Development of Predictive Models for the Specific Energy of Circular Diamond Sawblades in the Sawing of Granitic Rocks

This paper presents an experimental study on the sawing of granitic rocks by circular diamond sawblades. The influence of the operating variables and rock properties on the specific energy were initially investigated and analyzed. To determine the most significant operating variables and rock properties influencing the specific energy, statistical analyses were then employed and the models were built for the estimation of specific energy depending on the operating variables and the rock properties. Moreover, the derived models were validated through statistical tests such as the determination coefficient, t-test, F-test, and residuals. The results indicated that the specific energy decreased with the decreasing of peripheral speed and the increasing of traverse speed, cutting depth, and flow rate of cooling fluid, respectively. It was concluded that, rather than the physico-mechanical properties, the mineralogical properties were the dominant rock properties affecting the specific energy. Additionally, the peripheral speed was statistically determined as the most significant operating variable affecting the specific energy. The peripheral speed was followed by the cutting depth, traverse speed, and flow rate of cooling fluid with respect to their level of significance on the specific energy. Furthermore, the model results revealed that the developed models have high potentials as a guidance for practical applications.     

Prediction of the Cut Depth of Granitic Rocks Machined by Abrasive Waterjet (AWJ)

In this paper, an experimental study on the cut depth, which is an important cutting performance indicator in the abrasive waterjet (AWJ) cutting of rock, was presented. Taguchi experimental design of an orthogonal array was employed to conduct the experiments. A variety of nine types of granitic rocks were used in the cutting experiments. The experimental data were used to assess the influence of AWJ operating variables on the cut depth. Using regression analysis, models for prediction of the cut depth from the operating variables and rock properties in AWJ machining of granitic rocks were then developed and verified. The results indicated that the cut depths decreased with increasing traverse speed and decreasing abrasive size. On the other hand, increase of the abrasive mass flow rate and water pressure led to increases in the cut depths. Additionally, it was observed that the standoff distance had no discernible effects on the cut depths. Furthermore, from the statistical analysis, it was found that the predictive models developed for the rock types had potential for practical applications. Verification of the models for using them as a practical guideline revealed a high applicability of the models within the experimental range used.     

The Effects of Operational Parameters on a Mono-wire Cutting System: Efficiency in Marble Processing

Mono-wire block cutting machines that cut with a diamond wire can be used for squaring natural stone blocks and the slab-cutting process. The efficient use of these machines reduces operating costs by ensuring less diamond wire wear and longer wire life at high speeds. The high investment costs of these machines will lead to their efficient use and reduce production costs by increasing plant efficiency. Therefore, there is a need to investigate the cutting performance parameters of mono-wire cutting machines in terms of rock properties and operating parameters. This study aims to investigate the effects of the wire rotational speed (peripheral speed) and wire descending speed (cutting speed), which are the operating parameters of a mono-wire cutting machine, on unit wear and unit energy, which are the performance parameters in mono-wire cutting. By using the obtained results, cuttability charts for each natural stone were created on the basis of unit wear and unit energy values, cutting optimizations were performed, and the relationships between some physical and mechanical properties of rocks and the optimum cutting parameters obtained as a result of the optimization were investigated.     

An investigation on the kerf width in abrasive waterjet cutting of granitic rocks

This paper presents an experimental and statistical study on the kerf width, used instead of the width of the cut in abrasive waterjet (AWJ) cutting. Pre-dimensioned granitic rocks were sampled for the experimentations designed by using Taguchi orthogonal arrays. The effects of the AWJ operating variables on the kerf width were studied and the rock properties were correlated with the kerf widths. Additionally, predictive models for the kerf widths were developed using multi-variable regression analysis and the developed models were verified through some statistical tests. The results demonstrated that the standoff distance and the traverse speed have significant effects on the kerf widths. The results also showed that water absorption, unit weight, microhardness, the maximum grain size of rock-forming minerals, and mean grain size of the rock have significant correlations with the kerf widths of the tested rocks. Furthermore, the modeling results revealed that the predictive models derived from rock properties, can be successfully used as a practical guideline.     

