The paper represents a physical blasting model in laboratory scale along with a photographic approach to describe the distribution of blasted ROCK materials. For this purpose, based on we bull probability distribution function, eight samples each weighted 100 kg, were obtained. Four pictures from four different section of each sample were taken. Then, pictures were converted into graphic files with characterizing boundary of each piece of ROCKs in the samples. Error caused due to perspective were eliminated. Volume of each piece of the blasted ROCK materials and hence the required sieve size, each piece of ROCK to pass through, were calculated. Finally, original blasted ROCK size distribution was compared with that obtained from the photographic method. The paper concludes with presenting an approach to convert the results of photographic technique into size distribution obtained by seive analysis with sufficient verification.

Summary In this paper, the effect of cutter edge shape on the failure mechanism of ROCK has been investigated using particle flow code in two directions (PFC2D). Particle flow code represents a ROCK mass as an assemblage of bonded rigid particles. The standard process of generating a PFC2D assembly to represent a test model involves: particle generation, packing the particles, isotropic stress installation (stress initialization), floating particle (floater) elimination and bond installation. In PFC2D circular disks are connected with cohesive and frictional bonds and confined with planar walls. The values assigned to the strength bonds influence the macro strength of the sample. Friction is activated by specifying the coefficient of friction and is mobilized as long as particles stay in contact. Tensile cracks occur when the applied normal stress exceeds the specified normal bond strength. Shear cracks are generated as the applied shear stress surplus the specified shear bond strength either by rotation or by shearing of particles. The tensile strength at the contact immediately drops to zero after the bond breaks, while the shear strength decreases to the residual friction value. For all these microscopic behaviours, PFC only requires selection of the basic micro-parameters to define contact and bond stiffness, bond strength and contact friction, but these micro-parameters should provide the macroscale behaviour of the material being modelled. The code uses an explicit finite difference scheme to solve the equation of force and motion, and hence one can readily track initiation and propagation of bond breakage through the system. For this purpose, two numerical models with different tensile strength of 5 MPa and 25 MPa were built and compressed by two different confining pressures of 5 MPa and 25 MPa, respectively. Eight disc cutters with different edge shape peneterate into the model at the rate of 0. 02 m/s till 4 mm of disc peneteration is reached. Totally 16 simulation has been done. The ROCK materials, below the cutters, show three different mechanical behavior i. e. failure, plastic and elastic behavior. The failure zone is fully fractured. The plastic zone is consisted of partially micro crack with several major fractures. The elastic zone is an undamaged zone. The shape of cutter edge has important effect on extension of three introduce zones. When tensile strength is 5 MPa, the failure stress resulted from penetration of convex-shape cutter is the lowest one, 5. 3 MPa while the number of total cracks is maximum one, 102. It means that the cutter shape controls the failure stress and failure extension when it cuts the weak ROCK. When tensile strength is 25 MPa, the failure stress resulted from penetration of different cutters is similar, 21 MPa, but the extension of failure is largest under Ushape cutter. It means that the cutter shapes has not any effects on the failure stress when it cuts the hard ROCK while the U-shape cutter produce the largest failure zone. The results show that convex-shape edge and U-shape edge cutters have the best performance when tensile strength of ROCK is 5MPa and 25 MPa, respectively. The results also showed that the failure stress increases with increasing tensile strength, while the failure extension decreases.

In this paper, to predict the size distribution of ROCK FRAGMENTATION (D80), the blasting data and ROCK mass characteristics of Chogart, Chadormalu and Sechahum mines were used. ROCK FRAGMENTATION is affected by various parameters such as ROCK mass properties, in-situ blocks shape, blasting geometry. To quantity the shape of in-situ blocks, the fractal geometry is suitable method. To predict the ROCK FRAGMENTATION (D80) based on independent variables (ROCK mass characteristics, in-situ block shape, and blasting geometry); linear/nonlinear regression and neural network were used. The results shown that the nonlinear regression and neural network were ability to predict the size distribution of ROCK FRAGMENTATION.

Summary: This study is to simulate the ROCK FRAGMENTATION process with disc cutter in linear cutting machine (LCM) using the numerical method of finite element. The numerical model of ROCK and disc cutter was built according to the experimental settings, and then, validated with the test data. The ROCK model was built for Indiana Limestone as it was used in experimental study. The comparison of cutting forces obtained from the numerical simulation with those obtained from LCM test showed a good agreement between the simulation and the test results.Introduction: Use of tunnel boring machine (TBM) for hard ROCK tunneling has been ever increased due to the growth of technology and society, as well as growing demand. The main role of disc cutters in this machine is ROCK cutting. An accurate estimation of the forces acting on the disc cutter is very important in machine design. To do so, the cutting forces acting on a single disc cutter as well as its performance in a specific ROCK are predicted using full-scale linear ROCK cutting tests. The results are then generalized for TBM design in the same ROCK.Methodology and Approaches: The commercial finite element code ABAQUS/CAE was used to perform the numerical simulations of the ROCK cutting process in LCM test. The forces acting on a fresh constant cross section disc and specific energy were simulated. For validation purposes, the results obtained from numerical model were compared with those of experimental results.Results: and Conclusions The model validity was checked by comparing the results recorded from the experiments and those results obtained from numerical simulation. All cutting forces obtained from simulation were located in the confidence interval of experimental data. The analysis results showed that cutting forces and cutting coefficient increased non-linearly with increasing disc penetration. A good agreement was obtained between the numerical results and experimental data. Moreover, the cutting forces obtained from the simulation showed a maximum deviation of 15 and 21% from the experimental average values for normal force in penetration depth of 5 mm and rolling force in 2.5 mm, respectively.

