In the heart of Iran’s dimension stone industry, a groundbreaking study led by Amirhossein Vahedi from the Department of Mining Engineering at Isfahan University of Technology is revolutionizing how we approach quarry management and extraction processes. Published in the journal ‘Analytical and Numerical Methods in Mining Engineering’, this research delves into the intricate world of fracture modeling, offering a fresh perspective on optimizing dimension stone extraction.
Vahedi’s work focuses on the Josheghan marble mine in Isfahan Province, a region rich in geological diversity and economic potential. The study compares two prominent models used to estimate the volume of in-situ blocks: the Infinite Fracture Model (IFM) and the Discrete Fracture Network (DFN). The IFM, which assumes fractures extend indefinitely within the rock mass, often leads to inaccurate estimations. In contrast, the DFN model provides a more nuanced approach by accounting for the complexities of geological structures and hidden fractures.
To gather detailed data, Vahedi and his team established seven scanlines, each 22 meters in length, at various locations within the mine. This meticulous surveying process allowed them to analyze fracture intensity and related features, providing a comprehensive understanding of the mine’s geological conditions. “Effective management of dimension stone resources is contingent upon a thorough understanding of geological conditions and precise modeling of discontinuities within the rock mass,” Vahedi emphasizes.
The study highlights the significance of advanced techniques such as digital photogrammetry and drone technology in enhancing extraction efficiency. By utilizing these modern methodologies, the research team generated 70 DFN models based on the parameter P32, which were then used to simulate the behavior of rock blocks and estimate their volumes. This approach led to the creation of ten distinct DFN models for the entire mine area, offering more accurate estimations of extracted block volumes.
The implications of this research extend far beyond the confines of the Josheghan marble mine. As Vahedi notes, “The application of modern photogrammetry methods and DFN modeling can enhance the extraction process of dimension stones.” This insight could be particularly beneficial for dimension stone quarries in Iran, which face various challenges and could aid in sustainable development and optimization of mineral resources.
The findings of this study are poised to shape future developments in the field. By providing a more precise understanding of geological structures and discontinuities, the DFN model offers a pathway to more efficient and profitable extraction processes. This research not only contributes to a better understanding of the geological structure of mines but also leads to more effective managerial and economic decision-making in the field of mineral resource extraction. As the dimension stone industry continues to evolve, the integration of advanced modeling techniques and digital photogrammetry will undoubtedly play a pivotal role in driving innovation and sustainability.
