• Geomechanics and Engineering
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• 제9권3호
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• pp.329-344
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• 2015

Cratering tests in rock are generally carried out to identify its fragmentation characteristics. The test results can be used to estimate the minimum amount of explosives required for the target volume of rock fragmentation. However, it is not easy to perform this type of test due to its high cost and difficulty in securing the test site with the same ground conditions as the site where blasting is to be performed. Consequently, this study investigates the characteristics of rock fragmentation by using the hydrocode in the platform of AUTODYN. The effectiveness of the numerical models adopted are validated against several cratering test results available in the literature, and the effects of rock mass classification and ground formation on crater size are examined. The numerical analysis shows that the dimension of a crater is increased with a decrease in rock quality, and the formation of a crater is highly dependent on a rock of lowest quality in the case of mixed ground. It is expected that the results of the present study can also be applied to the estimation of the level and extent of the damage induced by blasting in concrete structures.

• Explosives and Blasting
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• 제36권4호
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• pp.9-15
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• 2018

Since the rock fragmentation by blasting can affect the subsequent processes including loading, hauling and secondary crushing, its control is essential for the assessment of blasting efficiency as well as production cost. In this study, we were analyzed the rock fragmentation by the direction of artificial joint. The underground blasting experiments were performed after forming the vertical and horizontal artificial joints. The blast fragmentation was conducted by the split-desktop which is a 2D image processing program. As a result, it was found that the horizontal artificial joint was evaluated to have lower overall the size of muck pile than the vertical artificial joint and the distribution of the size of muck pile was varied. It is possible that the direction of artificial joint could suppress the occur of oversize muck pile and control to a certain size or less.

• Tunnel and Underground Space
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• 제23권1호
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• pp.42-53
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• 2013

The percussion rate and spacing of the button of drill bit are very important in maximizing the drilling efficiency. Therefore, a series of percussion tests using Hopkinson bar system was carried out to assess the fragmentation performance against the beat rate and spacing of a drill bit. First, single percussion test complemented with numerical simulation was performed to analyze rock fragmentation phenomenon and to describe the fragmentation process. Next, multiple percussion test that repetitively strike the rock sample moving at predetermined rate was carried out to predict drilling efficiency against the button spacing. After the tests, the fragmented volume of the rock was measured by laser scanner and the drilling performance was analyzed using the calculated percussive energy and measured negative volume. Based on the results, the single impact performance of drill bit with 102 mm diameter was predicted.

• Proceedings of the Korean Geotechical Society Conference
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• 한국지반공학회 2001년도 봄 학술발표회 논문집
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• pp.129-136
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• 2001

Blasting method is used most engineering works for rock excavation. Blasting method is done much to upgrade of operation efficiency, contraction of construction period than other method. But blasting method happens damage by blasting vibration, nose and scattering. Therefore this study examined about effect, characteristic and application of Plasma method. To confirm effect measured vibration, noise and frequency, and analyzed data compare with general blasting.

• Structural Engineering and Mechanics
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• 제69권5호
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• pp.537-545
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• 2019

Stress analysis of bottom-hole rock has to be considered with much care to further understand rock fragmentation mechanism and high penetration rate. This original study establishes a fully coupled simulation model and explores the effects of overburden pressure, horizontal in-situ stresses, drilling mud pressure, pore pressure and temperature on the stress distribution in bottom-hole rock. The research finds that in air drilling, as the well depth increases, the more easily the bottom-hole rock is to be broken. Moreover, the mud pressure has a great effect on the bottom-hole rock. The bigger the mud pressure is, the more difficult to break the bottom-hole rock is. Furthermore, the maximum principal stress of the bottom-hole increases as the mud pressure, well depth and temperature difference increase. The bottom-hole rock can be divided into three main regions according to the stress state, namely a) three directions tensile area, b) two directions compression areas and c) three directions compression area, which are classified as a) easy, b) normal and c) hard, respectively, for the corresponding fragmentation degree of difficulty. The main contribution of this paper is that it presents for the first time a thorough study of the effect of related factors, including stress distribution and temperature, on the bottom-hole rock fracture rather than the well wall, using a thermo-poroelastoplasticity model.

