Probabilistically statistical analysis on physico-mechanical indices for sediment soils

LI Gang; ZHANG Jin-li; YANG Qing

doi:10.16285/j.rsm.2017.12.022

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Probabilistically statistical analysis on physico-mechanical indices for sediment soils

更新时间：2026-06-25

- Probabilistically statistical analysis on physico-mechanical indices for sediment soils
- Vol. 38, Issue 12, Pages: 3565-3572(2017)
- 作者机构：
  
  1. 西京学院陕西省混凝土结构安全与耐久性重点实验室,陕西,西安,710123
  2. 大连理工大学建设工程学部土木工程学院岩土工程研究所,辽宁,大连,116024
  3. 大连理工大学海岸和近海工程国家重点实验室,辽宁,大连,116024
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2017.12.022
  CLC： TU471
- Online First：05 June 2018，
  
  Published：2017
- 稿件说明：
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LI Gang, ZHANG Jin-li, YANG Qing. Probabilistically statistical analysis on physico-mechanical indices for sediment soils[J]. 2017, 38(12): 3565-3572.
DOI：

LI Gang, ZHANG Jin-li, YANG Qing. Probabilistically statistical analysis on physico-mechanical indices for sediment soils[J]. 2017, 38(12): 3565-3572. DOI： 10.16285/j.rsm.2017.12.022.

摘要

土体的物理力学指标具有地域特征，不同地质成因下土体的工程性质差异较大。基于大连离岸式人工岛工程地质勘察资料，根据不同的地质成因，将地基土体沿深度方向划分为海相沉积层、海陆交互沉积层与陆相沉积层3个独立的统计单元体。结合数理统计方法，应用SPSS软件对3个单元体土体的物理力学指标进行了统计与回归分析，并采用偏斜度、峰值法对土体指标的正态分布特征进行了假设检验。在正态分布的基础上，运用Bayes方法对土体抗剪强度指标进行了优化。研究结果表明：3个统计单元体土体物理力学性质差异较大，不同单元体下的土体指标呈现出不同的分布特征。经过Bayes优化后土体指标的标准差与变异系数明显减小，实现了对变量的时变预测。

Abstract

The physico-mechanical properties of soil vary in different regions. There are great differences on engineering properties for soils formed by different geological depositions. Based on the investigation data of Dalian offshore artificial island

the soils could be subdivided into three independent statistical unit according to the geological origin

i.e.

the top marine deposit

middle marine-continental deposit

and deep continental deposit. The physico-mechanical indices of deposits are analyzed by the SPSS software incorporated with mathematical statistics methods. The Gaussian distribution behaviors of deposit soils are hypothesis testing by the skewness and kurtosis method. The shear strength indices are optimized by the Bayesian approach. The results show that there are significant differences in the engineering properties of the deposits and their distribution. The standard deviation and variable coefficient of shear strength indices decrease after Bayesian optimized

and the time-varying predictions of parameters are realized.

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