Compressional harmonic wave propagation from a cylindrical tunnel or borehole in an intact rock is the basis for investigation of the practical explosion waves in a fractured rock mass. The amplitudes of the radial st...Compressional harmonic wave propagation from a cylindrical tunnel or borehole in an intact rock is the basis for investigation of the practical explosion waves in a fractured rock mass. The amplitudes of the radial stress wave obtained from the universal distinct element code (UDEC) were compared with the analytical solutions for two cases with different conditions. Good agreements between the UDEC results and the analytical solutions have been achieved. It indicates that UDEC can model 2-D dynamic problems at a high degree of accuracy.展开更多
Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models...Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models,but still selection of suitable transformation of the independent variables in a regression model is diffcult.In this paper,a genetic algorithm(GA)has been employed as a heuristic search method for selection of best transformation of the independent variables(some index properties of rocks)in regression models for prediction of uniaxial compressive strength(UCS)and modulus of elasticity(E).Firstly,multiple linear regression(MLR)analysis was performed on a data set to establish predictive models.Then,two GA models were developed in which root mean squared error(RMSE)was defned as ftness function.Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.展开更多
The material and elastic properties of rocks are utilized for predicting and evaluating hard rock brittleness using artificial neural networks（ANN）. Herein hard rock brittleness is defined using Yagiz＇method. A pre...The material and elastic properties of rocks are utilized for predicting and evaluating hard rock brittleness using artificial neural networks（ANN）. Herein hard rock brittleness is defined using Yagiz＇method. A predictive model is developed using a comprehensive database compiled from 30 years＇ worth of rock tests at the Earth Mechanics Institute（EMI）, Colorado School of Mines. The model is sensitive to density, elastic properties, and P- and S-wave velocities. The results show that the model is a better predictor of rock brittleness than conventional destructive strength-test based models and multiple regression techniques. While the findings have direct implications on intact rock, the methodology can be extrapolated to rock mass problems in both tunneling and underground mining where rock brittleness is an important control.展开更多
Intact rock is typically described according to its uniaxial compressive strength （UCS）. The UCS is needed in the design of geotechnical engineering problems including stability of rock slopes and design of shallow ...Intact rock is typically described according to its uniaxial compressive strength （UCS）. The UCS is needed in the design of geotechnical engineering problems including stability of rock slopes and design of shallow and deep foundations resting on and/or in rocks. Accordingly, a correct measure-ment/evaluation of the UCS is essential to a safe and economic design. Typically, the UCS is measured using the unconfined compression tests performed on cylindrical intact specimens with a minimum length to width ratio of 2. In several cases, especially for weak and very weak rocks, it is not possible to extract intact specimens with the needed minimum dimensions. Thus, alternative tests （e.g. point load test, Schmidt hammer） are used to measure rock strength. The UCS is computed based on the results of these tests through empirical correlations. The literature includes a plethora of these correlations that vary widely in estimating rock strength. Thus, it is paramount to validate these correlations to check their suitability for estimating rock strength for a specific location and geology. A review of the available correlations used to estimate the UCS from the point load test results is performed and summarized herein. Results of UCS, point load strength index and Young＇s modulus are gathered for calcareous sandstone specimens extracted from the Dubai area. A correlation for estimating the UCS from the point load strength index is proposed. Furthermore, the Young＇s modulus is correlated to the UCS.展开更多
基金Projects 50278057 supported by National Natural Science Foundation of China and 2002CB412703 supported by 973 Project
文摘Compressional harmonic wave propagation from a cylindrical tunnel or borehole in an intact rock is the basis for investigation of the practical explosion waves in a fractured rock mass. The amplitudes of the radial stress wave obtained from the universal distinct element code (UDEC) were compared with the analytical solutions for two cases with different conditions. Good agreements between the UDEC results and the analytical solutions have been achieved. It indicates that UDEC can model 2-D dynamic problems at a high degree of accuracy.
文摘Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models,but still selection of suitable transformation of the independent variables in a regression model is diffcult.In this paper,a genetic algorithm(GA)has been employed as a heuristic search method for selection of best transformation of the independent variables(some index properties of rocks)in regression models for prediction of uniaxial compressive strength(UCS)and modulus of elasticity(E).Firstly,multiple linear regression(MLR)analysis was performed on a data set to establish predictive models.Then,two GA models were developed in which root mean squared error(RMSE)was defned as ftness function.Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.
文摘The material and elastic properties of rocks are utilized for predicting and evaluating hard rock brittleness using artificial neural networks（ANN）. Herein hard rock brittleness is defined using Yagiz＇method. A predictive model is developed using a comprehensive database compiled from 30 years＇ worth of rock tests at the Earth Mechanics Institute（EMI）, Colorado School of Mines. The model is sensitive to density, elastic properties, and P- and S-wave velocities. The results show that the model is a better predictor of rock brittleness than conventional destructive strength-test based models and multiple regression techniques. While the findings have direct implications on intact rock, the methodology can be extrapolated to rock mass problems in both tunneling and underground mining where rock brittleness is an important control.
文摘Intact rock is typically described according to its uniaxial compressive strength （UCS）. The UCS is needed in the design of geotechnical engineering problems including stability of rock slopes and design of shallow and deep foundations resting on and/or in rocks. Accordingly, a correct measure-ment/evaluation of the UCS is essential to a safe and economic design. Typically, the UCS is measured using the unconfined compression tests performed on cylindrical intact specimens with a minimum length to width ratio of 2. In several cases, especially for weak and very weak rocks, it is not possible to extract intact specimens with the needed minimum dimensions. Thus, alternative tests （e.g. point load test, Schmidt hammer） are used to measure rock strength. The UCS is computed based on the results of these tests through empirical correlations. The literature includes a plethora of these correlations that vary widely in estimating rock strength. Thus, it is paramount to validate these correlations to check their suitability for estimating rock strength for a specific location and geology. A review of the available correlations used to estimate the UCS from the point load test results is performed and summarized herein. Results of UCS, point load strength index and Young＇s modulus are gathered for calcareous sandstone specimens extracted from the Dubai area. A correlation for estimating the UCS from the point load strength index is proposed. Furthermore, the Young＇s modulus is correlated to the UCS.
