Journal
RESULTS IN PHYSICS
Volume 10, Issue -, Pages 1006-1014Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.rinp.2018.08.019
Keywords
Radon exhalation; Coal damage; Acoustic emission counts; Radon concentration; Gas pressure
Funding
- National Key R&D Program of China [2017YFC0804207]
- Chinese Ministry of Education Science and Technology Research Project [213022A]
- program for Innovative Research Team in University of Ministry of Education of China [IRT_16R22]
- National Natural Science Foundation of China [U1704129]
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Coal and gas outburst during underground mining operations negatively affects the mining safety and decrease the mining productivity. Current outburst prediction has been largely relying on seismic monitoring which is passive and extremely difficult to quantify. As coal produces radon in the damage process, this unique feature potentially offer a new way to reliably predict the outburst incidents. Therefore, in this study, a series of experiments were carried out under different gas pressures adopting the new coal-rock triaxial-loading radon exhalation test system, which aim to investigate the effect of gas depletion pressures on the characteristics of radon exhalation. The data of stress-strain, radon concentration, and acoustic emission were monitored simultaneously in the dynamic loading processes, and were compared and discussed in detail. Experimental results show that in the loading process, radon concentration shows clear step changes and has good consistency with the results of the coal deformation stages according to the acoustic emission count, verifying the feasibility of coal deformation and fracturing prediction based on radon concentration. Meanwhile, at the early stage of loading, the peak value of radon concentration reduces gradually with the increase in gas pressure. Furthermore, relationship between the maximum value of radon concentration and gas pressure is obtained. This work presents a new method to link gas pressure, coal deformation and fracture prediction together based on radon concentration, which could provide significant guidance for the accurate prediction of coal and rock dynamic disasters.
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