粗粒土压实特性及颗粒破碎分形特征试验研究

对多个级配不同含水率的粗粒土进行击实试验,研究粗粒土的压实特性和颗粒破碎分形特征。结果表明,粗粒土最大干密度随级配中粗粒含量的增大而增大,当粗粒含量P5=70%时,最大干密度出现最大值;当P5＞70%时,最大干密度又随粗粒含量的增大而减小,粗粒土击实破碎后的粒径分布具有良好的分形特性,破碎分形维数为2.279 0～2.892 2,均大于击实前粗粒土粒度分形维数;相同级配条件下,粗粒土破碎分形维数随含水率的增大而增大,且粗粒含量P5＞50%时,增幅显著;粗粒土破碎分形维数D与破碎率Bg存在良好的线性关系,且击实前后粗粒土粒度分形维数差值能客观表征颗粒破碎的程度;粗粒含量和含水率是影响颗粒破碎率的两个重要因素,但相对于含水率而言,粗粒含量对破碎率的影响更加显著。     

采用土壤孔隙表面分形维数预测土壤水分特征曲线

采用土壤颗粒体积累积曲线按照不同的粒径分级方法计算表面分形维数,避免了原始计算过程中颗粒密度不变的假设,改进了计算中的缺陷。结合土壤水分特征曲线分形模型—de Gennes模型,预测试样的SWRC。结果发现:不同颗粒分级只会影响表面分形维数的大小;相同颗粒分级情况下,计算得出的分形维数随着土壤粘粒含量降低而减小;采用D2(最大半径为1mm)的分级情况计算出的表面分形维数,预测得出的结果与实测值相差偏大,RMSE≥2.11E-02cm3/cm3只适合粗略估计田间土壤的水分特征曲线;通过D1(最大半径为0.1mm)计算出的表面分形维数,结合de Gennes模型预测水分特征曲线结果与实测值非常接近,RMSE≤0.0105cm3/cm3。研究表明采用土壤颗粒体积累积曲线计算表面分形维数,并预测土壤水分特征曲线是合理的,具有较高的预测精度。     

基于压汞分形的高变质石煤孔渗特征分析

研究石煤（腐泥煤）的孔渗特征,对于深入了解页岩气的吸附/解吸特征具有重要意义。基于分形几何原理,推导出煤岩不同类型孔隙和毛细管压力曲线的分形几何模型,并将孔隙分形维数分为渗透分维数和扩散分维数分别计算。根据压汞实验数据分析,利用双对数图计算了安康地区石煤孔隙结构的分形维数。研究结果表明:石煤渗透分维数D_s介于2.524~2.917,其与挥发分产率、水分含量、灰分产率和迂曲度呈正相关关系,与变质程度及平均孔径呈负相关关系;扩散分维数D_k介于2.488~2.931,其与变质程度、挥发分产率、水分含量和平均孔径呈正相关关系,与灰分产率和迂曲度呈负相关关系;在物性方面,渗透分维数随孔隙度增大而减小,渗透性的分形表征与扩散分维数呈负相关关系,这说明渗透孔越不均一,煤岩孔隙度就越大,而扩散孔的均一化程度可以为评价石煤储层物性提供重要依据。      

基于孔隙分形维数的土壤大孔隙流水力特征参数研究

根据数字图像制备分析技术得到大孔隙数目、大小和形状等特征数据,用分形理论计算孔隙分形维数,并对两类不同质地土壤的孔隙分形维数进行分析比较,应用基于孔隙分形维数的大孔隙分形模型,建立了土壤水分特征曲线和非饱和导水率的预测模型。结果表明,孔隙分形维数D_v可定量描述不同质地土壤结构,其模型预测精度优于颗粒大小分布估计的分形模型,可用于实际问题的研究。     

