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Use of uncertainty methodology in identification and classification of soils based upon CPT

机译:基于CPT的不确定性方法在土壤识别和分类中的应用

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摘要

The current Cone Penetration Test (CPT) soil engineering classifications have two kinds of uncertainties: randomness and fuzziness. Research indicates that possible solutions to these uncertainties can only be worked out through modeling them. Therefore, a systematic investigation is performed and some preparative tasks are done in advance. First, an efficient soil classification index, U, is defined and several CPT soil classification charts are simplified accordingly. Second, a moving window approach based upon an Intraclass Correlation Coefficient (ICC) to determine normal soil behavior units is adopted so that a correlation between soil types and soil behavior units can be established. Based upon these approaches, a preliminary data reduction is performed on the raw CPT data from eight sites, and the characteristics and distributions of the soil behavior units are determined and discussed for seven soil types.;Two statistical criteria, Region Estimation and Point Estimation, based upon distributions of soil behavior units are then developed to predict soil type using CPT data. Also, a fuzzy subset approach is suggested to handle the fuzziness and randomness. In this CPT fuzzy soil engineering classification, a new naming system is used. The randomness of CPT soil engineering classification is put into the conceptual framework of three new soil types. The fuzziness is then described by fuzzy membership functions. These functions are derived from the modification of the density functions of corresponding compositional soil groups.;Finally, a new package of CPT soil engineering classification is suggested. It consists of following procedures: (1) Transform a CPT sounding profile of parameters (tip resistance, q$sb{rm c},$ and friction ratio, FR) by conformal mapping to a corresponding profile of soil classification index, U; (2) Layer the U profile by ICC moving window method and calculate the mean of U values for each layer to determine the soil behavior unit; (3) Predict the soil type of each layer by matching the soil behavior unit of that layer with the classification criteria suggested in this study.;Several sets of CPT soil engineering classification criteria are recommended in this dissertation. They are the indicators of an evolution process from the purely empirical to the purely theoretical.
机译:当前的锥形渗透测试(CPT)土壤工程分类具有两种不确定性:随机性和模糊性。研究表明,只有通过对它们进行建模,才能解决这些不确定性。因此,需要进行系统的调查并提前完成一些准备工作。首先,定义了有效的土壤分类指数U,并相应地简化了几个CPT土壤分类图。其次,采用基于类内相关系数(ICC)来确定正常土壤行为单位的移动窗口方法,从而可以建立土壤类型与土壤行为单位之间的相关性。基于这些方法,对来自八个地点的原始CPT数据进行了初步的数据约简,确定并讨论了7种土壤类型的土壤行为单位的特征和分布。;两种统计标准,区域估计和点估计,然后,根据土壤行为的分布,使用CPT数据开发单位以预测土壤类型。此外,建议使用模糊子集方法来处理模糊性和随机性。在此CPT模糊土壤工程分类中,使用了新的命名系统。 CPT土壤工程分类的随机性被引入了三种新型土壤的概念框架。然后通过模糊隶属度函数描述模糊性。这些功能来自对相应组成土壤群的密度函数的修改。最后,提出了一种新的CPT土壤工程分类包。它包括以下步骤:(1)通过共形映射将对应参数的CPT测深曲线(尖端阻力,q $ sb {rm c},$和摩擦比,FR)转换为相应的土壤分类指数U。 (2)通过ICC移动窗口法对U型材进行分层,并计算每层U值的平均值,以确定土壤行为单位; (3)通过匹配该层的土壤行为单元与本研究提出的分类标准来预测各层的土壤类型。;本论文推荐了几套CPT土壤工程分类标准。它们是从纯经验到纯理论演变过程的指标。

著录项

  • 作者

    Zhang, Zhongjie.;

  • 作者单位

    Louisiana State University and Agricultural & Mechanical College.;

  • 授予单位 Louisiana State University and Agricultural & Mechanical College.;
  • 学科 Civil engineering.
  • 学位 Ph.D.
  • 年度 1994
  • 页码 216 p.
  • 总页数 216
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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