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Zhonghui Li is a professor in the School of Safety Engineering, China University of Mining and Technology. He obtained his PhD in Safety Science and Engineering from China University of Mining and Technology in 2007 and was awarded the National Excellent Doctoral Dissertation Award. His research mainly focuses on the intelligent monitoring and early warning of coal-rock dynamic disasters, especially the prevention of coal and gas outbursts and geophysical responses. He has led more than 10 national-level high-profile projects supported by the National Natural Science Foundation of China and National Key R&D Program of China, and has published over 50 SCI papers in prestigious journals. He serves as an editorial board member of four Chinese journals. He has guided his postgraduate students to obtain one Jiangsu Provincial Excellent Doctoral Thesis award and three Jiangsu Provincial Excellent Master's Thesis awards.
Outline
The instability of composite coal-rock structures can easily trigger severe dynamic disasters, such as rockbursts. The application of electric potential (EP) method shows promise for disaster prediction and accurate identification of coal-rock interfaces. In this study, uniaxial compression experiments were conducted to monitor the EP spatiotemporal response of fine sandstone-coal and coarse sandstone-coal combined samples. EP distribution contour maps and three-dimensional (3D) EP models were utilized to explore the failure mechanisms and identify the interface state. Then the relationship between EP response and force field was examined through numerical simulations. An EP-based multifractal method was utilized to predict rock failure. Results show that the intensity and polarity of EPs differ between coal and rock but are correlated with stress state. The progressive failure features of two types of combined samples differ, triggering distinct EP responses. In the EP contour maps, the EP level increases with increasing height, and a low-intensity signal band appears around the interface before failure. When failure occurs, the EP field changes, and the low-intensity signal band becomes distorted. The 3D EP models effectively visualize the progressive failure of combined samples and clearly identify the interface location, similar to acoustic emission (AE) location. The evolution of force chain field is closely related to EP generation, and sparse strong force chain fields leads to a significant increase in EP level. Furthermore, the EPs display multifractal features, with precursory information being reflected inΔα and Δf. This study provides new ideas for early-warning of composite coal-rock and coal-rock interface identification.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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