Experimental Investigation of Cuttability Improvement for Hard Rock Fragmentation Using Conical Cutter

Wang, Shaofeng; Sun, Licheng; Li, Xibing; Wang, Shanyong; Du, Kun; Li, Xiang; Fan, Feng

doi:10.1061/(asce)gm.1943-5622.0001899

Cited by 44 publications

(23 citation statements)

References 25 publications

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“…With the depth of underground engineering increasing, the geo-stress levels are also increasing rapidly [31][32][33][34]. The geo-stress is an unignored factor affecting the occurrence of rockbursts, especially for non-coal rock engineering.…”

Section: Geo-stress Factorsmentioning

confidence: 99%

Differences of Mechanical Parameters and Rockburst Tendency Indices between Coal and Non-Coal Rocks and Modified Rockburst Tendency Classification Criteria for Non-Coal Rocks

Sun

Yang

et al. 2021

Applied Sciences

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Rockbursts represent hazardous dynamic disasters for underground coal mines and other underground rock engineering projects. Some bursting liability indices are put forward and applied to identify the likelihood of rock burst occurrence. The classification criteria of the bursting liability indices are proved to be reasonable for coals, but they are still immature for non-coal rocks. Thus, it is uncertain that it is reasonable to use the classification criteria of coal for evaluating the bursting liability of non-coal rocks. Hence, in this study, a large amount of data, such as the basic mechanical parameters, i.e., Poisson’s ratio μ, elastic modulus E, uniaxial compressive strength σc, and uniaxial tensile strength σt, and the bursting liability indices, i.e., elastic strain energy index WET, bursting energy index Wcf, dynamic fracture duration time DT, and brittleness index B, of different coals and non-coal rocks were collected in China. Then, the differences of mechanical parameters and rockburst tendency indices between coal and non-coal rocks were studied systematically, and apart from the Poisson’s ratio μ, the other three basic mechanical parameters of coal and non-coal rocks have great differences in data distribution and concentration scope, which proved that the non-coal rocks cannot share the same index system and classification criteria of coals. In addition, the evaluation results of a single index for rock bursting liability of rocks were directly compared in pairs, and the inconsistency rate for coals is about 42–68%. It is necessary to build a comprehensive evaluation method to evaluate the bursting liability of rocks. At last, the modified rockburst tendency classification criteria for non-coal rocks were put forward. It is reasonable to use the classification criteria of the WET and Wcf to classify the bursting liability of non-coal rocks, while it is unreasonable to use that of the DT and σc. It has been concluded that the index B are more suitable for non-coal rocks, and a new index, named strength decrease rate (SDR), was proposed to determine the bursting liability, which is the ratio of uniaxial compressive strength σc to duration of dynamic fracture DT.

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Section: Geo-stress Factorsmentioning

confidence: 99%

Differences of Mechanical Parameters and Rockburst Tendency Indices between Coal and Non-Coal Rocks and Modified Rockburst Tendency Classification Criteria for Non-Coal Rocks

Sun

Yang

et al. 2021

Applied Sciences

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“…The above mentioned research studies concentrated on the estimation of macroelastic modulus. Fracture toughness, reflecting the resistance for crack initiation and propagation [27,28], is another crucial parameter for rock fragmentation and hydrofracturing [29][30][31][32]. At the microscopic level, the fracture toughness of indents can be determined by the crack length method [33] or energy method [26,[34][35][36] based on nanoindentation results.…”

Section: Introductionmentioning

confidence: 99%

Estimating Macrofracture Toughness of Sandstone Based on Nanoindentation

et al. 2021

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An upscaling method for estimating macrofracture toughness by nanoindentation results was proposed in this study. Grid nanoindentation tests were conducted on sandstone samples to obtain micromechanical properties of indents, including elastic modulus, hardness, and stiffness. Multifactor cluster analysis was then carried out to categorize the sandstone into five mechanical phases. Finally, the macrofracture toughness was predicted by using the macroelastic modulus of the sample and the critical energy release rate of the weakest phase. To verify this method, the upscaling result was compared with the macrofracture toughness measured by the notched semicircular bending (NSCB) test. The discrepancy in the macrofracture toughness from our method and the NSCB test was 8.8%, which was acceptable. Also, it is proved that our method can provide more accurate upscaling results compared to other methods.

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“…The optimal threshold value for each image impeded the creation of an automatic mapping tool [14]. The manual, automatic, and semiautomatic methods had been used to characterize discontinuity traces using photographs of rock exposures, and the case studies on actual rock images were taken to conduct comparative analyses to quantify the accuracy of fracture detection and characterization [11,14] Fragmentation is an important operation in order to control and minimize the loading, hauling, crushing, classification, and processing costs in mining and minerals engineering [15][16][17][18]. Many methods based on photo-analysis were proposed to estimate the size distribution of rock fragments [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Digital Image Processing Method for Characterization of Fractures, Fragments, and Particles of Soil/Rock-Like Materials

Zhou

et al. 2021

Mathematics

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Natural soil and rock materials and the associated artificial materials have cracks, fractures, or contacts and possibly produce rock fragments or particles during geological, environmental, and stress conditions. Based on color gradient distribution, a digital image processing method was proposed to automatically recognize the outlines of fractures, fragments, and particles. Then, the fracture network, block size distribution, and particle size distribution were quantitatively characterized by calculating the fractal dimension and equivalent diameter distribution curve. The proposed approach includes the following steps: production of an image matrix; calculation of the gradient magnitude matrix; recognition of the outlines of fractures, fragments, or particles; and characterization of the distribution of fractures, fragments, or particles. Case studies show that the fractal dimensions of cracks in the dry mud layer, ceramic panel, and natural rock mass are 1.4332, 1.3642, and 1.5991, respectively. The equivalent diameters of fragments of red sandstone, granite, and marble produced in quasi-static compression failures are mainly distributed in the ranges of 20–40 mm, 25–65 mm, and 10–35 mm, respectively. The fractal dimension of contacts between mineral particles and the distribution of the equivalent diameters of particles in rock are 1.6381 and 0.8–3.6 mm, respectively. The proposed approach provides a computerized method to characterize quantitatively and automatically the structure characteristics of soil/rock or soil/rock-like materials. By this approach, the remote sensing for characterization can be achieved.

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Experimental Investigation of Cuttability Improvement for Hard Rock Fragmentation Using Conical Cutter

Cited by 44 publications

References 25 publications

Differences of Mechanical Parameters and Rockburst Tendency Indices between Coal and Non-Coal Rocks and Modified Rockburst Tendency Classification Criteria for Non-Coal Rocks

Differences of Mechanical Parameters and Rockburst Tendency Indices between Coal and Non-Coal Rocks and Modified Rockburst Tendency Classification Criteria for Non-Coal Rocks

Estimating Macrofracture Toughness of Sandstone Based on Nanoindentation

Digital Image Processing Method for Characterization of Fractures, Fragments, and Particles of Soil/Rock-Like Materials

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