煤系岩体物理力学参数特征及统计分析——以皖北青东煤矿为例
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摘要
在煤矿工程地质问题分析及地质工程设计中,岩石的物理力学指标必不可少,它们直接关系到井巷及围岩稳定性分析、预计开采围岩破坏高度、顶底板抗水压能力评价等工程地质问题的可靠性。以青东煤矿为例,在分析矿区3种典型岩性(泥岩、砂岩、粉砂岩)的视密度、含水率、吸水率、抗压强度、抗拉强度、抗剪强度、内摩擦角、内聚力、泊松比等岩石物理力学参数特征的基础上,重点对抗压强度等7个参数指标进行概率分布拟合,从而获得其参数分布类型及统计量,并利用Bayes方法对参数进行了优化。结果表明:随着煤系岩体赋存深度的增大,无论是泥岩、砂岩还是粉砂岩,其割线模量和视密度变化不大,而抗压强度等参数则不断变化。同时,相关性分析表明各参数岩石力学性质的差异性和一致性;粉砂岩各参数的P-P图、直方图、曲线拟合结果表明,全部参数符合正态分布,经过Bayes优化后其方差均有所降低。煤系岩体物理力学参数的确定可为该区煤矿工程地质问题防治提供参考。
Physical and mechanical indexes of rock are indispensable in the analysis of engineering geological problems and the design of geological engineering in coal mines. They are directly related to the reliability of engineering geological problems, such as the stability analysis of mine roadways and surrounding rocks, the prediction of failure height of mining surrounding rocks, and the evaluation of roof and floor water pressure resistance. Taking Qingdong Coal Mine as an example, this paper analyzes the physical and mechanical parameters of three typical lithologies(mudstone, sandstone and siltstone), such as apparent density, water content, water absorption, compressive strength, tensile strength, shear strength, internal friction angle, cohesion and Poisson's ratio. The probability distribution of seven parameters such as compressive strength of siltstone is fitted to obtain the distribution types and statistics of parameters. On this basis, the parameters are optimized by Bayes method. The results show that the secant modulus and apparent density of mudstone, sandstone and siltstone have little change, but the compressive strength and other parameters change with the increase of the depth of coal measures. At the same time, correlation analysis shows the difference and consistency of rock mechanical properties of various parameters. The P-P diagram, histogram and curve fitting results of siltstone parameters show that all parameters conform to normal distribution, and their variances are reduced after Bayes optimization. The determination of physical and mechanical parameters of coal measures rock mass can provide reference for prevention and control of engineering geological problems in coal mines in this area.
Physical and mechanical indexes of rock are indispensable in the analysis of engineering geological problems and the design of geological engineering in coal mines. They are directly related to the reliability of engineering geological problems, such as the stability analysis of mine roadways and surrounding rocks, the prediction of failure height of mining surrounding rocks, and the evaluation of roof and floor water pressure resistance. Taking Qingdong Coal Mine as an example, this paper analyzes the physical and mechanical parameters of three typical lithologies(mudstone, sandstone and siltstone), such as apparent density, water content, water absorption, compressive strength, tensile strength, shear strength, internal friction angle, cohesion and Poisson's ratio. The probability distribution of seven parameters such as compressive strength of siltstone is fitted to obtain the distribution types and statistics of parameters. On this basis, the parameters are optimized by Bayes method. The results show that the secant modulus and apparent density of mudstone, sandstone and siltstone have little change, but the compressive strength and other parameters change with the increase of the depth of coal measures. At the same time, correlation analysis shows the difference and consistency of rock mechanical properties of various parameters. The P-P diagram, histogram and curve fitting results of siltstone parameters show that all parameters conform to normal distribution, and their variances are reduced after Bayes optimization. The determination of physical and mechanical parameters of coal measures rock mass can provide reference for prevention and control of engineering geological problems in coal mines in this area.
引文
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[12]南波.基于K-S检验法的雪荷载统计分析[J].兰州理工大学学报,2012,38(1):115-119.
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[2]曹吉阳,姚多喜,鲁海峰,等.淮北矿区下组煤隔水底板岩体力学参数统计分析[J].工程地质学报,2015,23(S):584-589.
[3]姚多喜,鲁海峰,邵亚红.煤系岩体参数概率分布及Bayes优化[J].安徽理工大学学报(自然科学版),2014(4):15-18.
[4]张勤,陈志坚,罗增益.裂隙岩体结构面力学参数取值的工程地质研究[J].河海大学学报(自然科学版),1999,27(6):114-117.
[5]李红英,谭跃虎,赵辉.某滑坡体岩土参数概率分布统计分析方法研究[J].地下空间与工程学报,2012,8(3):659-665.
[6]杨泽.云南某露天矿东采区边坡岩体力学参数取值研究[D].昆明:昆明理工大学,2010.
[7]薛凉,姚多喜,李子明,等.青东煤矿矿井瓦斯地质特征[J].矿山工程,2018,6(1),16-24.
[8]何满潮,谢和平,彭苏萍,等.深部开采岩体力学研究[J].岩石力学与工程学报,2005,24(16):2803-2813.
[9]隋旺华,周圣武,姜振全,等.煤系岩石工程地质性质指标变异性研究[J].煤田地质与勘探,1998,26(5):44-47.
[10]陈剑平,王清,肖树芳,等.K-S检验假设分布有效性在岩体工程中的应用;全国工程地质大会论文集[C].北京:地震出版社,1996.
[11]马建全,李广杰,徐佩华,等.基于拉丁方抽样及K-S检验的边坡可靠性分析[J].岩土力学,2011,32(7):2153-2156.
[12]南波.基于K-S检验法的雪荷载统计分析[J].兰州理工大学学报,2012,38(1):115-119.
[13]阮云凯,陈剑平,曹琛,等.K-S检验在裂隙岩体统计均质区划分中的应用[J].东北大学学报(自然科学版),2015,36(10):1471-1475.
[14]陆乐,吴吉春,陈景雅.基于贝叶斯方法的水文地质参数识别[J].水文地质工程地质,2008,35(5):58-63.