基于分形理论的堆石料级配优化研究

建立颗粒粒径的质量分布分形模型,收集不同堆石坝工程32条堆石料级配曲线,统计分形维数D的分布特性。各堆石坝工程堆石料级配具有良好的分形特性,可考虑将D作为反映和描述堆石料级配特性的新指标,D在2.348～2.699之间,大多数堆石料的分形维数在2.6左右。以古水垫层料为研究对象,设计了6组不同分形维数的级配曲线,采用随机颗粒不连续变形方法（SGDD）研究不同分形维数对堆石料压实性能和宏细观力学特性的影响。分形维数从2.0到2.8,孔隙比呈先减后增趋势,在D =2.7时压实性能最优,而力链的非均匀程度随分形维数的增大而增大。综合考虑试样压实性和力链的非均匀程度,确定D =2.7时的级配为优化级配。     

渝东南岩溶山区耕地利用变化下土壤颗粒体积分形特征研究

通过对重庆东南部喀斯特山区的野外调查采样和室内粒度分析,利用土壤颗粒体积分维模型,分析了该区域耕地土壤与撂荒地土壤颗粒体积分形维数特征,探讨了颗粒体积分形特征与颗粒体积含量的关系。研究结果表明:土壤颗粒体积分形维数与土壤中粘粒(<0.002mm)含量呈明显的线性相关,表现为粘粒含量越高的土壤,其分形维数也越高。土壤粘粒含量与土壤颗粒体积分形维数在不同土地利用方式的土壤剖面上表现出相同的变化规律。土壤分形维数不仅受粘粒含量的支配,还与土壤质地的均一程度有关,分形维数与土壤质地均匀指数表现出一定的相关性,但相关性较弱。耕地土壤分形维数值(平均值为2.5065)大于撂荒地分形维数值(平均值为2.4835),说明岩溶区人类农耕活动对土壤质地尤其是粘粒含量影响明显。土壤体积分形维数可以作为区域耕地土壤质量评价指标之一。      

基于SEM图像的既有地基红黏土颗粒微观结构及分形特征研究

采用IPP（Image-Pro Plus）图像分析软件对贵州省贵阳市某工厂三种既有地基红黏土SEM图像的信息进行提取和处理,定性描述和定量分析土体的微观结构,并引入分形理论分析SEM图像,提出在IPP软件中获取颗粒三维分形维数的计算方法。结果表明:（1）抗剪强度参数随微观颗粒数、颗粒形态比的增大而增大,随颗粒平均面积的增大而减小;（2）颗粒分布及形态均具有明显的分形特征,分形维数介于2~3之间,抗剪强度参数均随颗粒分布及形态分维值的增大而增大;（3）与构建三维模型的方法相比,利用IPP软件计算土颗粒三维分形维数的方法具有可行性,简单易操作,结果可靠。      

基于分形理论研究土壤结构及其水分特征关系

为定量获得土壤结构对其水力性质的指示作用,室内实验选用华北平原子牙河流域原状土样为研究对象,用张力计法和激光粒度分析仪分别测定土壤水分特征曲线和样品粒度分布,基于分形理论计算土壤粒度分布的分形维数,采用实验测定与模型验证相结合的方法对水分特征曲线进行分析.结果表明,土壤颗粒粒度分布在[10 μm,50 μm]区间内的分段分维值是表征土壤粒度累积分布显著上升段特征的关键参数,与0~80 kPa吸力范围内的土壤水分特征曲线幂函数模型拟合参数(a、b)有极显著相关关系.研究区内土壤水分特征曲线以分形形式表达的幂函数模型为:θ=100.78×(3-D)S(D-3)/3,利用土壤结构分形特征能够有效指示其水力性质.      

基于连续分形理论的土壤非饱和水力传导度的研究

土壤的孔隙是具有连续分形性质的物理结构,根据土壤孔隙分形结构建立了非饱和水力传导度模型。模型包括综合系数、分形维数和临界体积比3个参数,综合系数为不同土壤基质势对应的非饱和水力传导度与饱和传导度之间的水力联系,与土壤质地有关;分形维数反映土壤孔隙结构对于非饱和水力传导度的作用,土壤不同尺寸孔隙之间的连通性则通过临界体积加以描述。模型具有较为明确的物理解释。将模型应用于5种不同土壤的结果表明,所提出的非饱和水力传导度模型具有较好的模拟效果。     

