Xuefeng Xu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Xuefeng Xu has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Fengjie Zhang
School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China
1 shared publication Hao Xu
College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266590, People’s Republic of China
1 shared publicationZuo Dai
School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454000, People’s Republic of China
1 shared publication
Latest Publications
- Open Access
- 24 May 2024
- Published by American Chemical Society (ACS) in ACS Omega
- Vol. 9 (22) , 23542-23554
Study on the Impact Failure Rules of Roadway Floor Induced by Dynamic Load Disturbance under Extremely Thick Conglomerate
The dynamic load resulting from the fracture of extremely thick rock layers directly influences the surrounding rock layers within stopes and roadways, thereby inducing rockburst disasters. Hence, studying the tunnel floor's impact and ground pressure induced by dynamic load disturbance under extremely thick conglomerates is crucial. This study focuses on the 23130 working face of Yuejin Coal Mine as its engineering background. Initially, through similar simulation experiments, the impact characteristics of dynamic load disturbance positions under thick conglomerates on tunnel bottom damage are investigated. Building upon this foundation, finite element numerical simulation is employed to explore the further conglomerate thickness' impact on tunnel floor damage under dynamic load disturbance. Lastly, the accuracy of similar and numerical simulation results is validated by incorporating field examples. Findings reveal that dynamic load disturbance leads to an instantaneous increase in coal and rock mass acceleration in the roof and floor of roadways, followed by a decrease to an equilibrium state, thereby subjecting the interior to high static load conditions. The thickness of conglomerate in the overlying rock layer emerges as a crucial factor affecting tunnel floor rockburst incidents. With dynamic load disturbance, as conglomerate thickness increases, the stress concentration area of the tunnel floor gradually shifts to deeper rock strata. Effective control of tunnel floor rockbursts can be achieved by implementing support measures like anchor rods and cables and managing tunnel deformation and damage under dynamic loads. Dynamic load disturbance under extremely thick conglomerates emerges as a pivotal condition for inducing tunnel floor impact damage. This study provides a theoretical foundation for the safe excavation of similar mine tunnels and for implementing rockburst prevention and control measures.
- 24 May 2024
- Published by American Chemical Society (ACS) in ACS Omega
- Vol. 9 (22) , 23542-23554
Open AccessStudy on the Impact Failure Rules of Roadway Floor Induced by Dynamic Load Disturbance under Extremely Thick Conglomerate
The dynamic load resulting from the fracture of extremely thick rock layers directly influences the surrounding rock layers within stopes and roadways, thereby inducing rockburst disasters. Hence, studying the tunnel floor's impact and ground pressure induced by dynamic load disturbance under extremely thick conglomerates is crucial. This study focuses on the 23130 working face of Yuejin Coal Mine as its engineering background. Initially, through similar simulation experiments, the impact characteristics of dynamic load disturbance positions under thick conglomerates on tunnel bottom damage are investigated. Building upon this foundation, finite element numerical simulation is employed to explore the further conglomerate thickness' impact on tunnel floor damage under dynamic load disturbance. Lastly, the accuracy of similar and numerical simulation results is validated by incorporating field examples. Findings reveal that dynamic load disturbance leads to an instantaneous increase in coal and rock mass acceleration in the roof and floor of roadways, followed by a decrease to an equilibrium state, thereby subjecting the interior to high static load conditions. The thickness of conglomerate in the overlying rock layer emerges as a crucial factor affecting tunnel floor rockburst incidents. With dynamic load disturbance, as conglomerate thickness increases, the stress concentration area of the tunnel floor gradually shifts to deeper rock strata. Effective control of tunnel floor rockbursts can be achieved by implementing support measures like anchor rods and cables and managing tunnel deformation and damage under dynamic loads. Dynamic load disturbance under extremely thick conglomerates emerges as a pivotal condition for inducing tunnel floor impact damage. This study provides a theoretical foundation for the safe excavation of similar mine tunnels and for implementing rockburst prevention and control measures.
- Open Access
Evaluation and Optimization of Multi-Parameter Prediction Index for Coal Spontaneous Combustion Combined with Temperature Programmed Experiment
Coal spontaneous combustion (CSC) is a serious threat to the safe mining of coal resources, and the selection of suitable gas indicators to predict the CSC state is crucial for the prevention and control of coal mine fires. In this paper, the temperature-programmed experiment of CSC was first carried out to analyze the gas components and compositions in the oxidative pyrolysis process of three coal samples (lignite, long-flame coal, and lean coal) with different coalification degrees. Subsequently, the spontaneous combustion tendency of these three coal samples was evaluated. Finally, through the variation of gas concentration, gas concentration ratio, and fire coefficient with coal temperature, the indicators suitable for predicting the spontaneous combustion of coal were preferred, and a multi-parameter indicator system was established to make a comprehensive judgment on the spontaneous combustion status of coal. The results show that coal rank is negatively correlated with oxygen consumption rate. The higher the coalification degree of coal, the slower the oxidation reaction and the later the characteristic temperature point appears. The lignite selected in this experiment is a type of coal that is more prone to spontaneous combustion than long-flame coal and poor coal, and the CO concentration, C2H6/CH4, and second fire coefficient R2 can be used as the main indicators for predicting CSC, while the other gases, olefin-alkane ratio and fire coefficient can be used as auxiliary indicators. To some extent, the research content can effectively and accurately determine the stage and degree of coal spontaneous combustion, which has a certain guiding role in predicting CSC.
Open AccessEvaluation and Optimization of Multi-Parameter Prediction Index for Coal Spontaneous Combustion Combined with Temperature Programmed Experiment
Coal spontaneous combustion (CSC) is a serious threat to the safe mining of coal resources, and the selection of suitable gas indicators to predict the CSC state is crucial for the prevention and control of coal mine fires. In this paper, the temperature-programmed experiment of CSC was first carried out to analyze the gas components and compositions in the oxidative pyrolysis process of three coal samples (lignite, long-flame coal, and lean coal) with different coalification degrees. Subsequently, the spontaneous combustion tendency of these three coal samples was evaluated. Finally, through the variation of gas concentration, gas concentration ratio, and fire coefficient with coal temperature, the indicators suitable for predicting the spontaneous combustion of coal were preferred, and a multi-parameter indicator system was established to make a comprehensive judgment on the spontaneous combustion status of coal. The results show that coal rank is negatively correlated with oxygen consumption rate. The higher the coalification degree of coal, the slower the oxidation reaction and the later the characteristic temperature point appears. The lignite selected in this experiment is a type of coal that is more prone to spontaneous combustion than long-flame coal and poor coal, and the CO concentration, C2H6/CH4, and second fire coefficient R2 can be used as the main indicators for predicting CSC, while the other gases, olefin-alkane ratio and fire coefficient can be used as auxiliary indicators. To some extent, the research content can effectively and accurately determine the stage and degree of coal spontaneous combustion, which has a certain guiding role in predicting CSC.