共查询到19条相似文献，搜索用时 562 毫秒
1.
将土壤或含水层的介质参数视为随机分布,建立了饱和非饱和水流运动的随机微分方程,利用随机数值求解方法,得到各种随机参数对水头分布和含水量空间变异性的影响。分析结果表明,随着渗透系数空间变异性和相关尺度的增大,含水层水头分布的变异性增大;对于区域内有抽水井分布的问题,在井点附近区域,z向水流速度空间变异性大,而在井点处变异性较小。当采用Gardner-Russo模型描述非饱和水分特征时,其非饱和土壤介质参数α的变异性对土壤负压和含水量变异性的影响大于饱和渗透系数,土壤含水量越小,含水量的空间变异性越大。初步讨论了根据随机数值方法研究地下水运动问题的可靠性分析方法。 相似文献
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渗流场水头分布计算是进行渗流量和渗流水力坡降计算的基础,准确、有效地求取渗流场水头分布是渗流计算的关键环节。对均质非饱和土体一维稳态流的流动方程进行分析,考虑到渗透系数是与基质吸力相关的函数,通过数学变换,给出了稳定渗流场的解析通式,并基于渗透性函数中的Gardner模型,给出了非饱和土一维稳态流水头垂直分布的解析解。该解析通式表明,均质非饱和土一维稳态流水头垂直分布主要受地表水头、深度和流动率3个因素控制。分别计算了一维稳态蒸发条件下粉土和黏土两种典型土类水头沿垂直方向的分布。计算结果表明：稳态蒸发条件下粉土层和黏土层内的水头分布表现出相似的变化规律,即自地表至地下水位处随着土层深度的增加,水头分布呈现出加速递减的趋势;在相同的蒸发条件下,对于相同深度处的黏土和粉土而言,黏土层内水头更高些;对同一种土类而言,在较大的蒸发状态下同一深度处土层内水头更高。反之,则较低。 相似文献
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通过模拟均质和非均质两种情形下非饱和-饱和系统中压力水头的时空变化,研究非饱和-饱和系统对水流波动的 阻尼作用和系统非均质性对水流波动的作用。结果显示,两种情形下非饱和-饱和系统对水流波动均有阻尼作用,随深度 增加,压力水头波动减弱,方差、自协方差和功率谱减小;压力水头在早期因初始条件做非平稳波动,而后随时间增长演 变为平稳波动;系统的非均质性加剧了压力水头的波动,是波动的主要来源,使得压力水头方差、自协方差和功率谱增 大;非均质性减小压力水头波动的短期相关性。 相似文献
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以一水平向具有空间变异而垂直向为均质的二维非饱和流动区域中的均匀入渗问题为例,应用Monte Carlo随机模拟方法分析了土壤水分变量的随机统计特性及其一、二阶矩的时空分布规律。在随机分析过程中,将所研究的流动区域土壤水力特性的空间变异性以随空间位置变化的标定参数δ(x)表示,并将标定参数δ(x)视为一维随机空间函数的实现,应用随机生成模型来生成参数δ(x)的随机样本。通过随机模拟分析得到:垂直方向上负压水头方差与平均负压水头近似呈一线性关系;随入渗时间的延长,不同深度处表征负压水头空间变异结构的自相关函数趋于一稳定结构。 相似文献
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为反映非饱和地基土变形全过程,以某基础工程非饱和土为研究对象,开展固结排水三轴压缩试验。研究发现,非饱和土的偏应力-应变曲线形态近似双曲线,基质吸力对土体力学行为影响十分明显,基质吸力越大,土体偏应力越高。根据非饱和土变形特性及工程特点,选取邓肯-张双曲线模型作为基础模型,引入统计损伤理论,假设非饱和土微元强度服从Weibull概率密度分布,建立邓肯-张统计损伤模型。通过搭建初始切线模量与基质吸力的联系,建立一种新的考虑基质吸力的非饱和土邓肯-张统计损伤模型。给出参数解析方法,得到Weibull分布参数经验表达式,从而修正模型。分析不同基质吸力条件下非饱和土损伤累积规律,采用所建模型和传统邓肯-张模型对比验证非饱和土偏应力-应变试验曲线,证明所建模型的可行性和合理性。研究成果为非饱和土的力学特性研究及辨识模拟提供一定参考。 相似文献
