• Geomechanics and Engineering
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• v.21 no.4
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• pp.391-399
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• 2020

Brittleness is one of the most important properties of rock which has a major impact not only on the failure process of intact rock but also on the response of rock mass to tunneling and mining projects. Due to the lack of a universally accepted definition of rock brittleness, a wide range of methods, including direct and indirect methods, have been developed for its measurement. Measuring rock brittleness by direct methods requires special equipment which may lead to financial inconveniences and is usually unavailable in most of rock mechanic laboratories. Accordingly, this study aimed to develop a new strength-based index for predicting rock brittleness based on the obtained base form. To this end, an innovative algorithm was developed in Matlab environment. The utilized algorithm finds the optimal index based on the open access dataset including the results of punch penetration test (PPT), uniaxial compressive and Brazilian tensile strength. Validation of proposed index was checked by the coefficient of determination (R²), the root mean square error (RMSE), and also the variance for account (VAF). The results indicated that among the different brittleness indices, the suggested equation is the most accurate one, since it has the optimal R², RMSE and VAF as 0.912, 3.47 and 89.8%, respectively. It could finally be concluded that, using the proposed brittleness index, rock brittleness can be reliably predicted with a high level of accuracy.

• Tunnel and Underground Space
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• v.24 no.4
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• pp.325-333
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• 2014

Hydraulic fracturing is the key technology for production of shale gas, which is one of the major unconventional resources. Brittleness index is one of the most important mechanical properties which determine the efficiency of hydraulic fracturing. It was required that the production of shale gas increases with more brittle behavior. Confusingly, there are numerous definitions available for brittleness of rock. This paper summarizes various definitions of brittleness index, and presents correlation analysis of the brittleness indices by using the laboratory experimental results of 48 shale specimens in Korea. Generally, it shows a very weak positive correlation between the brittleness index ($B_1$) which is the ratio of uniaxial compressive strength to tensile strength and the brittleness index ($B_3$) which is calculated by using the Youngs modulus and Poisson's ratio. In addition, the role of Poissons ratio is not clear in defining brittleness indices. In conclusion, standardization of definition for brittleness index is required to apply it to hydraulic fracturing as a parameter for predicting the efficiency.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.401-411
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• 2022

To obtain the dynamic mechanical properties, fracture modes, energy and brittleness characteristics of Furong Baijiao coal rock, the dynamic impact compression tests under 0, 4, 8 and 12 MPa confining pressure were carried out using the split Hopkinson pressure bar. The results show that failure mode of coal rock in uniaxial state is axial splitting failure, while it is mainly compression-shear failure with tensile failure in triaxial state. With strain rate and confining pressure increasing, compressive strength and peak strain increase, average fragmentation increases and fractal dimension decreases. Based on energy dissipation theory, the dissipated energy density of coal rock increases gradually with growing confining pressure, but it has little correlation with strain rate. Considering progressive destruction process of coal rock, damage variable was defined as the ratio of dissipated energy density to total absorbed energy density. The maximum damage rate was obtained by deriving damage variable to reflect its maximum failure severity, then a brittleness index BD was established based on the maximum damage rate. BD value declined gradually as confining pressure and strain rate increase, indicating the decrease of brittleness and destruction degree. When confining pressure rises to 12 MPa, brittleness index and average fragmentation gradually stabilize, which shows confining pressure growing cannot cause continuous damage. Finally, integrating dynamic deformation and destruction process of coal rock and according to its final failure characteristics under different confining pressures, BD value is used to classify the brittleness into four grades.

