西安建筑科技大学学报(自然科学版)

考虑颗粒分布的不确定性,在排列熵计算过程中引入蒙特卡罗(Monte-Carlo, 简称M-C)方法,用以表征排列混乱程度.为探究粗粒土剪切过程中排列熵的演化规律,以粗颗粒含量P5为指标,设立4种不同类型的粗粒土结构为研究对象,结合常法向应力下的剪切试验(CNL)试验结果,运用Image Pro Plus等图像处理软件,同时通过室内剪切试验和数值模拟双向验证所揭示规律的可靠性.在206 kPa的法向应力下对4种结构的粗粒土进行剪切试验,以一组骨架密实结构数据为算例,利用多项式拟合试验结果,对比分析数值模拟和室内剪切试验排列熵变化结果.研究结果表明:剪切初期,粗粒土的排列熵随剪应力的增加呈先增大后减小的趋势,在达到峰值后随着剪应力的缓慢减小表现为先增大后减小的趋势.随着粗颗粒含量的升高,粗粒土结构发生变化,排列熵值增大,同时其排列分布的有序性受剪切作用的影响越大.

Considering the uncertainty of particle distribution, M-C method is introduced in the calculation of permutation entropy to characterize the degree of permutation chaos. To explore the coarse grained soil shear permutation entropy evolution rule, in the process of P5 coarse particle content as indexes, four different types of coarse grained soil structure were set up as the research object, in combination with shear test under normal stress(CNL)test results, using the image processing software, such as the Image Pro Plus through indoor shear test and numerical simulation of two-way authentication at the same time reveals the reliability of the law. Under the normal stress of 206 kPa, shear tests were carried out on coarse grained soil with four kinds of structures. A set of dense skeleton structure data is taken as an example, and polynomial fitting test results are used to compare and analyze the results of permutation entropy change in numerical simulation and laboratory shear test. Results show that the permutation entropy of coarse-grained soil increases first and then decreases with the increase of shear stress at the initial stage of shear stress, and increases first and then decreases with the slow decrease of shear stress after reaching the peak. With the increase of coarse grain content, the structure of coarse grain soil changs, the permutation entropy increases. Meanwhile the ordering of its permutation distribution is greatly affected by shear.

引言
1 粗粒土颗粒排列熵计算方法
2 试验方案
3 试验数据分析
4 结论

图1 颗粒剪切分析模型<br/>Fig.1 Particle shear analysis model

图1 颗粒剪切分析模型
Fig.1 Particle shear analysis model

图2 颗粒主定向角示意图[18]<br/>Fig.2 Schematic diagram of particle main orientation angle

图2 颗粒主定向角示意图[18]
Fig.2 Schematic diagram of particle main orientation angle

图3 剪应力-位移对比曲线<br/>Fig.3 Shear stress-displacement relation curve

图3 剪应力-位移对比曲线
Fig.3 Shear stress-displacement relation curve

图4 试验材料
Fig.4 Test material

表1 材料颗粒级配<br/>Tab.1 Material particle grading

表1 材料颗粒级配
Tab.1 Material particle grading

图5 土体颗粒识别标记、形态测量过程图<br/>Fig.5 The process diagram of soil particle identification and morphological measurement

图5 土体颗粒识别标记、形态测量过程图
Fig.5 The process diagram of soil particle identification and morphological measurement

图6 4种颗粒单元形状<br/>Fig.6 Four particle unit shapes

图6 4种颗粒单元形状
Fig.6 Four particle unit shapes

表2 模型参数
Tab.2 Model parameters

图7 主定向角概率分布图<br/>Fig.7 Probability distribution diagram of angle

图7 主定向角概率分布图
Fig.7 Probability distribution diagram of angle

图8 排列熵与剪应力拟合曲线<br/>Fig.8 Fitting curve of permutation entropy and shear stress

图8 排列熵与剪应力拟合曲线
Fig.8 Fitting curve of permutation entropy and shear stress

图9 数值模拟和室内试验的比较<br/>Fig.9 The comparison between thenumerical modeling and the laboratory test

图9 数值模拟和室内试验的比较
Fig.9 The comparison between thenumerical modeling and the laboratory test

图10 排列熵变化规律<br/>Fig.10 Permutation entropy change rule

图10 排列熵变化规律
Fig.10 Permutation entropy change rule

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备注

引言

1 粗粒土颗粒排列熵计算方法

2 试验方案

3 试验数据分析

4 结论

期刊信息