辽河东部凸起太原组页岩孔隙分形特征

页岩孔隙结构具有良好的分形特征,孔隙结构的分形维数能定量描述孔隙结构的复杂程度。以辽河东部凸起为例,应用高压压汞方法研究了页岩孔隙结构及其不规则性,计算了页岩孔隙分形维数。研究结果表明,辽河东部凸起太原组页岩孔隙分形无标度区为0.09~60μm,孔隙分维数为2.378~3.007,随着分形维数的增大,页岩的非均质性增强,压汞实验得出的页岩孔径分布特征也证明了页岩的孔隙分形维数可以用来定量描述页岩储层岩石孔隙结构的微观非均质性;数学拟合表明分形维数与有机质含量相关性差,反映页岩中无机孔隙为主体孔隙类型;分形维数与石英含量呈较弱的正相关而与黏土矿物含量呈较强的负相关性,表明黏土矿物含量对页岩孔隙结构影响明显。分形维数与页岩的渗透率和孔隙度均具有很好的负相关性,分形维数越大,岩心的渗透率和孔隙度越小,表明分形维数越大,孔隙结构越趋于复杂,不利于气体的渗流和产出。     

确定田间土壤水力传导率的分形方法

采用了一种简便易行的分形方法来间接估计水力传导率函数,即根据土壤粒径分布曲线确定孔隙表面分形维数,将其作为分形水力传导率模型的参数来预测整个压力水头范围内的水力传导率.利用UNSODA数据库中217个样本的实测资料对模型进行检验,结果表明分形方法预测的水力传导率其精度明显高于根据水分特征曲线利用统计孔径分布模型的估计结果.     

非饱和土壤水力参数预测的分形模型

综述了利用分形几何理论,可在土壤水力性质,包括土壤水分特征曲线及水力传导系数与土壤结构分维之间建立起一定的函数关系式.这些函数关系式大多与Campbell定律具有相同或相似的幂定律形式,一方面揭示了Campbell定律的物理实质,另一方面可用于土壤持水量及水力传导系数的预测.     

几种土壤累积粒径分布模型的对比研究

土壤粒径分布是最基本的土壤物理性质。作为许多预测模型的输入参数,准确描述土壤的粒径分布是保证模拟质量的前提。评价了对数正态分布、三次样条、逻辑生长、改进逻辑生长以及van Genuchten方程等经验模型在描述土壤粒径分布中的适用情况。结果表明,改进的逻辑生长曲线模型预测效果最好,而广泛采用的对数正态分布的结果最差。其它3种模型的效果介于两者之间。根据5种粒径分布模型的模拟结果,利用分形方法来预测土壤水分特征曲线也得到了类似的结论。     

土−水特征曲线测量过程中孔隙分布的演化规律探讨

测量了在宽广吸力范围内原状样和压实样的脱湿持水曲线,对比分析了单双峰结构持水性能的差异;并利用压汞试验测试两种土样在脱湿过程的孔隙分布,分析了两者的差异并探讨了脱湿过程孔隙的演化规律;在考虑收缩变形的基础上,基于孔隙分布曲线确定了土?水特征曲线的基本参数。试验结果表明：原状样在宽广吸力范围内基本上呈单峰孔隙结构;饱和压实样具有单峰孔隙结构,随着吸力的增加,双峰结构越来越明显,当吸力达到很大时,演化成完全双峰孔隙结构。原状样的持水曲线为经典的S形,而压实样的持水曲线在过渡段出现了水平台阶状;低吸力段,压实样的持水曲线低于原状样,而高吸力段,两者的持水曲线基本重合。基于孔隙分布曲线确定了控制持水曲线进气值和残余值的孔径,并计算出对应的吸力值,其值更符合实际物理意义。     

A multi-gene genetic programming model for estimating stress-dependent soil water retention curves

