共查询到20条相似文献，搜索用时 46 毫秒
1.
D. Posa 《Mathematical Geology》1991,23(5):695-702
A natural extrapolation of stochastic operations (continuity and differentiation) already described in time domain (one-dimensional case) is established for spatial processes (two- or three-dimensional case). If stationarity decision is assumed, the continuity and differentiability (in the mean square sense) of a spatial process depends on the continuity and differentiability of the correlation function at the origin. Spatial processes described by stationary random functions are not continuous (in the mean square sense) when the covariance function presents a nugget effect, and they are not differentiable when the same covariance function is described by a spherical or an exponential covariance (models which are often used in geostatistics). 相似文献
2.
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
3.
Chunsheng Ma 《Mathematical Geosciences》2011,43(2):229-242
This paper studies vector (multivariate, multiple, or multidimensional) random fields in space and/or time with second-order
increments, for which the variogram matrix is an important tool to measure the dependence within each component and between
each pair of distinct components. We introduce an efficient approach to construct Gaussian or non-Gaussian vector random fields
from the univariate random field with higher dimensional index domain, and particularly to generate a class of variogram matrices. 相似文献
4.
《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2013,7(3-4):207-217
The present study comprises Monte-Carlo simulation assisted analysis of foundations resting on reinforced earth beds using the concept of beams on an elastic foundation, treating the modulus of subgrade reaction (MSR) as a stationary stochastic field characterised by mean, variance, autocorrelation function (ACF) and the autocorrelation distance (ACD). Realisations of the MSR, generated by solving a stochastic differential equation, are fed to a deterministic distributed parameter model to generate realisations of two dependent stochastic fields, namely deflection and bending moment in the foundation beam, and two random variables, namely the location of occurrence of maximum deflection and the bending moment. Subsequently these realisations are analysed to evolve probability distribution functions, variance and ACF of the dependent stochastic fields and the random variables. It is revealed that the ACF of these fields is independent of the ACF of the MSR. Further, variance of deflection is found to increase as the ACD of the MSR increases, implying requirement of a larger factor of safety when random soils display low frequency (macro level) variations. On the other hand, variance of the bending moment is larger at smaller ACDs of the MSR, indicating that for bending moments a larger factor of safety is required when the random soils display high frequency (micro level) variations. 相似文献
5.
P. Juan J. Mateu M.M. Jordan J. Mataix-Solera I. Meléndez-Pastor J. Navarro-Pedreño 《Journal of Geochemical Exploration》2011
The problem of estimating and predicting spatial distribution of a spatial stochastic process, observed at irregular locations in space, is considered in this paper. Environmental variables usually show spatial dependencies among observations, with lead one to use geostatistical methods to model the spatial distributions of those observations. This is particularly important in the study of soil properties and their spatial variability. In this study geostatistical techniques were used to describe the spatial dependence and to quantify the scale and intensity of spatial variations of soil properties, which provide the essential spatial information for local estimation. In this contribution, we propose a spatial Gaussian linear mixed model that involves (a) a non-parametric term for accounting deterministic trend due to exogenous variables and (b) a parametric component for defining the purely spatial random variation due possibly to latent spatial processes. We focus here on the analysis of the relationship between soil electrical conductivity and Na content to identify spatial variations of soil salinity. This analysis can be useful for agricultural and environmental land management. 相似文献
6.
渗流场随机性的随机有限元分析 总被引：3，自引：0，他引：3
基于一阶Taylor随机有限元法,推导出相应的渗流场随机分析中渗流响应量（水头和水力梯度）的随机响应公式,进而实现三维稳定渗流场随机有限元分析,并编制了相应的程序。在分析中,将渗流区域材料的渗透张量视为三维各向异性随机场,利用三维可分离向量随机场的局部平均法对随机场进行离散,根据参数选取的不同,可以离散出不同数量的随机变量。最后,给出一个算例,对离散出随机变量数量不同的情况分别进行随机分析,将分析结果和仅仅将渗透张量视为三维随机变量得到的结果对比,验证了所提方法的可行性。 相似文献
7.