Influence of physico-mechanical properties of Indian dimension stones on cutting rate of diamond wire saw

Cutting performance of diamond wire saw is a key factor influencing mine planning, production scheduling, and equipment selection for dimension stone quarries. It is normally measured in terms of cutting rate. Rock samples collected from various granite and marble quarries in India were tested in laboratory to determine their physico-mechanical properties. Cutting rate of diamond wire saw was measured in the field studies during the actual cutting process in quarries. Using these laboratory determined properties and the cutting rate, a multiple linear regression model has been developed to predict the cutting rate of diamond wire saw. Physico-mechanical properties of rocks determined in laboratory are used as independent variables and cutting rate as predictor variable in the regression model. The study indicates that the cutting rate increases with a decrease in most of the hardness and strength parameters of rock. The final model is tested for its goodness of fit indicating a significant linear relation between cutting rate and physico-mechanical properties, namely tensile strength, slake durability index, and Cerchar hardness index with regression coefficient of 94%. The resulting model can be used suitably for different types of hard to medium hard and soft dimension stones. The generalized model for estimating the cutting rate becomes a handy tool for mining engineers to work out operating efficiency, expenses, planning etc. of the dimension stone block cutting.     

Predicting the production rate of diamond wire saw using statistical analysis

Performance prediction of diamond wire saws is important in the cost estimation and the planning of the stone quarries. An accurate estimation of sawability helps to make the planning of the rock cutting projects more efficient. In this paper, the performance prediction of diamond wire saws in cutting carbonate rocks was studied on 14 different carbonate rocks in stone quarries located in Iran. Rock samples were collected from the quarries for laboratory tests. Uniaxial compressive strength, Brazilian tensile strength, Schmidt hammer value, and Los Angeles abrasion were determined in the laboratory. Performance prediction was evaluated using simple and multiple regression analyses. Finally, a new model was proposed for predicting the production rate of diamond wire saw. It was concluded that the production rate of carbonate rock using diamond wire saw can reliably be estimated using the developed model.     

盘形滚刀破岩过程的数值研究

为了研究全断面岩石掘进机盘形滚刀的破岩过程以及盘形滚刀的结构参数（刀刃宽、刀刃角）对滚刀破岩特性的影响,利用离散元方法建立岩石与盘形滚刀的二维数值模型,研究了滚刀侵入岩石过程中贯入度、切削力以及裂纹数三者的关系,在此基础上通过仿真得到滚刀结构参数与岩石破碎特性的规律。研究结果表明：裂纹的扩展与滚刀受到的切削力密切相关;破岩过程中切削力先增大后减小的循环模式,证实了岩石跃进破碎特性。在盘形滚刀作用下,岩石中的应力是向下、向四周无限扩展的对称的应力泡。滚刀刀刃作用区域,应力值最高,随着滚刀贯入度增加,最大应力减小;远离滚刀刀刃区域,应力呈应力泡形式逐层降低至0。选择滚刀刀刃宽在10～15 mm之间,既避免滚刀受到的推力过大,又能提高滚刀的破岩效率;岩石破碎以滚刀刀刃下方向下发展裂纹的扩展为主,刀刃角在10°～20°之间,既能减少滚刀的磨损又能提高破岩效率。     

楔形刀具侵入岩石损伤破坏影响因素的理论分析及数值模拟

通过空腔膨胀理论研究楔形刀具几何参数（刃角）、岩石力学参数（抗压强度、泊松比）对刀具与岩石接触面下岩石弹-塑性交界面半径的影响。结果表明：刀具与岩石接触宽度一定时,刃角越小,岩体的损伤区域越大,从而导致弹-塑性交界面半径增大。在其他因素不变的前提下,岩石泊松比增大或者抗压强度增加都导致弹-塑性交界面半径减小。采用参数敏感性分析方法对3种影响因素的敏感性进行了分析,在接触宽度一定的条件下,刃角的大小对弹-塑性交界半径的影响最大。采用ABAQUS软件建立刀具侵入岩石的数值模型,研究表明,刃角的变化对文中定义的岩体内最大拉应力点空间位置以及最小梯度方向有着显著影响。     

