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Geostatistical analysis of cone penetration test (CPT) sounding using the modified Bartlett test

机译:使用改进的Bartlett检验进行锥形渗透试验(CPT)探测的地统计分析

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摘要

More in situ tests are typically carried out over the same volume of soil in comparison to laboratory tests on undisturbed borehole samples. Hence, geostatistical analysis of in situ test records should in principle provide a more accurate and representative overview of spatial variation. A natural probabilistic model for correlated spatial data is the random field. Although the random field provides a concise description of spatial variation, it poses considerable practical difficulties for statistical inference because of the underlying autocorrelation structure. This note presents an extended discussion of the modified Bartlett random field estimation procedure, which is capable of rejecting the null hypothesis of weak stationarity for spatially correlated data. In comparison with simple visual inspection and the standard run test, the modified Bartlett test is shown to provide three advantages: (i) it is a more consistent measure that is unaffected by the vagaries of subjective interpretation; (ii) it is sufficiently discriminative to decide if a section is stationary, even when visual clues are ambiguous; and (iii) it is capable of accommodating realistic constraints (e.g., short record length). The possibility of identifying secondary soil boundaries that may not be readily apparent from visual inspection of cone soundings, its robustness to alternate transformations of the cone data, and the sensitivity of the proposed procedure to different levels of significance are discussed.
机译:与对未受干扰的井眼样品进行实验室测试相比,通常在相同体积的土壤上进行更多的原位测试。因此,原位测试记录的地统计分析原则上应提供更准确,更具代表性的空间变化概况。相关空间数据的自然概率模型是随机字段。尽管随机字段提供了空间变化的简明描述,但由于潜在的自相关结构,它给统计推断带来了相当大的实际困难。本说明提出了对改进的Bartlett随机场估计程序的扩展讨论,该程序能够拒绝空间相关数据的弱平稳性的零假设。与简单的外观检查和标准运行测试相比,改进的巴特利特测试显示出三个优点:(i)这是一种更一致的度量,不受主观解释的各种影响; (ii)即使视觉线索不明确,也有足够的判别力来决定一个部分是否静止; (iii)能够适应现实的限制(例如,较短的记录长度)。讨论了确定次要土壤边界的可能性,这些可能性从视锥细胞探测的目视检查中可能不容易看出,它对于视锥细胞数据的交替转换的鲁棒性,以及所提出的方法对不同显着性水平的敏感性。

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