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降雨入渗条件下边坡岩体饱和非饱和渗流计算 总被引：22，自引：2，他引：20
简要分析了连续介质饱和非饱和渗流数学模型,并讨论了渗流有限元计算中的有关问题,同时研究了降雨入渗机理及模拟方法,在此基础上编写了非饱和渗流程序SUSC。运用该程序模拟了某边坡降雨过程渗流场的变化情况。计算结果表明,在降雨入渗作用下边坡顶部迅速被饱和,随后表面雨水逐渐向边坡深部下渗,形成从坡顶往深部压力水头等值线由高(零)→低→高的封闭现象。随着降雨的继续,边坡顶部负压区进一步缩小,且负压绝对值减小。降雨结束后,由于上部地下水的继续下渗,在边坡的一定范围、一定时间内压力水头继续升高。根据计算结果可知,局部地方的压力水头最高值出现在降雨结束2 d左右,往后整个边坡非饱和区地下水压力水头全面下降,逐渐恢复原状。模拟结果总体可靠,可作为边坡稳定性分析评价及边坡排水加固的参考依据。同时表明,运用上述饱和非饱和渗流模型及降雨模拟方法,计算降雨条件下边坡岩体的渗流场是可行的。 相似文献
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不同初始孔隙比下非饱和黏土渗透性试验研究及模型预测 总被引：1，自引：0，他引：1
不同初始孔隙比下非饱和土渗透系数的试验测量及预测,是进行非饱和土渗流分析及水-力耦合研究的基础,相关工作具有重要的意义。以湖南邵阳红黏土为例,利用千斤顶制备5种不同初始孔隙密度塑土样;采用压力板仪测量其土-水特征曲线;选用变水头法测量其饱和渗透系数;自制有机玻璃桶试验装置,采用瞬态剖面法进行非饱和渗透试验,测量不同初始孔隙比土样的非饱和渗透系数。选用CCG(Childs和Collis-George)修正模型和陶-孔模型预测非饱和渗透系数,并与实测值进行比较,验证模型有效性。以上述试验及模型预测的成果为基础,研究初始孔隙比对非饱和(相对)渗透系数的影响规律。研究结果表明:湖南非饱和黏性土渗透系数随基质吸力增加而降低,在低基质吸力阶段(100 k Pa以内)变化较为剧烈,在高基质吸力阶段(100 kPa以上)变化较为缓慢;CCG模型预测误差较大,陶-孔模型预测值与实测值总体吻合较好;进气值之后,初始孔隙比对非饱和渗透系数的影响较小,对非饱和相对渗透系数的影响较大,相同基质吸力条件下初始孔隙比越小,相对渗透系数越大。 相似文献
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为了研究压实黄土中的水分垂直入渗规律和非饱和渗透系数函数,在实验室内利用一维土柱垂直入渗模型试验装置,对两组压实黄土土柱试样分别进行了常水头入渗和降雨入渗试验。得到主要结论如下:（1）常水头入渗试验中,累积入渗量和湿润锋前进距离都随入渗时间呈幂函数形式增长,累积入渗量和湿润锋前进距离之间存在线性关系。入渗率在入渗初期最大,之后随入渗时间而快速降低,并在土柱试样底部出水以后达到稳定,且与湿润锋前进距离呈反比关系。（2）降雨入渗试验中,得到两组试样入渗过程中土-水特征曲线数据,分别用van Genuchten模型和Fredlund-Xing模型对两组试样进行了特征曲线拟合。并利用瞬时剖面法处理了入渗过程中水分和水势传感器的监测数据,得到两组试样的非饱和渗透系数,并拟合得到非饱和渗透系数与体积含水率之间的指数函数关系式。同时,采用van Genuchten和Fredlund等渗透系数模型分别对两组试样的非饱和渗透系数进行预测,通过对比模型预测结果和瞬时剖面法实测值,发现van Genuchten渗透系数模型预测结果更接近实测值。 相似文献
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为探究冻融循环条件下初始含水率对膨胀土偏应力-应变关系和剪切特性的影响,本文对不同初始含水率的非饱和膨胀土进行了不固结不排水三轴剪切试验。结果表明：1）非饱和膨胀土的偏应力-应变曲线的形式随含水率增大由应变软化逐渐转变为应变硬化,偏应力峰值随含水率增大而降低;2）非饱和膨胀土的抗剪强度随初始含水率的增加呈线性下降趋势;3）非饱和膨胀土在第1次冻融循环后偏应力及抗剪强度大幅度下降,在3~7次冻融循环后达到稳定。初始含水率是影响非饱和膨胀土力学性质的主要原因。 相似文献
11.
