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ZHAO Yixin, JING Gang, LIU Bin, et al. Preliminary investigation on neutron emission characteristics during the failure process of coal and rock under uniaxial compressionJ. Journal of Mining and Strata Control Engineering, 2026, 8(1): 013051. DOI: 10.13532/j.jmsce.cn10-1638/td.2025-1226
Citation: ZHAO Yixin, JING Gang, LIU Bin, et al. Preliminary investigation on neutron emission characteristics during the failure process of coal and rock under uniaxial compressionJ. Journal of Mining and Strata Control Engineering, 2026, 8(1): 013051. DOI: 10.13532/j.jmsce.cn10-1638/td.2025-1226

Preliminary investigation on neutron emission characteristics during the failure process of coal and rock under uniaxial compression

  • Neutron emission (NE) has the advantage of electromagnetic interference immunity. To explore a new monitoring method for potential application on the forecast of dynamic hazards in mining, the NE characteristics of coal, granite, and magnetite samples were investigated by performing uniaxial compression experiments. Acoustic emission (AE) signals were synchronously monitored in the experimental process. The early warning indicators of coal and rock were discussed based on the acquired NE and AE data. It was found that the NE signals vary enormously during the failure process, which demonstrates its potential to serve as a novel method for monitoring coal and rock instability. Samples with higher iron contents are more prone to induce NE upon sudden failure, and the amplitude of NE is correlated with the iron content. For the strongly burst-prone coal sample from Hongqinghe Coal Mine, the peak NE intensity at instability is approximately 13.3 times the background NE intensity of the test environment. In contrast, for the weakly burst-prone coal sample from Wanglou Coal Mine, it shows no noticeable difference from the background intensity throughout failure. AE can continuously characterize the entire process of damage accumulation, while NE displays a sharp surge at the critical point of macroscopic instability. The two kinds of signals are complementary in terms of time sequence and physical mechanisms. Prior to instability, NE is characterized by the nonlinear growth of cumulative values and an order-of-magnitude jump in the coefficient of variation. When the samples approach instability, all coefficients of variation curves exhibit a significant sudden surge to the peak value.
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