长江科学院院报 ›› 2024, Vol. 41 ›› Issue (12): 101-108.DOI: 10.11988/ckyyb.20230775

• 岩土工程 • 上一篇    下一篇

膨胀土物理力学指标分布规律统计分析——以安康地区为例

郭瑞1(), 张建华2, 李俊祥3, 冯旭明4, 李文强1   

  1. 1 陕西理工大学 土木工程与建筑学院,陕西 汉中 723001
    2 中国建筑西南勘察设计研究院有限公司,成都 610052
    3 武汉纺织大学 机械工程与自动化学院,武汉 430200
    4 广东真正工程检测有限公司,广州 510530
  • 收稿日期:2023-07-17 修回日期:2023-11-22 出版日期:2024-12-01 发布日期:2024-12-01
  • 作者简介:

    郭 瑞(1982-),男,陕西武功人,副教授,博士,主要从事道路建筑材料、岩土工程方面的教学科研工作。E-mail:

  • 基金资助:
    陕西省自然科学基础研究计划一般项目(面上)(2023-JC-YB-307); 陕西省教育厅一般专项项目(23JK0370)

Probability Distribution Law of Physical and Mechanical Property Indexes of Expansive Soil: A Case Study from Ankang Area

GUO Rui1(), ZHANG Jian-hua2, LI Jun-xiang3, FENG Xu-ming4, LI Wen-qiang1   

  1. 1 School of Civil Engineering and Architecture, Shaanxi University of Technology, Hanzhong 723001, China
    2 China Southwest Geotechnical Investigation & Design Institute Co., Ltd., Chengdu 610052, China
    3 Schoolof Mechanical Engineering & Automation, Wuhan Textile University, Wuhan 430200, China
    4 Guangdong Zhenzheng Construction Engineering Testing Company Limited, Guangzhou 510530, China
  • Received:2023-07-17 Revised:2023-11-22 Published:2024-12-01 Online:2024-12-01

摘要:

为探究安康地区膨胀土物理力学指标的分布规律和合理取值范围,基于陕西安康某膨胀土工程实例,通过数理统计模型(正态分布、伽马分布、威布尔分布及对数正态分布)对不同指标的分布规律和范围进行统计分析,并采用柯尔莫哥洛夫-斯米洛夫(K-S)检验法对各指标分布特征进行检验。 结果表明: 膨胀土的干密度指标偏度最小且为右偏接近正态分布,膨胀率指标偏度最大且为左偏。采用对数正态分布函数能够更好地反映膨胀土含水率和孔隙比指标分布规律,正态分布函数能够更好地反映干密度指标分布规律,威布尔分布能够更好地反映膨胀土的液限、塑限、塑性指数、膨胀率及膨胀力等指标的分布规律;与平均值法相比较,采用最优拟合分布函数峰值能够较准确地评价膨胀土物理力学指标。研究结果对深入认识区域内膨胀土的变形特征和工程建设具有借鉴意义。

关键词: 膨胀土, 物理力学指标, 分布规律, 数理统计, 柯尔莫哥洛夫-斯米洛夫(K-S)检验法

Abstract:

In this study, we analyzed the distribution patterns and ranges of expansive soil indices through an engineering case study in Ankang, Shaanxi Province. By utilizing mathematical statistical models, specifically the Normal, Gamma, Weibull, and Lognormal distributions, we aimed to gain a deeper understanding of these indices. To validate our findings, we conducted the Kolmogorov-Smirnov (K-S) test, which allowed us to confirm the distribution of the indices and further elucidate the physical and mechanical properties of expansive soil. Our results revealed notable trends: the dry density index exhibited minimal deviation with a right skew, closely aligning with the Normal distribution. Conversely, the expansion rate demonstrated the greatest deviation and a left skew, indicating its heightened sensitivity to other indices. We also observed that the Lognormal distribution adeptly captured the patterns of water content and void ratio, while the Normal distribution provided an accurate representation of dry density. The Weibull distribution, on the other hand, excelled in describing the distributions of liquid limit, plastic limit, plasticity index, expansion rate, and expansion force in expansive soil. When compared to the traditional average method, our approach by utilizing the peak parameter values from the optimal distribution functions of various indices offers a more precise evaluation of the physical and mechanical properties of expansive soil. The findings serve as valuable guidance for comprehending regional expansion deformation and enhancing engineering design and construction practices.

Key words: expansive soil, physical-mechanical indexes, distribution law, mathematic statistics, Kolmogorov-Smilov test

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