Lin Y. Hu 《Mathematical Geology》2002,34(8):953-963
Gradual deformation is a parameterization method that reduces considerably the unknown parameter space of stochastic models. This method can be used in an iterative optimization procedure for constraining stochastic simulations to data that are complex, nonanalytical functions of the simulated variables. This method is based on the fact that linear combinations of multi-Gaussian random functions remain multi-Gaussian random functions. During the past few years, we developed the gradual deformation method by combining independent realizations. This paper investigates another alternative: the combination of dependent realizations. One of our motivations for combining dependent realizations was to improve the numerical stability of the gradual deformation method. Because of limitations both in the size of simulation grids and in the precision of simulation algorithms, numerical realizations of a stochastic model are never perfectly independent. It was shown that the accumulation of very small dependence between realizations might result in significant structural drift from the initial stochastic model. From the combination of random functions whose covariance and cross-covariance are proportional to each other, we derived a new formulation of the gradual deformation method that can explicitly take into account the numerical dependence between realizations. This new formulation allows us to reduce the structural deterioration during the iterative optimization. The problem of combining dependent realizations also arises when deforming conditional realizations of a stochastic model. As opposed to the combination of independent realizations, combining conditional realizations avoids the additional conditioning step during the optimization process. However, this procedure is limited to global deformations with fixed structural parameters. 相似文献
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J. A. Vargas-Guzmán 《Mathematical Geology》2004,36(3):307-322
This paper introduces geostatistical approaches (i.e., kriging estimation and simulation) for a group of non-Gaussian random fields that are power algebraic transformations of Gaussian and lognormal random fields. These are power random fields (PRFs) that allow the construction of stochastic polynomial series. They were derived from the exponential random field, which is expressed as Taylor series expansion with PRF terms. The equations developed from computation of moments for conditional random variables allow the correction of Gaussian kriging estimates for the non-Gaussian space. The introduced PRF geostatistics shall provide tools for integration of data that requires simple algebraic transformations, such as regression polynomials that are commonly encountered in the practical applications of estimation. The approach also allows for simulations drawn from skewed distributions. 相似文献
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This work presents the application of a Monte Carlo simulation method to perform an statistical analysis of transient variably saturated flow in an hypothetical random porous media. For each realization of the stochastic soil parameters entering as coefficients in Richards' flow equation, the pressure head and the flow field are computed using a mixed finite element procedure for the spatial discretization combined with a backward Euler and a modified Picard iteration in time. The hybridization of the mixed method provides a novel way for evaluating hydraulic conductivity on interelement boundaries. The proposed methodology can handle both large variability and fractal structure in the hydraulic parameters. The saturated conductivity K
s and the shape parameter vg in the van Genuchten model are treated as stochastic fractal functions known as fractional Brownian motion (fBm) or fractional Gaussian noise (fGn). The statistical moments of the pressure head, water content, and flow components are obtained by averaging realizations of the fractal parameters in Monte Carlo fashion. A numerical example showing the application of the proposed methodology to characterize groundwater flow in highly heterogeneous soils is presented. 相似文献
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Dynamic stochastic estimation of physical variables 总被引：1，自引：0，他引：1
A fundamental problem facing the physical sciences today is analysis of natural variations and mapping of spatiotemporal processes. Detailed maps describing the space/time distribution of groundwater contaminants, atmospheric pollutant deposition processes, rainfall intensity variables, external intermittency functions, etc. are tools whose importance in practical applications cannot be overestimated. Such maps are valuable inputs for numerous applications including, for example, solute transport, storm modeling, turbulent-nonturbulent flow characterization, weather prediction, and human exposure to hazardous substances. The approach considered here uses the spatiotemporal random field theory to study natural space/time variations and derive dynamic stochastic estimates of physical variables. The random field model is constructed in a space/time continuum that explicitly involves both spatial and temporal aspects and provides a rigorous representation of spatiotemporal variabilities and uncertainties. This has considerable advantages as regards analytical investigations of natural processes. The model is used to study natural space/time variations of springwater calcium ion data from the Dyle River catchment area, Belgium. This dataset is characterized by a spatially nonhomogeneous and temporally nonstationary variability that is quantified by random field parameters, such as orders of space/time continuity and random field increments. A rich class of covariance models is determined from the properties of the random field increments. The analysis leads to maps of continuity orders and covariances reflecting space/time calcium ion correlations and trends. Calcium ion estimates and the associated statistical errors are calculated at unmeasured locations/instants over the Dyle region using a space/time kriging algorithm. In practice, the interpretation of the results of the dynamic stochastic analysis should take into consideration the scale effects. 相似文献
