ISSN 1000-3665 CN 11-2202/P
    夏露, 谢娟, 于青春. 裂隙延展性统计分布离散性对岩体块体化程度REV的影响[J]. 水文地质工程地质, 2019, 46(4): 112-118. DOI: 10.16030/j.cnki.issn.1000-3665.2019.04.15
    引用本文: 夏露, 谢娟, 于青春. 裂隙延展性统计分布离散性对岩体块体化程度REV的影响[J]. 水文地质工程地质, 2019, 46(4): 112-118. DOI: 10.16030/j.cnki.issn.1000-3665.2019.04.15
    XIALu, . Influence of statistical distribution dispersion in the fracture size on blockiness REV of fractured rock masses[J]. Hydrogeology & Engineering Geology, 2019, 46(4): 112-118. DOI: 10.16030/j.cnki.issn.1000-3665.2019.04.15
    Citation: XIALu, . Influence of statistical distribution dispersion in the fracture size on blockiness REV of fractured rock masses[J]. Hydrogeology & Engineering Geology, 2019, 46(4): 112-118. DOI: 10.16030/j.cnki.issn.1000-3665.2019.04.15

    裂隙延展性统计分布离散性对岩体块体化程度REV的影响

    Influence of statistical distribution dispersion in the fracture size on blockiness REV of fractured rock masses

    • 摘要: 表征单元体(REV) 的存在是应用连续介质力学方法对岩体进行研究的前提,REV可以从岩体块体化程度的角度进行研究,裂隙大小及其统计分布是影响岩体块体化程度REV的重要因素。本文利用课题组自主研发的GeneralBlock 软件,建立更一般化实际化的模型,研究裂隙延展性统计分布的离散程度对岩体块体化程度REV的影响。分析时选取了最常用的裂隙延展性统计分布形式:正态分布。由于所建立的岩体结构模型是随机的,需要对每个随机裂隙模型进行多次实现。为节省计算量,当研究范围比较小时,对每种结构的每个研究范围进行9次随机实现。当研究范围足够大,达到REV大小的时候进行100次随机实现。为确定离散程度对表征单元体的影响,本文针对5个不同标准差进行了模拟分析(共建立了1 005个裂隙模型,分别进行了块体识别并计算其块体化程度B)。结果表明,裂隙延展性服从正态分布的情况下,如果其平均值一定,岩体的块体化程度随着统计分布离散程度的增加略有上升,裂隙岩体的REV值基本上由裂隙延展性统计平均值决定。

       

      Abstract: The existence of representative elementary volume (REV) is the premise of using the continuous-media method to study rock mass, and it can be studied from the view of blockiness. The size and statistical distribution of the fractures are the important factors in the blockiness REV of fractured rock masses. In this paper more generalized models are built to examine the influence of statistical distribution dispersion in the fracture size on the Blockiness REV of fractured rock masses by using the General Block software, which was developed by our research group. The most common statistical distribution of the fracture size, the normal distribution, is used. For each model, multiple realizations are carried out to reduce the effects of randomness. To improve the efficiency of computation, 9 random realizations are performed when the model domains are small. When the model domain sizes reach the REV volume, 100 random realizations are carried out. Five different standard deviations are considered in the simulation analysis to study the influence of statistical distribution dispersion in fracture size on the blockiness REV (1 005 fracture models are established, and rock blocks in each models are identified to calculate the blockiness). The results indicate that if the distribution of fracture size is normal, the REV is controlled by the mean value of the fracture size, and the blockiness increases slightly with the distribution dispersion in the fracture size.

       

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