In mechanics of ROCK fracture and comminution, researchers have always been looking for a relationship between the consumed energy and the particle size distribution of the disintegrated ROCK specimen. This relationship has important industrial applications considering the fact that comminution of ROCK is a very energy demanding process and its efficiency is very low. Furthermore, investigating the damage evolution of ROCK under different loading rates, helps to better understand and more accurately design ROCK structures such as tunnels, ROCK slopes and foundations subjected to dynamic loading. In this work, a hybrid finite-discrete element numerical model was used to simulate ROCK disintegration under different loading rates in the Split Hopkinson Pressure Bar (SHPB) system. The ROCK and the steel bars in the SHPB apparatus were simulated by the Bonded Particle Model (BPM) and finite element model, respectively. BPM is a simplified version of the discrete element method in which the discrete particles are spherical in shape. Spherical particles or balls in the BPM are very useful in reducing the computational time; the contact detection of the spherical particles is computationally very fast. The computer program CA3, which is a 3D code for static, dynamic and nonlinear simulation of geomaterials was used for the numerical analysis. To capture the rate dependent behavior of ROCK, a micromechanical model was utilized in which the bond strength at a contact point increases as a function of relative velocity of involved particles. The numerical model was calibrated to mimic the mechanical behavior of Masjed Soleyman sandstone. To facilitate and expedite the calibration process of the BPM system, the curves and dimensionless parameters introduced in the literature were used. Input pulses with different intensities were applied to the specimen in the numerical modeling of the SHPB system. The input energy and the energy consumed to disintegrate the numerical ROCK specimen were evaluated by the numerical integration. Different particle sizes in the BPM system were used to investigate the impact of combined particle size and input energy on the ROCK disintegration. The results suggest that the energy consumption density for ROCK crushing changes linearly with the stress rate. Furthermore, it is shown that the dynamic strength of the ROCK increases with the increase in the consumed energy density. The disintegrated numerical specimen was carefully inspected and its particle size distribution was obtained. This was achieved by using a searching algorithm to identify the clusters in the damaged specimen; each cluster was made of one or several spherical particles. The volume of each cluster was calculated by finding the volume of its constituent particles and the porosity of the specimen. This volume was used to obtain the equivalent radius of the cluster; the cluster shape was imagined as a sphere to identify the equivalent particle or cluster size. The mean particle size (D50) of the damaged numerical specimen shows a linear relationship with the stress rate in a logarithmic coordinate system, which is consistent with the physical test results reported in the literature.

ROCK mass properties are one of the important factors affecting the results of the blasting. In this study, in regard to the importance of optimal FRAGMENTATION in mining tried to investigate the effect of these properties on the size distribution of FRAGMENTATION in the study area including Choghart, Chadormalu and Sechahun iron ore mines. To achieve this purpose, the properties of the ROCK mass along approximately 1961 meter scanlines and 1771 meter seismic profiles was evaluated in 51 blasting blocks. Also digital image processing technique was used in order to measure the blasting FRAGMENTATION. For this purpose with the processing of 1500 images taken from the surface of muck piles was obtained size distribution of FRAGMENTATION. FRAGMENTATION changes according to the ROCK mass properties showed that with increasing of spacing, persistency, aperture, roughness and wavy surface of discontinuities, increasing of uniaxial compressive strength and longitudinal wave velocity in intact ROCKs and increasing of being close angle between discontinuities strike and free surface strike of blasting blocks to 90o, blasting material size are also increasing. The results indicate that the ROCK mass properties impact on the size of blasting materials.

