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Determination of representative elementary volume of fault core materials by particle distribution analysis

机译：粒子分布分析测定故障芯材料的代表性基础体积

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Fault core materials (fault breccia and fault gouge) exhibit heterogeneous particle size distributions due to many factors, including the type of cataclasis, the degree of weathering, and the scale and mechanism of the fault system. When studying particle size distributions in fault core materials, there is no clear standard of the sample size that should typically be used for testing and analysis. In this study, we present a method to establish the ideal sample size by statistically assessing a suite of laboratory tests on 451 fault-core samples from 21 locations in South Korea. These samples were divided into five different classes according to grain size. Weight ratios of gravel, sand, and silt/clay were calculated from laboratory tests on each sample, and the means and standard deviations were subsequently assessed via analysis of variance and multiple comparison analysis. The results of the analysis of variance suggested that classes 1-5 are different from each other in at least one factor. Tukey's HSD tests and Duncan's LSR tests were also applied to identify groups within the classes that might be statistically similar to each other. In this manner, it was found that classes 1 and 2 could be grouped together (group A), as could classes 3, 4, and 5 (group B). Standard deviation means and distribution ranges within groups were used to deduce that group B, rather than group A, contained the sample sizes that best represented the site. Furthermore, class 3 (which had the smallest weight among the different classes in group B) was determined as being the representative elementary volume (REV). This deduction is consistent with the recommendation for reference sample size used in soil particle size analysis (as defined by the American Society for Testing and Materials).
机译：故障芯材（故障Breccia和Fault Gouge）由于许多因素而具有异质粒度分布，包括Cataclasis类型，风化程度和故障系统的规模和机制。在故障核心材料中研究粒度分布时，不明确标准的样品尺寸通常用于测试和分析。在这项研究中，我们提出了一种通过统计评估来自韩国21个地点的451个故障核心样本的实验室测试套件来建立理想的样本量的方法。根据晶粒尺寸将这些样品分成五种不同的等级。从每个样品的实验室测试计算砾石，沙子和淤泥/粘土的重量比，随后通过方差分析和多重比较分析来评估该装置和标准偏差。方差分析的结果表明，在至少一个因素中，类别1-5彼此不同。 Tukey的HSD测试和Duncan的LSR测试也用于识别可能在统计上相似的类中的组。以这种方式，发现类1和2可以被分组在一起（组A），如类别3,4和5（B组）。组内的标准偏差和分配范围用于推导出B组，而不是A组，包含最能代表该网站的样本尺寸。此外，第3类（B组中不同类别中最小的重量）被确定为代表基本体积（Rev）。该扣除与土壤粒子尺寸分析中使用的参考样本尺寸的建议一致（由美国的测试和材料社会所定义）。

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