• 지반과기술
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• 제3권3호
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• pp.15-22
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• 2006

The optimum blasting pattern to excavate a quarry efficiently and economically can be determined based on the minimum production cost, which is generally estimated according to rock fragmentation. Therefore, it is a critical problem to predict fragment size distribution of blasted rocks over an entire quarry. By comparing various prediction models, it can be ascertained that the result obtained from Kuz-Ram model relatively coincides with that of field measurements. Kuz-Ram model uses the concept of rock factor to signify conditions of rock mass such as block size, rock jointing, strength and others. For the evaluation of total production cost, it is imperative to estimate 3-D spatial distribution of rock factor for the entire quarry. In this study, a sequential indicator simulation technique is adopted for estimation of spatial distribution of rock factor due to its higher reproducibility of spatial variability and distribution models than Kriging methods. Further, this can reduce the uncertainty of predictor using distribution information of sample data. The entire quarry is classified into three types of rock mass and optimum blasting pattern is proposed for each type based on 3-D spatial distribution of rock factor. In addition, plane maps of rock factor distribution for each ground level are provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

• Journal of Korean Tunnelling and Underground Space Association
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• 제3권1호
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• pp.3-9
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• 2001

The investigation of the fragmentation of blasted rocks is particularly important because it is a measure of the blast efficiency. The degree of fragmentation has a major effect on the efficiency of the loading and crushing operations. Getting such an information on the large pile of blasted rock is not an easy operation. This paper presents the results of case study to evaluate the performance of two types of tunnel blasting: V-cut and burn cut. The digital images of muckpiles were analyzed to produce size distribution and it was compared with those of predictive equations.

• Geomechanics and Engineering
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• 재33권6호
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• pp.567-581
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• 2023

The prediction and achievement of a proper rock fragmentation size is the main challenge of blasting operations in surface mines. This is because an optimum size distribution can optimize the overall mine/plant economics. To this end, this study attempts to develop four improved artificial intelligence models to predict rock fragmentation through cascaded forward neural network (CFNN) and radial basis function neural network (RBFNN) models. In this regards, the CFNN was trained by the Levenberg-Marquardt algorithm (LMA) and Conjugate gradient backpropagation (CGP). Further, the RBFNN was optimized by the Dragonfly Algorithm (DA) and teaching-learning-based optimization (TLBO). For developing the models, the database required was collected from the Midouk copper mine, Iran. After modeling, the statistical functions were computed to check the accuracy of the models, and the root mean square errors (RMSEs) of CFNN-LMA, CFNN-CGP, RBFNN-DA, and RBFNN-TLBO were obtained as 1.0656, 1.9698, 2.2235, and 1.6216, respectively. Accordingly, CFNN-LMA, with the lowest RMSE, was determined as the model with the best prediction results among the four examined in this study.

• Explosives and Blasting
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• 제35권1호
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• pp.18-26
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• 2017

In Analysis of Fragmentation of rock blasted, The photo analysis method has been mainly used and these image acquisitions are mainly obtained by digital image from the front of the crushed rock. However, Image analysis is basically advantage of the image of planar shooting not front shooting but There is no way to take a photograph of huge plane rock slope. Thus, Unavoidably It is resolved by distorting or extending the image filmed at the front as well as adjusting it similar to its angle of plane shooting. Lately, With advancing unmanned aerial vehicle, It can simply image the fragment conditions of blasted rock of a high-definition digital image and Through it, It can acquire the most planar image to angle which accumulate cataclastic rock and also can make image analysis. In this study, It has been confirmed that tolerance value of analysis result of image filmed flatly is markedly lower than the existing front filmed image.

• Geomechanics and Engineering
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• 제34권5호
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• pp.547-559
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• 2023

We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r²). The XGBoost model had the smallest RMSE and the highest r² value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.