圆洞弹性随机位移场的拟解析表达 总被引：2，自引：0，他引：2
研究弹性随机介质中圆形洞室的随机位移场的解析原理，并给出了无衬砌圆洞随机位移场的拟解析式及其统计特征。可作为随机场数值计算方法的参考算例。 相似文献
8.
Xavier Emery 《Mathematical Geosciences》2008,40(1):83-99
This paper presents random field models with Gaussian or gamma univariate distributions and isofactorial bivariate distributions,
constructed by composing two independent random fields: a directing function with stationary Gaussian increments and a stationary
coding process with bivariate Gaussian or gamma distributions. Two variations are proposed, by considering a multivariate
directing function and a coding process with a separable covariance, or by including drift components in the directing function.
Iterative algorithms based on the Gibbs sampler allow one to condition the realizations of the substitution random fields
to a set of data, while the inference of the model parameters relies on simple tools such as indicator variograms and variograms
of different orders. A case study in polluted soil management is presented, for which a gamma model is used to quantify the
risk that pollutant concentrations over remediation units exceed a given toxicity level. Unlike the multivariate Gaussian
model, the proposed gamma model accounts for an asymmetry in the spatial correlation of the indicator functions around the
median and for a spatial clustering of high pollutant concentrations. 相似文献
9.
Digital simulation of multivariate two- and three-dimensional stochastic processes with a spectral turning bands method 总被引：3，自引：0，他引：3
Aristotelis Mantoglou 《Mathematical Geology》1987,19(2):129-149
The space domain version of the turning bands method can simulate multidimensional stochastic processes (random fields) having particular forms of covariance functions. To alleviate this limitation a spectral representation of the turning bands method in the two-dimensional case has shown that the spectral approach allows simulation of isotropic two-dimensional processes having any covariance or spectral density function. The present paper extends the spectral turning bands method (STBM) even further for simulation of much more general classes of multidimensional stochastic processes. Particular extensions include: (i) simulation of three-dimensional processes using STBM, (ii) simulation of anisotropic two- or three-dimensional stochastic processes, (iii) simulation of multivariate stochastic processes, and (iv) simulation of spatial averaged (integrated) processes. The turning bands method transforms the multidimensional simulation problem into a sum of a series of one-dimensional simulations. Explicit and simple expressions relating the cross-spectral density functions of the one-dimensional processes to the cross-spectral density function of the multidimensional process are derived. Using such expressions the one-dimensional processes can be simulated using a simple one-dimensional spectral method. Examples illustrating that the spectral turning bands method preserves the theoretical statistics are presented. The spectral turning bands method is inexpensive in terms of computer time compared to other multidimensional simulation methods. In fact, the cost of the turning bands method grows as the square root or the cubic root of the number of points simulated in the discretized random field, in the two- or three-dimensional case, respectively, whereas the cost of other multidimensional methods grows linearly with the number of simulated points. The spectral turning bands method currently is being used in hydrologic applications. This method is also applicable to other fields where multidimensional simulations are needed, e.g., mining, oil reservoir modeling, geophysics, remote sensing, etc. 相似文献
10.
11.
12.
Towards Stochastic Time-Varying Geological Modeling 总被引：3，自引：1，他引：2
Guillaume Caumon 《Mathematical Geosciences》2010,42(5):555-569
The modeling of subsurface geometry and properties is a key element to understand Earth processes and manage natural hazards
and resources. In this paper, we suggest this field should evolve beyond pure data fitting approaches by integrating geological
concepts to constrain interpretations or test their consistency. This process necessarily calls for adding the time dimension
to 3D modeling, both at the geological and human time scales. Also, instead of striving for one single best model, it is appropriate
to generate several possible subsurface models in order to convey a quantitative sense of uncertainty. Depending on the modeling
objective (e.g., quantification of natural resources, production forecast), this population of models can be ranked. Inverse
theory then provides a framework to validate (or rather invalidate) models which are not compatible with certain types of
observations. We review recent methods to better achieve both stochastic and time-varying geomodeling and advocate that the
application of inversion should rely not only on random field models, but also on geological concepts and parameters. 相似文献
13.