Soil water retention curve (SWRC) is an important parameter required for seepage modelling in unsaturated soil and is used for analysing rainfall-induced slope failures, design of waste contaminant liners and cover, etc. The influence of stress, which is one of constitutive variables that governs unsaturated soil behaviour on the SWRC, has been well recognised by researchers. Stress is essential for study as it drastically alters the soil fabric which includes macropores, minipores and micropores and thus affects the ability of soil to retain water. Various computational modelling techniques that formulate models based on existing databases such as UNSODA, ISRIC and HYPRES for the estimation of SWRC do not take into account the stress influence on soil behaviour. In the present work, three artificial intelligence (AI) methods of support vector regression, artificial neural network and multi-gene genetic programming (MGGP) have been applied to formulate the mathematical relationship between the water content and input variables such as stress and suction (i.e. stress-dependent soil water characteristic curves (SDSWRCs)). The results indicate that the MGGP model outperforms the other two models and is able to extrapolate the water content values satisfactorily along the stress value of 800 kPa. This MGGP model can then be deployed by experts for the estimation of SDSWRCs, thus eliminating the need for conducting costly and time-consuming experiments.     

化学溶液作用下基于压实膨润土孔隙结构演化的土水特征模型研究

在高放废弃物深地质处置库复杂的地下水环境影响下,缓冲/回填材料微观孔隙结构的改变通常会大大影响其水力性质.为探究这种影响,众多学者从不同理论出发,建立了相应的土水特征模型.然而,针对这些模型的对比研究较少,且缺少将模型应用于考虑化学影响的情况.在压实膨润土微观结构分析的基础上,基于分形理论和双孔理论,分别构建了压实膨润...     

Fractal models for predicting soil hydraulic properties: a review

Modern hydrological models require information on hydraulic conductivity and soil-water retention characteristics. The high cost and large spatial variability of measurements makes the prediction of these properties a viable alternative. Fractal models describe hierarchical systems and are suitable to model soil structure and soil hydraulic properties. Deterministic fractals are often used to model porous media in which scaling of mass, pore space, pore surface and the size-distribution of fragments are all characterized by a single fractal dimension. Experimental evidence shows fractal scaling of these properties between upper and lower limits of scale, but typically there is no coincidence in the values of the fractal dimensions characterizing different properties. This poses a problem in the evaluation of the contrasting approaches used to model soil-water retention and hydraulic conductivity. Fractal models of the soil-water retention curve that use a single fractal dimension often deviate from measurements at saturation and at dryness. More accurate models should consider scaling domains each characterized by a fractal dimension with different morphological interpretations. Models of unsaturated hydraulic conductivity incorporate fractal dimensions characterizing scaling of different properties including parameters representing connectivity. Further research is needed to clarify the morphological properties influencing the different scaling domains in the soil-water retention curve and unsaturated hydraulic conductivity. Methods to functionally characterize a porous medium using fractal approaches are likely to improve the predictability of soil hydraulic properties.     

Continuous determination of drying-path SWRC of fine-grained soils

Establishing the soil water retention curve, SWRC or the soil water characteristic curve, SWCC, is very useful for determination of unsaturated properties of soils. However, it has been observed that SWRC of a soil is not unique and depends on various factors such as the initial moisture content, density of soil, method of compaction, soil fabric and the path (drying or wetting) adopted for establishing it. In this context, many techniques and instruments have been employed by earlier researchers for determination of the SWRC of soils. However, these techniques entail weighing of the samples during prolonged testing, manually, and hence yield discrete data points. In this situation, AquaSorp® Isotherm Generator (manufactured by Decagon Devices Inc., USA) has been found to be quite useful for continuous determination of the drying-path SWRC of fine-grained soils. This device has been primarily employed for food products, powders and amorphous materials. Hence, demonstration of the utility and limitations of this device for SWRC determination of fine-grained soils becomes essential. With this in mind, extensive studies were conducted on commercially available soils (Kaolinite and Bentonite) by employing this device. In order to understand the influence of specimen specific parameters on the obtained SWRCs, the molding water content and thickness of the specimens were varied and the results have been evaluated critically. Details of the methodology adopted for these investigations, and the findings of the study are presented in this technical note. Based on a critical comparison of the results obtained from this device with those obtained from the dewpoint potentiameter, WP4®, the utility of this device for continuous determination of drying-path SWRC of the soils has also been demonstrated.