• Tunnel and Underground Space
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• v.33 no.1
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• pp.29-41
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• 2023

The brittleness of rocks plays an important role in determining the fragmentation and failure behavior of rock. However, there is still no standard method to evaluate the brittleness of rock, and previous studies have suggested the several definitions for estimation of brittleness of rock. Even in the process of mechanical rock excavation and drilling, the brittleness of rock is considered as an important property for evaluating the excavation efficiency of mechanical excavators or boreability of rock. The previous studies have been carried out to investigate the correlation between different brittleness of rock and cutting efficiency and boreability of rock. This study introduced a method for calculating the brittleness of rock from punch penetration test, and analyzed the correlation between the brittleness of rock calculated by the uniaxial compressive and Brazilian tensile strengths and that from punch penetration test. From the results of correlation analysis, the relationship between various brittleness was confirmed, and it was found that PSI and BI₃ showed a good correlation with the strength-based brittleness index. In addition, the results indicated that B₃ and B₄ are suitable to represent the brittleness of rock in the field of mechanical rock excavation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.4
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• pp.611-634
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• 2017

In rapid urbanization, demand for utility tunnel increases more, and tunnel boring machine (TBM) has been used widely. Prediction of TBM penetration rate is important for proper estimation of construction period and cost. Although there are several methods, such as NTNU model and CSM model that require many input parameters, fundamental understanding on correlations between rock properties and TBM penetration rate is critical. In this study, we explored the brittleness indices of hard rocks according to various definitions, and the correlations between the brittleness indices and the TBM penentration rates.

• Geomechanics and Engineering
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• v.13 no.1
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• pp.63-77
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• 2017

The failure mechanism of a deep hard rock tunnel under high geostress and high geothermalactivity is extremely complex. Uniaxial compression tests of granite at different temperatures were conducted. The complete stress-strain curves, mechanical parameters and macroscopic failure types of the rock were analyzed in detail. The brittleness index, which represents the possibility of a severe brittleness hazard, is proposed in this paperby comparing the peak stress and the expansion stress. The results show that the temperature range from 20 to $60^{\circ}C$ is able to aggravate the brittle failure of hard rock based on the brittleness index. The closure of internal micro cracks by thermal stress can improve the strength of hard rock and the storage capacity of elastic strain energy. The failure mode ofthe samples changes from shear failure to tensile failure as the temperature increases. In conclusion, the brittle failure mechanism of hard rock under the action of thermal coupling is revealed, and the analysis result offers significant guidance for deep buried tunnels at high temperatures and under high geostress.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.349-356
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• 2020

Rock brittleness, which is closely related to the failure modes, plays a significant role in the design and construction of many rock engineering applications. However, the brittle-ductile failure transition is mostly ignored by the current statistical damage constitutive model, which may misestimate the failure strength and failure behaviours of intact rock. In this study, a new statistical damage model considering rock brittleness is proposed for brittle to ductile behaviour of rocks using brittleness index (BI). Firstly, the statistical constitutive damage model is reviewed and a new statistical damage model considering failure mode transition is developed by introducing rock brittleness parameter-BI. Then the corresponding damage distribution parameters, shape parameter m and scale parameter F₀, are expressed in terms of BI. The shape parameter m has a positive relationship with BI while the scale parameter F₀ depends on both BI and ε_e. Finally, the robustness and correctness of the proposed damage model is validated using a set of experimental data with various confining pressure.

• Geomechanics and Engineering
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• v.33 no.3
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• pp.279-289
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• 2023

Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σ_c) and tensile strength (σ_t) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R²), adjusted R² (Adj R²), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R² and Adj R² values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.

• Korean Journal of Food Science and Technology
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• v.24 no.3
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• pp.289-293
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• 1992

This study was carried out to investigate the quality characteristics of commercial breakfast cereals. The results showed that as water absorption index (WAI) increased, water soluble index (WSI) decreased. WSI has an effect on Bowl life, so Bowl life became longer as WSI enhanced. The size, shape and texture of breakfast cereals were also affective factors of their Bowl life. The quality describing terms of breakfast cereals were surveyed and the terms were classified to brittleness, roasted nutty taste, sweetness, hardness and aftertaste, especially brittleness was the most important quality determining terms among these. Significantly, sweetness had positive correlationship with roasted nutty taste. Overall eating quality had positively correlationship with color and roasted nutty flavor, and negatively with pain in mouth, adhesiveness and additive taste.