基于多方法融合的煤岩体抗拉强度快速预测模型研究

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

  • 摘要: 针对煤岩体抗拉强度(Rt)与点荷载强度指数(Is)的关联性展开研究,通过实验、数值模拟与理论分析相结合的方法,建立了两者的转换关系式,并验证其可靠性。实验选取煤、泥岩、砂岩和石灰岩四类煤岩试样,分别进行巴西劈裂试验与点荷载试验,获得单轴抗拉强度及点荷载强度数据。结果表明:RtIs呈高度线性正相关,拟合方程为Rt=1.093Is+1.014(R2=0.992),通过有限元分析模拟点荷载作用下煤岩体的应力分布,发现数值模拟结果与实验破坏模式高度吻合(误差<5%);基于弹性力学理论推导的应力集中系数与实验方程高度一致,验证了理论模型的准确性。Mohr-Coulomb准则分析表明,煤岩体点荷载破坏机制符合最大拉应力失效判据,为煤矿巷道支护设计提供了快速估算抗拉强度的理论依据,但样本类型有限,未来需扩展至更多岩类及环境条件研究。

     

    Abstract: 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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