CHENG Haojie. Research on Rapid Prediction Model of Tensile Strength for Coal and Rock Mass Based on Multi-method FusionJ. Shandong Coal Science and Technology, 2026, 44(1): 166-171, 176. DOI: 10.3969/j.issn.1005-2801.2026.01.031
Citation: CHENG Haojie. Research on Rapid Prediction Model of Tensile Strength for Coal and Rock Mass Based on Multi-method FusionJ. Shandong Coal Science and Technology, 2026, 44(1): 166-171, 176. DOI: 10.3969/j.issn.1005-2801.2026.01.031

Research on Rapid Prediction Model of Tensile Strength for Coal and Rock Mass Based on Multi-method Fusion

  • In view of the correlation between uniaxial tensile strength (Rt) and point load strength index (Is) of coal and rock mass, a study is carried out. Through a combination method of experiment, numerical simulation, and theoretical analysis, a conversion relationship between the two is established and its reliability is verified. Four types of coal rock samples, including coal, mudstone, sandstone, and limestone, are selected for the experiment and subjected to Brazilian splitting test and point load test, respectively, to obtain uniaxial tensile strength and point load strength data. The results show that Rt is highly linearly positively correlated with Is, and the fitting equation is Rt=1.093Is+1.014 (R2=0.992). The stress distribution of coal and rock mass under point load action is simulated through finite element analysis, it is found that the numerical simulation results are highly consistent with the experimental failure mode (error <5%); The stress concentration coefficient derived from the elasticity mechanics theory is highly consistent with the experimental equation, the accuracy of the theoretical model is verified. The Mohr-Coulomb criterion analysis shows that the point load failure mechanism of coal and rock mass conforms to the maximum tensile stress failure criterion, providing a theoretical basis for rapidly estimating the tensile strength of coal mine roadway support design, but the sample types are limited, in the future, it is necessary to expand to more rock types and environmental conditions for research.
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