Mullite thermal storage ceramics were prepared by low-cost calcined bauxite and kaolin.The phase composition,microstructure,high temperature resistance and thermophysical properties were characterized by modern testin...Mullite thermal storage ceramics were prepared by low-cost calcined bauxite and kaolin.The phase composition,microstructure,high temperature resistance and thermophysical properties were characterized by modern testing techniques.The experimental results indicate that sample A3(bauxite/kaolin ratio of 5:5)sintered at 1620℃has the optimum comprehensive properties,with bulk density of 2.83 g·cm^(-3)and bending strength of 155.44 MPa.After 30 thermal shocks(1000℃-room temperature,air cooling),the bending strength of sample A3 increases to 166.15 MPa with an enhancement rate of 6.89%,the corresponding thermal conductivity and specific heat capacity are 3.54 W·(m·K)^(-1)and 1.39 kJ·(kg·K)^(-1)at 800℃,and the thermal storage density is 1096 kJ·kg^(-1)(25-800 mullite ceramics;sintering properties;high-temperature thermal storage;thermal shock resistance).Mullite forms a dense and continuous interlaced network microstructure,which endows the samples high thermal storage density and high bending strength,but the decrease of bauxite/kaolin ratio leads to the decrease of mullite content,which reduces the properties of the samples.展开更多
In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is a...In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is affected by more than one mining panel, traditional PIM parameter inversion model is difficult to ensure the reliability of the results due to the complexity of rock movement. With crossover,mutation and selection operators, GA can perform a global optimization search and has high computation efficiency. Compared with the pattern search algorithm, the fitness function can avoid falling into local minima traps. GA reduces the risk of local minima traps which improves the accuracy and reliability with the mutation mechanism. Application at Xuehu colliery shows that GA can be used to inverse the PIM parameters for multi-panel surface movement observation, and reliable results can be obtained. The research provides a new way for back-analysis of PIM parameters for mining subsidence under complex conditions.展开更多
The security challenges from room and pillar gobs include land subsidence, spontaneous combustion of coal pillars and mine flood caused by gob water. To explore the instability mechanism of room and pillar gob, we est...The security challenges from room and pillar gobs include land subsidence, spontaneous combustion of coal pillars and mine flood caused by gob water. To explore the instability mechanism of room and pillar gob, we established a mechanical model of elastic plate on elastic foundation in which pillars and hard roofs were considered as continuous Winkler foundations and elastic plates, respectively. The synergetic instability of pillar and roof system was analyzed based on plate bending theory and catastrophe theory. In addition, mechanical conditions and math criterion of roof failure and overall instability of coal pillar and roof system were given. Through analyzing both advantages and disadvantages of some technologies such as induced caving, filling, gob sealing and isolation, we presented a new filling method named box-filling, in view of box foundation theory, to control the disasters of ground collapse, water inrush and mine fire. In a gob's treatment project in Ordos, safety assessment and filling design of a room and pillar gob have been done by the mechanical model. The results show that the gob will collapse when the pillars' average yield band is wider than 0.93 m, and box-filling can control land collapse, mine flood and mine fire economically and efficiently. So it is worth to study further and popularize.展开更多
In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and time...In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.展开更多
In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine (SVM) was established to calculate the displacement factor. The study is based on a comprehensive an...In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine (SVM) was established to calculate the displacement factor. The study is based on a comprehensive analysis of factors affecting the displacement factor, such as mechanical properties of the cover rock, the ratio of mining depth to seam thickness, dip angle of the coal seam and the thickness of loose layer. Data of 63 typical observation stations were used as a training and testing sample set. A SVM regression model of the displacement factor and the factors affecting it was established with a kernel function, an insensitive loss factor and a properly selected penalty factor. Given an accurate calculation algorithm for testing and analysis, the results show that an SVM regression model can calculate displacement factor precisely and reliable precision can be obtained which meets engineering requirements. The experimental results show that the method to calculation of the displacement factor, based on the SVM method, is feasible. The many factors affecting the displacement factor can be considered with this method. The research provides an efficient and accurate approach for the calculation of displacement in mining subsidence prediction.展开更多
基金Funded by the National Key Research and Development Program of Science and Technology of China(No.2018YFB1501002)。
文摘Mullite thermal storage ceramics were prepared by low-cost calcined bauxite and kaolin.The phase composition,microstructure,high temperature resistance and thermophysical properties were characterized by modern testing techniques.The experimental results indicate that sample A3(bauxite/kaolin ratio of 5:5)sintered at 1620℃has the optimum comprehensive properties,with bulk density of 2.83 g·cm^(-3)and bending strength of 155.44 MPa.After 30 thermal shocks(1000℃-room temperature,air cooling),the bending strength of sample A3 increases to 166.15 MPa with an enhancement rate of 6.89%,the corresponding thermal conductivity and specific heat capacity are 3.54 W·(m·K)^(-1)and 1.39 kJ·(kg·K)^(-1)at 800℃,and the thermal storage density is 1096 kJ·kg^(-1)(25-800 mullite ceramics;sintering properties;high-temperature thermal storage;thermal shock resistance).Mullite forms a dense and continuous interlaced network microstructure,which endows the samples high thermal storage density and high bending strength,but the decrease of bauxite/kaolin ratio leads to the decrease of mullite content,which reduces the properties of the samples.
