线-面结合的结构面粗糙系数经验计算方法

范祥, 安宏磊, 包含, 任贤达, 邓志颖, 吴睿. 线-面结合的结构面粗糙系数经验计算方法[J]. 水文地质工程地质, 2023, 50(1): 78-86. doi: 10.16030/j.cnki.issn.1000-3665.202205027
引用本文: 范祥, 安宏磊, 包含, 任贤达, 邓志颖, 吴睿. 线-面结合的结构面粗糙系数经验计算方法[J]. 水文地质工程地质, 2023, 50(1): 78-86. doi: 10.16030/j.cnki.issn.1000-3665.202205027
FAN Xiang, AN Honglei, BAO Han, REN Xianda, DENG Zhiying, WU Rui. An empirical method for calculating the roughness coefficient of structural plane with line-plane combination[J]. Hydrogeology & Engineering Geology, 2023, 50(1): 78-86. doi: 10.16030/j.cnki.issn.1000-3665.202205027
Citation: FAN Xiang, AN Honglei, BAO Han, REN Xianda, DENG Zhiying, WU Rui. An empirical method for calculating the roughness coefficient of structural plane with line-plane combination[J]. Hydrogeology & Engineering Geology, 2023, 50(1): 78-86. doi: 10.16030/j.cnki.issn.1000-3665.202205027

线-面结合的结构面粗糙系数经验计算方法

  • 基金项目: 国家自然科学基金项目(41807241);中国博士后科学基金项目(2021M693544);长安大学中央高校专项资金资助项目(300102211205)
详细信息
    作者简介: 范祥(1986-),男,博士,副教授,从事岩体力学与隧道工程研究;E−mail:fanxiang224@126.com
  • 中图分类号: TU452

An empirical method for calculating the roughness coefficient of structural plane with line-plane combination

  • 岩体结构面的剪切力学特性主要取决于其表面粗糙特征,结构面粗糙系数是表征该粗糙特征的主要方法。目前对结构面粗糙系数的研究局限于单一维度,多角度且定量化计算结构面粗糙系数能避免单一维度分析导致计算精度不准的局限性。采用立方体花岗岩,通过巴西劈裂的方式制备含结构面的试样;利用高精度三维扫描仪对试样结构面进行扫描,得到结构面的点云数据,同时借助逆向软件对点云数据进行三维重构。研究了点云数据Z方向上的分布频率,剖面线剖面比与节理粗糙系数(JRC)值的关系,结构面面积比与JRC均值的关系。研究表明:点云数据Z方向上的分布频率可以作为初步评估结构面粗糙度的手段;剖面线剖面比与JRC数值、结构面面积比与JRC均值有二次函数的关系。通过数值分析建立了结构面JRC均值与剖面比、面积比的二元函数关系,并得到结构面JRC均值的经验计算公式。本次研究为结构面粗糙度提供了一种“点-线-面”逐渐深入的多角度评估思路,得到的经验公式为计算结构面JRC均值提供了一种新的计算方法。

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  • 图 1  结构面制作流程

    Figure 1. 

    图 2  结构面试样

    Figure 2. 

    图 3  结构面扫描图

    Figure 3. 

    图 4  剖面线形态特征

    Figure 4. 

    图 5  结构面示意图

    Figure 5. 

    图 6  点数柱状图

    Figure 6. 

    图 7  JRC数值

    Figure 7. 

    图 8  剖面线对比图

    Figure 8. 

    图 9  JRC数值与剖面比关系

    Figure 9. 

    图 10  JRC均值与面积比关系

    Figure 10. 

    图 11  JRC均值与剖面比、面积比的函数关系

    Figure 11. 

    表 1  拟合公式表

    Table 1.  Table of fitting formulas

    采样间距/mmJRC拟合计算公式来源
    0.25Yu等[6]
    0.5Tatone等[7]
    1Tatone等[7]
    下载: 导出CSV

    表 2  点云数据统计表

    Table 2.  Statistical table of point cloud data

    编号点数最大值/mm最小值/mm高差/mm均值/mm
    S1121893740.0580.98139.07722.050
    S2111105430.64012.76517.87522.820
    S3108851632.5688.30424.26420.708
    S4111410653.19231.28421.90842.682
    S5106690126.80314.06412.73920.668
    S6106489930.47112.02018.45120.787
    S7111204130.9979.42821.56920.359
    S8107454835.6885.52430.16423.831
    S9103441927.1920.07927.11318.420
    S10103831718.0511.21216.83911.554
    下载: 导出CSV

    表 3  S4试样剖面比统计表

    Table 3.  Statistical table of profile ratio of sample S4

    序号基准长度/mm实际长度/mm剖面比序号基准长度/mm实际长度/mm剖面比
    1147.946 2149.348 71.009 59150.276 6153.983 71.024 7
    2149.152 1152.422 01.021 910150.074 5153.291 81.021 4
    3149.209 1151.769 91.017 211150.276 8153.530 21.021 7
    4149.416 3151.581 71.014 412150.171 1153.031 41.019 0
    5150.135 4152.689 31.017 013150.042 8153.703 81.024 4
    6149.924 5152.605 11.017 914150.210 1154.129 61.026 1
    7149.966 1153.246 11.021 915147.501 0150.102 41.017 6
    8150.082 6153.455 61.022 5
    下载: 导出CSV

    表 4  试样面积比

    Table 4.  Area ratios of samples

    编号基准面积/mm2真实面积/mm2面积比
    S122 35024 116.034 11.079 0
    S222 35023 423.588 81.048 0
    S322 35023 201.424 41.038 1
    S421 02522 435.221 31.067 1
    S522 20022 641.000 01.019 9
    S621 31622 213.150 61.042 1
    S721 60922 986.338 91.063 7
    S822 20122 808.410 41.027 4
    S921 75622 973.348 31.056 0
    S1022 05223 216.181 81.052 8
    下载: 导出CSV

    表 5  试样数据统计

    Table 5.  Statistical data of the tested samples

    序号平均剖面比面积比JRC均值
    S11.032 21.079 08.93
    S21.029 81.048 08.62
    S31.026 01.038 18.51
    S41.029 51.067 18.78
    S51.015 01.019 96.68
    S61.016 01.042 17.86
    S71.024 91.063 79.14
    S81.018 01.027 47.18
    S91.040 51.056 08.95
    S101.026 31.052 88.90
    下载: 导出CSV
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出版历程
收稿日期:  2022-05-10
修回日期:  2022-06-16
录用日期:  2022-06-16
刊出日期:  2023-01-15

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