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Gaussian Cosimulation: Modelling of the Cross-Covariance 总被引：1，自引：0，他引：1
Dean S. Oliver 《Mathematical Geology》2003,35(6):681-698
Whenever two or more random fields are assumed to be correlated in reservoir characterization, it is necessary to generate valid cross-covariance models to describe the relationship. The standard methods for constructing covariance matrices for correlated random fields are not very general. In particular, they do not allow one to specify different auto-covariance models for the two fields. It is not possible, for example, for one field to have a Gaussian auto-covariance and the other an exponential auto-covariance, unless the two fields are uncorrelated. The standard approaches also do not allow for nonsymmetric cross-covariance functions. In this report, I present a straightforward method of cosimulation based on the square root of the auto-covariances. The same approach is used for constructing cross-covariance models for the variables. The approach is quite general and does not require symmetry of the cross-covariance. The modelling of the cross-covariance is illustrated with gamma ray and spontaneous potential logs. 相似文献
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Probabilistic analysis of underground rock excavations using response surface method and SORM 总被引：6，自引：0，他引：6
Probabilistic analysis of underground rock excavations is performed using response surface method and SORM, in which the quadratic polynomial with cross terms is used to approximate the implicit limit state surface at the design point. The response surface is found using an iterative algorithm and the probability of failure is evaluated using the first-order and the second-order reliability method (FORM/SORM). Independent standard normal variables in U-space are chosen as basic random variables and transformed into correlated non-normal variables in the original space of random variables for constructing the response surface. The proposed method is first illustrated for a circular tunnel with analytical solutions considering Mohr–Coulomb (M–C) and Hoek–Brown (H–B) yield criteria separately. The failure probability with respect to the plastic zone criterion and the tunnel convergence criterion are estimated from FORM/SORM and compared to those obtained from Monte Carlo Simulations. The results show that the support pressure has great influence on the failure probability of the two failure modes. For the M–C model, the hypothesis of uncorrelated friction angle and cohesion will generate higher non-performance probability in comparison to the case of negatively correlated shear strength parameters. Reliability analyses involving non-normal distributions are also investigated. Finally, an example of a horseshoe-shaped highway tunnel is presented to illustrate the feasibility and validity of the proposed method for practical applications where numerical procedures are needed to calculate the performance function values. 相似文献
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Water flow is greatly influenced by the characteristics of the domain through which the process occurs. It is generally accepted that earth materials have extreme variations from point to point in space. Consequently, this heterogeneity results in high variation in hydraulic properties of soil. In order to develop an accurate predictive model for transport processes in soil, the effects of this variability should be considered. In this study a two‐dimensional stochastic finite element flow model was developed for simulation of water flow through unsaturated soils. In this model, the stochastic partial differential governing equation of water flow, obtained from implementation of the perturbation‐spectral stochastic method on classical Richard's equation, was solved using a finite element method in the space domain and a finite difference scheme in the time domain. The effective hydrological parameters embedded in the mathematical model depend on time derivatives of capillary tension head; this makes possible to consider the hysteresis due to large‐scale variability of soil hydrological properties. The model is also capable of simulating infiltration and evaporation events and rapid change in the land surface boundary condition from one type event to another, based on a scheme used in the model for implementation of land surface boundary condition. The model was validated with the data obtained from a layered lysimeter test. The model was also used to simulate water flow under a long irrigation furrow. The results obtained with this model show better agreement with experimental measurements in comparison with a deterministic model. The possible reason for this agreement is that in the developed model, the influence of the variability of the properties of soil and effects of parameter hysteresis on water flow and water content redistribution are considered. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献