Textural characterisation of rocks

Textural characteristics are a major factor in determining the mechanical behaviour of rocks and in the prediction of performance of rock cutting and drilling equipment. The principal textural characteristics of rocks are grain size, grain shape, grain orientation, relative proportion of grains and matrix material which were herein quantitatively measured using a modern image analysis system. These features resulted in a texture coefficient represented by a single number for each rock specimen. In this study a range of both textural and mechanical data for a range of rock types are given with some of the textural determination methodology. Correlation between textural and physical properties are also highlighted. The results of drilling tests using polycrystalline diamond compact (pin and hybrid) and impregnated diamond core bits in the rocks are presented which demonstrate the influence of rock texture on drillability. The rock texture can be used as a predictive factor for assessing the drillability and cuttability, mechanical and wear performance of rocks.     

Continuous Monitoring of Pin Tip Wear and Penetration into Rock Surface Using a New Cerchar Abrasivity Testing Device

Evaluation of rock abrasivity is important when utilizing mechanized excavation in various mining and civil projects in hard rock. This is due to the need for proper selection of the rock cutting tools, estimation of the tool wear, machine downtime for cutter change, and costs. The Cerchar Abrasion Index (CAI) test is one of the simplest and most widely used methods for evaluating rock abrasivity. In this study, a new device for the determination of frictional forces and depth of pin penetration into the rock surface during a Cerchar test is discussed. The measured parameters were used to develop an analytical model for calculation of the size of the wear flat (and hence a continuous measure of CAI as the pin moves over the sample) and pin tip penetration into the rock during the test. Based on this model, continuous curves of CAI changes and pin tip penetration into the rock were plotted. Results of the model were used for introduction of a new parameter describing rock–pin interaction and classification of rock abrasion.     

The Derivation and Validation of TBM Disc Cutter Wear Prediction Model

The problem of disc cutter wear is inevitable when shield or TBM excavating hard rock for a long distance, thus, the study of disc cutter wear model has an important project value on predicting its service life and replacement opportunity. It is put forward by analyzing disc cutter wear mechanism that the main wear form is abrasive wear, which is based on plastic removal mechanism. Then, disc cutter wear rate and linear wear rate prediction models are obtained by approximate calculation and mathematical deduction, which are based on Rabinowicz equation and CSM model. At last, the two models are verified through field test data from three projects, and the results show that the prediction model can accurately reflect the real wear situation of disc cutter.     

Numerical Studies on Chip Formation in Drag-Pick Cutting of Rocks

A two dimensional non-linear finite element simulation model has been developed using a mathematical model for progressive rock failure for understanding the mode and sequence of rock failure under a drag pick cutter. Rock cutting simulation has also been done using linear elastic modeling using local stability factor contouring. It has been observed from the simulation results that during negative rake angle cutting the chipping occurs by shear failure of the elements. Whereas, in positive rake angle cutting, some elements were observed to fail in shear and some under tension. The predicted peak cutting force using the developed models was found to be up to 25% higher than the experimental values. The effect of input parameters such as rake angle, flank wear, depth of cut and rock properties on the predicted peak cutting force has been studied, verified from earlier experimental studies and compared with some earlier proposed theories on rock cutting. The elastic stress analysis model based on the stability factor contouring method has also been found to be an effective tool to bracket the expected peak cutting force for a given operational and rock parameters but failed to simulate the effect of pick geometry (rake angle) correctly. The non-linear simulation model using progressive rock element failure is superior to elastic linear stress analysis model by simulating the correct trends for all the rock and machining parameters.     

