• Geomechanics and Engineering
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• v.17 no.6
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• pp.527-534
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• 2019

There have been developed a number of methods to assess the abrasivity of rock materials with the increased use of mechanized rock excavation. These methods range from determination of abrasive and hard mineral content using petrographic thin section analysis to weight loss or development of wear flat on a specified cutting tool. The Cerchar abrasivity index (CAI) test has been widely accepted for the assessment of rock abrasiveness. This test has been considered to provide a reliable indication of rock abrasiveness for isotropic rocks. However, a great amount of rocks in nature are anisotropic. Hence, viability assessment of Cerchar abrasivity test for the anisotropic rocks is investigated in this research. The relationship between CAI value and quartz content for the isotropic rocks is well known in literature. However, a correlation between EQ, F-Schimazek value, Rock Abrasivity Index (RAI) and CAI of anisotropic rocks such as phyllite was done first time in literature with this research. The results obtained with this research show F-Schimazek values and RAI values should be considered when determination of the abrasivity of anisotropic rocks instead of just using Cerchar scratch test.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.219-228
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• 2022

The most widely used parameter to represent rock abrasiveness is the Cerchar abrasivity index (CAI). The CAI value can be applied to predict wear in TBM cutters. It has been extensively demonstrated that the CAI is affected significantly by cementation degree, strength, and amount of abrasive minerals, i.e., the quartz content or equivalent quartz content in rocks. The relationship between the properties of rocks and the CAI is investigated in this study. A database comprising 223 observations that includes rock types, uniaxial compressive strengths, Brazilian tensile strengths, equivalent quartz contents, quartz contents, brittleness indices, and CAIs is constructed. A linear model is developed by selecting independent variables while considering multicollinearity after performing multiple regression analyses. Machine learning-based regression methods including support vector regression, regression tree regression, k-nearest neighbors regression, random forest regression, and artificial neural network regression are used in addition to multiple linear regression. The results of the random forest regression model show that it yields the best prediction performance.

• Tunnel and Underground Space
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• v.22 no.4
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• pp.284-295
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• 2012

Abrasiveness of rock plays an important role on the wear of rock cutting tools. In this study, Cerchar abrasiveness tests were carried out to assess the abrasiveness of 19 different Korean rocks. Cerchar abrasiveness test is widely used to assess the abrasiveness of rock because of its simplicity and inexpensive cost. This study examines the relationship between Cerchar Abrasiveness Index (CAI) and mechanical properties (uniaxial compressive strength, Brazilian tensile strength, Young's modulus, Poisson's ratio, porosity, shore hardness of rock), and the effect of quartz content, equivalent quartz content, which was obtained from XRD analysis. As a result of test, CAI was more influenced by petrographical properties than by the bonding strength of the matrix material of rock. CAI prediction model which consisted of UCS and EQC was proposed. CAI decreased linearly with the hardness of the steel pin. Numerical analysis was performed using Autodyn-3D for simulating the Cerchar abrasiveness test. In the simulations, most of pin wear occurred during the initial scratching distance, and CAI increased with the increase of normal loading.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.882-889
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• 2004

Wetness index obtained from topography data of Woogak Mountain was compared with chemical alteration index(CAI), clay minerall contents of rock, and magnetic susceptibility changes of outcrops, and they show a close interrelationship. It is shown that the wetness index can be used as a quantitative indicator of the weathering degree of rocks. Moreover, wetness index simulate quantitatively the hydrologic condition of the local area. Therefore, it is anticipated that wetness index can be used as the data that calculate the weathering speed of rock and weathering grade in the study of weathering sensitivity of rock.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.6
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• pp.533-542
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• 2014

In this study TBM disc cutter prediction models including Gehring, CSM and NTNU models were investigated and the characteristics of the models were examined. The influence of penetration, uniaxial compressive strength and abrasiveness index on the models was analyzed. The life of disc cutter linearly increases with penetration per revolution and decreases with increasing uniaxial compressive strength of rocks. As the abrasiveness index, CAI, increases, the life of disc cutter in Gehring and CSM model decreases. On the contrary, the life of disc cutter life in NTNU model decreases with increasing CLI. Also, comparisons of predicted disc life were made between models using actual job site data.

• The Journal of the Petrological Society of Korea
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• v.23 no.3
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• pp.273-277
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• 2014

This paper presents a brief historical review of various attempts to estimate the age of the Earth, and reappraises the study of Patterson (1956) which revealed for the first time that the age of the Earth is $4550{\pm}70Ma$ by measuring Pb isotope ratios of several meteorites and a marine sediment. The standard model for the planetary formation of early solar system is: formation of solid particles condensed from the cooling of hot nebular gas -> formation of planet-sized bodies by accretion of those solid particles. The Moon is supposed to have formed from the accretion of the relicts produced by the collision of proto-Earth with Mars-sized body. It is not easy to pinpoint the age of the Earth, considering the series of events related to the formation of the Earth. So, I propose that the collision age as that of the Earth, since the present status of the Earth is thought to be the direct product of the collision. According to the previous studies, the collision age can be broadly constrained between the age ($4567.30{\pm}0.16Ma$) of the earliest condensates (CAI, calcium-aluminum rich inclusion) of the nebula gas, i.e., the age of the solar system, and the oldest age ($4,456{\pm}40Ma$) among rocks and minerals of the Earth and the Moon. We need more precise estimation of the collision age, since it is important in estimating time scale for the formation of planet-size body and in revealing thermal evolution of magma oceans of the Earth and the Moon presumably developed right after the collision.