processed to extract fractal dimensions using ImageJ software. Regression models were then developed to examine the relationships between fractal metrics and measured properties. The results reveal clear and statistically significant relationships between fractal dimension and all examined properties. Among the investigated parameters, porosity exhibited the strongest correlation with fractal dimension, indicating that fractal geometry is particularly sensitive to the spatial distribution and configuration of void spaces within the rock fabric. Brazilian tensile strength, Schmidt rebound hardness, and density also exhibited systematic relationships with fractal dimension, confirming that microstructural irregularity plays a decisive role in governing both physical and mechanical behavior. This study shows that thin-section fractal analysis is a practical and cost-effective method for quantifying rock heterogeneity and relating petrographic features to engineering properties. Coupling fractal geometry with regression modeling provides a reliable framework for indirectly predicting physicomechanical parameters and linking microstructural characteristics to macroscopic rock behavior.
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