A Comparative Analysis of Cognitive Systems for the Prediction of Drillability of Rocks and Wear Factor

This paper demonstrates the applicability of cognitive systems or neural networks in predicting the drillibality of rocks and wear factor using engineering properties of rocks. Drillability of rocks is a useful guide for evaluating the suitability of drills for different ground operations. The wear factor of different materials subsequently helps in the selection of proper drills for different drilling operations. Different rocks were tested for Protodyakonov index, impact strength index, shore hardness number, Schmidt hammer number, drillability and micro bit chisels for wear factor. The data obtained from the tests were used to train and test the neural network. Results from the analysis demonstrate that cognitive systems are an effective tool in the prediction and suitability of drilling operations. Application of these predictive models can be a useful tool to obtain the value of these important parameters, they can save time and help to avoid the tedious process of instrumentation.     

Discrete element modelling of rock cutting: from ductile to brittle transition

It is well accepted that there is a transition of failure mode from ductile to brittle with increasing depth of cut during rock cutting process. Rock failure modes affect cutting efficiency, and knowledge of the failure transition is essential to the determination of optimum cutting parameters. The critical transition depth can be linked with rock properties. In this study, an attempt was made to model rock cutting process and to check the dependence of the critical failure mode transition depth on the brittleness of rock. For this purpose, dimensional analysis was first performed to establish the correlations between rock macro‐properties and micro‐parameters for discrete element simulations. Following the specimen calibration procedure, two types of synthetic rocks having approximately the same uniaxial compressive strength were generated as the synthetic specimens for simulating the rock cutting process. The first specimen was created using conventional model construction method with identical bond strengths between particles, giving rise to undesirably high indirect tensile strength. The second specimen was created using a proposed clustering algorithm such that the ratio between the tensile and compressive strength matches reasonably well with that of real rocks. The results of rock cutting simulations demonstrate that failure mode transition took place in both models, but for the clustered model the transition emerged at a shallower cutting depth. A further exploration was made to derive the critical depth for this transition based on the simulations performed on the clustered models. The derived relationship indicates that the critical transition depth decreases as strength ratio or brittleness of the rock increases. This provides a very useful tool for predicting the critical depth which can be used to help cutting tool design and cutting parameter optimisations. Copyright © 2015 John Wiley & Sons, Ltd.     

Effect of cutting depth and line spacing on the cuttability behavior of sandstones by conical picks

Various types of conical picks in different shapes are produced and widely employed on mechanical excavators. Depending on the mechanical and abrasivity properties of rocks, appropriate shape of pick is selected. In order to obtain maximum efficiency from the pick during excavation, the interaction between the pick and rock and the cutting mechanism play very important role. In this context, linear cutting tests were conducted by using a conical pick at the cutting depths between 3 and 18 mm and also at the various line spacings on sandstones exhibiting different mechanical properties. The results indicated that cutting depth and line spacing have significant influences on the tool forces acting on the pick, the ratio of normal to cutting force, and the specific energy. Accordingly, strong correlations and empirical models were developed. In conclusion, the empirical models proposed for estimating the forces and specific energy would be used for producing the conical bits and also designing the cutter heads of mechanical excavators on soft and medium-hard strength sandstones.     

Rock mass excavatability estimation using artificial neural network

One important decision in design of surface mine is the selection of mine equipment and plant. Demand for mechanical excavation is growing in mining industry because of its high productivity and excavation in large scale with lower costs. Several models have been developed over the years to evaluate the ease of excavation and machine performance against rock mass properties. Due to complexity of excavation process and large number of effective parameters, approaches made for this purpose are essentially empirical. There are many uncertainties in results of these models. An attempt is made in this paper to revise the exisiting models. Neural network models for estimation of rock mass excavatability and production rate of VASM-2D excavating machine at Limestone quarry in Retznei, Austria, is presented. Input parameters of this model are Uniaxial compressive strength, tensile strength and discontinuities spacing of rocks. Output is the specific excavation rate per power consumption (bcm/Kwh) as the productivity indicator. Average of deviation between actual data and results estimated by neural network model was only 15% which is in an acceptable range.     