In order to control and optimize a mining operation, it is important to assess the FRAGMENTATION caused by blasting and subsequent crushing and grinding stages. Prediction of the mean size of a fragmented ROCK through the ROCK mass characteristics, the blasting geometry, the technical parameters and the explosive properties is an important challenge for the blasting engineers. Some of the effective parameters on ROCK FRAGMENTATION have been investigated in several empirical models. A model for FRAGMENTATION in bench blasting was developed using the effective parameters on the existing empirical models to propose a simple applicable model for predicting the X50 value. The proposed model was calibrated by nonlinear fits to 35 bench blasts in different sites from the Sungun copper mine, the Akdaglar quarry, the and Mrica quarry. In order to validate the proposed model, the results were compared to the data obtained from six blast sites in the Chadormalu iron ore mine and the Porgera gold mine. The results indicated a small variance in X50, which was calculated by the proposed model through the image processing approach. The Comparison of the powers between the proposed and the Kuz-Ram models showed that the specific explosive energy and the powder factor are almost the same. The advantage of the proposed model over the Kuz-Ram model is the specific explosive energy, since this parameter includes the powder factor and the weight strength of an explosive. In addition, a sensitivity analysis was conducted based on the artificial neural network. The results showed that the burden and the specific explosive energy were the most effective parameters in the proposed model.

This work assessed the curve fitting ability of Rosin-Rammler and Swebrec functions and the comparison of their fitting parameters with ROCK strength properties. The work aimed to show if there exists a relationship between the function’ s distribution parameters and ROCK strength properties. The ROCK strengths properties were determined in accordance with International Society of ROCK Mechanics standards. The two functions were used to reproduce sieving curves of different ROCKs fragmented on a laboratory scale using electric detonators. The Swebrec function reproduces the sieving curves better than Rosin-Rammler. The Rosin-Rammler curve fitting performs creditably with well-fragmented ROCKs of poor grading or uniformly sorted fragments. The Rosin-Rammler curve fitted better to Class II ROCKs than the Class I ROCKs. The Rosin-Rammler parameters are shown to be interdependent while only factor ‘ a’ and exponent ‘ c’ parameters of the Swebrec function are mutually dependent. The undulating exponent ‘ b’ of Swebrec is related to the uniformity index, ‘ n’ and characteristic size, ‘ Xc’ of Rosin-Rammler. By comparison, the parameters of the two functions show correlations with ROCK strength properties (BTS, UCS, E, and v). The uniformity index, ‘ n’ is related to ROCK properties included in this study while the Swebrec ‘ c’ parameters did not show any relationship with ROCK properties. The ‘ Xc’ parameter of Rosin-Rammler is related to UCS, E and v. The ‘ a’ and ‘ b’ parameters of the Swebrec function are related to BTS, UCS, and v and BTS UCS and E respectively. In all cases, the correlation coefficients are greater than 0. 6 and can be fitted by the power form function.

One of the key outcomes of blasting in mines is ROCK FRAGMENTATION that profoundly affects downstream expenses. In fact, size prediction of ROCK FRAGMENTATION is the first step towards the optimization of blasting design parameters. This paper attempts to present a model to predict ROCK FRAGMENTATION using Mutual Information (MI) in Meydook copper mine. Ten parameters are considered to influence FRAGMENTATION. On the other hand, ROCK Engineering System (RES) is employed in order to compare different models. To validate the results, six blasting scenarios were selected and the results were compared. The coefficient of correlation (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were used to assess the performance of presented models. The R2, RMSE and MAE values for 30 blasting cycles were calculated to be 0.81, 10.7, and 9.02 for MI model, and 0.75, 11.87, and 9.61 for RES, implying the better capability of MI model to predict FRAGMENTATION.

ROCK FRAGMENTATION is one of the desired results of ROCK blasting. Therefore, controlling and predicting it has direct effects on operational costs of mining. There are different ways to predict the size distribution of fragmented ROCKs. Mathematical relations have been widely used in these predictions. Among three proposed mathematical relations, one was selected in this study to estimate the size distribution curve of blasting. The accuracy of its estimates was compared to that of the RR (Rosin-Rammler), SveDeFo (The Swedish Detonic Research Foundation), TCM (Two-Component Model), CZM (Crushed Zone Model), and KCO (Kuznetsov – Cunningham-Ouchterlony) relationships. The comparison included assessing the accuracy (Regression, R) and precision (Mean Square Error, MSE) of the best possible fit between the mathematical relations to estimate the cumulative distribution of fragmented ROCKs that result from ROCK blasting in open pit mines (Miduk Copper Mine, Sirjan Gol-e-Gohar, and Chadormalu Iron Mines) using image analysis techniques. The results showed that the power hyperbolic tangent function can estimate the size distribution of hard ROCK FRAGMENTATION with more uniformity in fine and coarse-grained sizes (unlike soft and altered ROCKs with the non-uniform distribution in these regions), more accurately and with higher precision. In addition, unlike the KCO, the absence of a second turning point for the largest block dimensions (Xm) in the proposed function, can guarantee the accuracy of estimations related to any range of inputs. Finally, due to the ability of the proposed relation to accurately estimate the ROCK FRAGMENTATION distribution caused by blasting, the uniformity coefficient required for the relation was provided by a linear combination of the geometric blasting parameters, where R=0. 855 and MSE=0. 0037.