Coal burst remains one of the gravest safety risks that will be encountered in mining in the future, because the stress conditions will become more complex as mining depths increase. Various influencing elements exist...Coal burst remains one of the gravest safety risks that will be encountered in mining in the future, because the stress conditions will become more complex as mining depths increase. Various influencing elements exist, and varied geological and mining circumstances might result in diverse coal burst phenomena. The impact propensity of coal has variations as a result of the distinct physical and mechanical qualities of each. To identify the impact propensity of coal and then understand the rules of coal burst occurrence, laboratory tests can be conducted to identify the physical and mechanical parameters affecting coal samples. The mechanical properties, energy absorption, and energy dissipation characteristics of coal samples were examined experimentally in this paper using coal samples that were taken from the mine. On the basis of the evaluation of the impact inclination parameters for four fundamental coal samples, novel impact inclination indicators and the relationship between the fractures in the coal sample and the impact inclination parameters were discussed. The following are the key conclusions: 1) On-site samples of No. 15 coal from the Qi yuan Coal Mine were taken (15 s) and processed in accordance with the guidelines for the coal specimen impact inclination test. The accuracy of the specimen was sufficient for the test. 2) Analysis is done on the mechanical relevance and calculation techniques of the four fundamental coal sample impact tendency characteristics, dynamic failure time (DT), elastic strain energy index (W<sub>ET</sub>), impact energy index (K<sub>E</sub>), as well as uniaxial compressive strength (R<sub>C</sub>). 3) Regarding the rock burst danger of rock samples, the potential use of the ratio of pre-peak and post- peak deformation modulus to Kλ and the residual elastic strain energy index C<sub>EF</sub> as the impact propensity indices of coal samples are discussed. It is possible to utilize two new impact propensity indices to evaluate the impact propensity of coal samples, according to test results that reveal a linear correlation between two new impact inclination indexes and four fundamental impact tendency indexes. 4) The statistical analysis of the crack ratio with the four impact propensity indicators after coal specimen failure, and the correlation among the crack ratio with the indicators, are both done. The findings indicate that the four impact propensity indicators have a linear relationship with the crack ratio of the coal sample surface cracks.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
文摘Coal burst remains one of the gravest safety risks that will be encountered in mining in the future, because the stress conditions will become more complex as mining depths increase. Various influencing elements exist, and varied geological and mining circumstances might result in diverse coal burst phenomena. The impact propensity of coal has variations as a result of the distinct physical and mechanical qualities of each. To identify the impact propensity of coal and then understand the rules of coal burst occurrence, laboratory tests can be conducted to identify the physical and mechanical parameters affecting coal samples. The mechanical properties, energy absorption, and energy dissipation characteristics of coal samples were examined experimentally in this paper using coal samples that were taken from the mine. On the basis of the evaluation of the impact inclination parameters for four fundamental coal samples, novel impact inclination indicators and the relationship between the fractures in the coal sample and the impact inclination parameters were discussed. The following are the key conclusions: 1) On-site samples of No. 15 coal from the Qi yuan Coal Mine were taken (15 s) and processed in accordance with the guidelines for the coal specimen impact inclination test. The accuracy of the specimen was sufficient for the test. 2) Analysis is done on the mechanical relevance and calculation techniques of the four fundamental coal sample impact tendency characteristics, dynamic failure time (DT), elastic strain energy index (W<sub>ET</sub>), impact energy index (K<sub>E</sub>), as well as uniaxial compressive strength (R<sub>C</sub>). 3) Regarding the rock burst danger of rock samples, the potential use of the ratio of pre-peak and post- peak deformation modulus to Kλ and the residual elastic strain energy index C<sub>EF</sub> as the impact propensity indices of coal samples are discussed. It is possible to utilize two new impact propensity indices to evaluate the impact propensity of coal samples, according to test results that reveal a linear correlation between two new impact inclination indexes and four fundamental impact tendency indexes. 4) The statistical analysis of the crack ratio with the four impact propensity indicators after coal specimen failure, and the correlation among the crack ratio with the indicators, are both done. The findings indicate that the four impact propensity indicators have a linear relationship with the crack ratio of the coal sample surface cracks.
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.