Artificial neural networks and nonlinear regression techniques to assess the influence of slake durability cycles on the prediction of uniaxial compressive strength and modulus of elasticity for carbonate rocks

Understanding rock material characterizations and solving relevant problems are quite difficult tasks because of their complex behavior, which sometimes cannot be identified without intelligent, numerical, and analytical approaches. Because of that, some prediction techniques, like artificial neural networks (ANN) and nonlinear regression techniques, can be utilized to solve those problems. The purpose of this study is to examine the effects of the cycling integer of slake durability index test on intact rock behavior and estimate some rock properties, such as uniaxial compressive strength (UCS) and modulus of elasticity (E) from known rock index parameters using ANN and various regression techniques. Further, new performance index (PI) and degree of consistency (Cd) are introduced to examine the accuracy of generated models. For these purposes, intact rock dataset is established by performing rock tests including uniaxial compressive strength, modulus of elasticity, Schmidt hammer, effective porosity, dry unit weight, p‐wave velocity, and slake durability index tests on selected carbonate rocks. Afterward, the models are developed using ANN and nonlinear regression techniques. The concluding remark given is that four‐cycle slake durability index (I_d4) provides more accurate results to evaluate material characterization of carbonate rocks, and it is one of the reliable input variables to estimate UCS and E of carbonate rocks; introduced performance indices, both PI and Cd, may be accepted as good indicators to assess the accuracy of the complex models, and further, the ANN models have more prediction capability than the regression techniques to estimate relevant rock properties. Copyright © 2011 John Wiley & Sons, Ltd.     

Study of Dominant Factors Affecting Cerchar Abrasivity Index

The Cerchar abrasion index is commonly used to represent rock abrasion for estimation of bit life and wear in various mining and tunneling applications. Although the test is simple and fast, there are some discrepancies in the test results related to the equipment used, condition of the rock surface, operator skills, and procedures used in conducting and measuring the wear surface. This paper focuses on the background of the test and examines the influence of various parameters on Cerchar testing including pin hardness, surface condition of specimens, petrographical and geomechanical properties, test speed, applied load, and method of measuring wear surface. Results of Cerchar tests on a set of rock specimens performed at different laboratories are presented to examine repeatability of the tests. In addition, the preliminary results of testing with a new device as a potential alternative testing system for rock abrasivity measurement are discussed.     

Predicting the Performance of Chain Saw Machines Based on Shore Scleroscope Hardness

Shore hardness has been used to estimate several physical and mechanical properties of rocks over the last few decades. However, the number of researches correlating Shore hardness with rock cutting performance is quite limited. Also, rather limited researches have been carried out on predicting the performance of chain saw machines. This study differs from the previous investigations in the way that Shore hardness values (SH₁, SH₂, and deformation coefficient) are used to determine the field performance of chain saw machines. The measured Shore hardness values are correlated with the physical and mechanical properties of natural stone samples, cutting parameters (normal force, cutting force, and specific energy) obtained from linear cutting tests in unrelieved cutting mode, and areal net cutting rate of chain saw machines. Two empirical models developed previously are improved for the prediction of the areal net cutting rate of chain saw machines. The first model is based on a revised chain saw penetration index, which uses SH₁, machine weight, and useful arm cutting depth as predictors. The second model is based on the power consumed for only cutting the stone, arm thickness, and specific energy as a function of the deformation coefficient. While cutting force has a strong relationship with Shore hardness values, the normal force has a weak or moderate correlation. Uniaxial compressive strength, Cerchar abrasivity index, and density can also be predicted by Shore hardness values.