摘要
以昆明轨道交通工程中大量的泥炭质土物理力学指标试验数据为基础,采用统计分析方法,分析昆明地区泥炭质土物理力学指标的统计分布规律及指标间的相关关系,建立指标间的数学回归方程,并给出相应的相关系数。结果表明:昆明地区第二层泥炭质土工程性质较差、承载力较低,对工程沉降、稳定性影响明显。其物理力学指标的变异性较大,区域差异较为明显,概率分布模型较为复杂。根据一元回归和多元回归分析结果,泥炭质土的压缩系数与天然含水率、孔隙比及液性指数有较好的正相关性,压缩模量与液性指数有较好的负相关性,而抗剪强度指标与物理指标之间没有呈现明显相关性。进一步提出了一种能对压缩系数和主要物理指标间较好关联的多元线性模型,供设计参数取值提供参考。
Based on the experimental data of a large number physical and mechanical indexes of peaty soil in Kunming rail transit engineering,the method of statistical analysis was used to analyze the statistical distribution and the correlation of the physical and mechanical indexes of peaty soil in Kunming area.The mathematical regression equation between the indexes is established,and the corresponding correlation coefficient is given.The results show that the peaty soils in Kunming area are very weak,low bearing capacity,it has obvious effect on the settlement and stability of the engineering.The variability of physical and mechanical indexes is great,it has remarkable regional difference and complicated probabilistic distribution model.According to the results of simple and multiple regression analysis,there is positive correlation between the coefficient of compressibility and natural water content,void ration,liquidity index,and negative correlation between the compression modulus and liquidity index,while no significant correlation between the shear strength and physical indexes.A new multivariate linear model is proposed to associate the coefficient of compressibility and main physical indexes for peaty soil.It can provides a reference for defining the values of design parameters for peaty soil.
作者
丁祖德
付江
李夕松
王志良
李向红
DING Zude;FU Jiang;LI Xisong;WANG Zhiliang;LI Xianghong(Faculty of Civil Engineering and Mechanics,Kunming University of Science and Technology,Kunming,Yunnan 650500,China;Shanghai Tunnel Engineering Company Limited,Shanghai 200232,China)
出处
《公路工程》
北大核心
2018年第4期86-91,共6页
Highway Engineering
基金
国家自然科学基金项目(51768028
51308270
51408284)
云南省应用基础研究计划项目(2013FB015)
关键词
泥炭质土
物理力学指标
统计特征
相关性分析
多元线性回归
peaty soil
physical and mechanical indexes
statistical characteristic
correlation analysis
multiple linear regression
