Optimizing Design in Open-Pit Mines and Large-Scale Civil Projects

University of Tehran Researchers Present a Practical Method for Estimating Rock Mass Strength and Representative Element Volume at Real-World Scales

According to the Public Relations Office of the University of Tehran, researchers from the Faculty of Mining Engineering, College of Engineering, University of Tehran, have successfully evaluated the scale effect and anisotropy in the mechanical properties of jointed rock masses using advanced numerical methods.

Dr. Mojtaba Bahaaddini, a faculty member at the Faculty of Mining Engineering, College of Engineering, along with his research colleagues, has conducted a comprehensive study investigating the scale effect and anisotropy in the mechanical properties of jointed rock masses.

Announcing this, Dr. Bahaaddini said: "This research, conducted using the Synthetic Rock Mass (SRM) approach and combining two numerical methods—the Discrete Element Method (DEM) and the Discrete Fracture Network (DFN)—offers a novel solution for estimating the Representative Elementary Volume (REV) at large scales and can serve as an efficient tool for engineering design in open-pit mines and large-scale civil projects."

The faculty member of Mining Engineering added: "Predicting the mechanical behavior of rock masses at large scales has always been one of the fundamental challenges in rock engineering. This complexity primarily arises from the strong scale dependence and the presence of anisotropy caused by geological discontinuities. Conventional methods for estimating the Representative Elementary Volume (REV) face limitations, but numerical simulations represent a reliable and efficient alternative for this purpose."

In this research, the results of which have been published in a reputable international journal, the researchers used the Synthetic Rock Mass (SRM) approach and combined two numerical methods—the Discrete Element Method (DEM) and the Discrete Fracture Network (DFN)—to investigate the scale effect and anisotropy in a jointed rock mass under uniaxial loading.

According to Dr. Bahaaddini, as a case study, the active wall of one of the large open-pit iron ore mines was selected. The discontinuities present in this wall were surveyed using photogrammetry (close-range photogrammetric surveying), and a valid DFN model was generated based on it. The intact rock was simulated using the Bonded Particle Model (BPM), and to maintain computational efficiency, the particle size was increased as the model dimensions increased.

By conducting uniaxial compressive tests on 54 models with different sizes and orientations, the researchers achieved remarkable results. The findings indicate that both the Uniaxial Compressive Strength (UCS) and the deformation modulus of the rock mass decrease with increasing sample size; however, the deformation modulus exhibits a more rapid rate of decrease.

According to this study, the Mechanical Representative Elementary Volume (Mechanical REV) for this rock mass was determined to be 5 × 5 × 10 cubic meters. It was also found that the studied rock mass exhibits significant anisotropy, which is more pronounced for the Uniaxial Compressive Strength parameter than for the deformation modulus. The researchers found that at dimensions larger than 5 meters, although the Uniaxial Compressive Strength and deformation modulus show less sensitivity to scale changes, the anisotropy persists to larger dimensions, which is due to the dominant effect of the joint set orientation.

One of the key achievements of this research is the relationship between the "Geometrical Representative Elementary Volume" and the "Mechanical Representative Elementary Volume". The key and practical point of this research is that the "Geometrical REV" can be used as a preliminary and practical indicator for estimating the "Mechanical REV". This finding provides an efficient and rapid tool for engineering design at large scales, such as open-pit mines, rockfill dams, tunnels, and other civil projects, and is considered an effective step toward reducing costs and increasing accuracy in predicting the behavior of rock masses.

Article: https://www.sciencedirect.com/science/article/abs/pii/S0266352X26004763