基金provided by the National Natural Science Foundation of China(No.51404272)the Hunan Province Key Laboratory of Coal Resources Clean-Utilization and Mine Environment Protection(No.E21224)
文摘In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is affected by more than one mining panel, traditional PIM parameter inversion model is difficult to ensure the reliability of the results due to the complexity of rock movement. With crossover,mutation and selection operators, GA can perform a global optimization search and has high computation efficiency. Compared with the pattern search algorithm, the fitness function can avoid falling into local minima traps. GA reduces the risk of local minima traps which improves the accuracy and reliability with the mutation mechanism. Application at Xuehu colliery shows that GA can be used to inverse the PIM parameters for multi-panel surface movement observation, and reliable results can be obtained. The research provides a new way for back-analysis of PIM parameters for mining subsidence under complex conditions.
基金provided by the National Natural Science Foundation of China (No. 41071273)
文摘The security challenges from room and pillar gobs include land subsidence, spontaneous combustion of coal pillars and mine flood caused by gob water. To explore the instability mechanism of room and pillar gob, we established a mechanical model of elastic plate on elastic foundation in which pillars and hard roofs were considered as continuous Winkler foundations and elastic plates, respectively. The synergetic instability of pillar and roof system was analyzed based on plate bending theory and catastrophe theory. In addition, mechanical conditions and math criterion of roof failure and overall instability of coal pillar and roof system were given. Through analyzing both advantages and disadvantages of some technologies such as induced caving, filling, gob sealing and isolation, we presented a new filling method named box-filling, in view of box foundation theory, to control the disasters of ground collapse, water inrush and mine fire. In a gob's treatment project in Ordos, safety assessment and filling design of a room and pillar gob have been done by the mechanical model. The results show that the gob will collapse when the pillars' average yield band is wider than 0.93 m, and box-filling can control land collapse, mine flood and mine fire economically and efficiently. So it is worth to study further and popularize.
基金supported by the Research and Innovation Program for College and University Graduate Students in Jiangsu Province (No.CX10B-141Z)the National Natural Science Foundation of China (No. 41071273)
文摘In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.
基金the Research and Innovation Program for College and University Graduate Students in Jiangsu Province (No.CX10B_141Z)the National Natural Science Foundation of China (No.41071273) for support of this project
文摘In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine (SVM) was established to calculate the displacement factor. The study is based on a comprehensive analysis of factors affecting the displacement factor, such as mechanical properties of the cover rock, the ratio of mining depth to seam thickness, dip angle of the coal seam and the thickness of loose layer. Data of 63 typical observation stations were used as a training and testing sample set. A SVM regression model of the displacement factor and the factors affecting it was established with a kernel function, an insensitive loss factor and a properly selected penalty factor. Given an accurate calculation algorithm for testing and analysis, the results show that an SVM regression model can calculate displacement factor precisely and reliable precision can be obtained which meets engineering requirements. The experimental results show that the method to calculation of the displacement factor, based on the SVM method, is feasible. The many factors affecting the displacement factor can be considered with this method. The research provides an efficient and accurate approach for the calculation of displacement in mining subsidence prediction.