Practical Calculation of Non-Gaussian Multivariate Moments in Spatiotemporal Bayesian Maximum Entropy Analysis 总被引：1，自引：0，他引：1
During the past decade, the Bayesian maximum entropy (BME) approach has been used with considerable success in a variety of geostatistical applications, including the spatiotemporal analysis and estimation of multivariate distributions. In this work, we investigate methods for calculating the space/time moments of such distributions that occur in BME mapping applications, and we propose general expressions for non-Gaussian model densities based on Gaussian averages. Two explicit approximations for the covariance are derived, one based on leading-order perturbation analysis and the other on the diagrammatic method. The leading-order estimator is accurate only for weakly non-Gaussian densities. The diagrammatic estimator includes higher-order terms and is accurate for larger non-Gaussian deviations. We also formulate general expressions for Monte Carlo moment calculations including precision estimates. A numerical algorithm based on importance sampling is developed, which is computationally efficient for multivariate probability densities with a large number of points in space/time. We also investigate the BME moment problem, which consists in determining the general knowledge-based BME density from experimental measurements. In the case of multivariate densities, this problem requires solving a system of nonlinear integral equations. We refomulate the system of equations as an optimization problem, which we then solve numerically for a symmetric univariate pdf. Finally, we discuss theoretical and numerical issues related to multivariate BME solutions. 相似文献
14.
The dissolution of Iceland spar in CO2-saturated solutions at 25°C and 1 atm total pressure has been followed by measurement of pH as a function of time. Surface concentrations of reactant and product species have been calculated from bulk fluid data using mass transport theory and a model that accounts for homogeneous reactions in the bulk fluid. The surface concentrations are found to be close to bulk solution values. This indicates that calcite dissolution under the experimental conditions is controlled by the kinetics of surface reaction. The rate of calcite dissolution follows an empirical second order relation with respect to calcium and hydrogen ion from near the initial condition (pH 3.91) to approximately pH 5.9. Beyond pH 5.9 the rate of surface reaction is greatly reduced and higher reaction orders are observed. Calculations show that the rate of calcite dissolution in natural environments may be influenced by both transport and surface-reaction processes. In the absence of inhibition, relatively short times should be sufficient to establish equilibrium. 相似文献
15.
This paper aims to provide a stochastic response surface method (SRSM) that can consider non-Gaussian dependent random variables under incomplete probability information. The Rosenblatt transformation is adopted to map the random variables from the original space into the mutually independent standard normal space for the stochastic surrogate model development. The multivariate joint distribution is reconstructed by the pair-copula decomposition approach, in which the pair-copula parameters are retrieved from the incomplete probability information. The proposed method is illustrated in a tunnel excavation example. Three different dependence structures characterized by normal copulas, Frank copulas, and hybrid copulas are respectively investigated to demonstrate the effect of dependence structure on the reliability results. The results show that the widely used Nataf transformation is actually a special case of the proposed method if all pair-copulas are normal copulas. The effect of conditioning order is also examined. This study provides a new insight into the SRSM-based reliability analysis from the copula viewpoint and extends the application of SRSM under incomplete probability information. 相似文献
16.
Bayes约束随机场下坝基溶蚀区随机模拟方法及其影响分析 总被引：1，自引：0，他引：1
基于完全随机场模拟溶蚀岩体可能会高估其空间变异性和不能有效地利用溶蚀以外的地质信息和实践经验,提出用Bayes约束参数随机场模型描述坝基溶蚀区的随机模拟方法。引入Bayes公式,对溶蚀区域岩土参数的统计特性进行修正,反映出地质勘测的新增地质信息和试验参数信息,建立约束随机场,并在此基础上进行随机有限元分析,研究坝基溶蚀对大坝结构性态的作用效应。计算结果表明,相对于完全随机场模型,Bayes约束随机场模型更为客观地考虑了溶蚀岩体的空间变异性,有效地降低了溶蚀参数完全随机场下结构响应的模拟方差。在概率分析过程中,推荐蒙特卡洛响应面耦合方法（MC-RSM）作为适用于复杂工程的随机模拟方法,该方法能够代替直接MC法对同样力学机制的不断重复,减小计算时间成本。 相似文献
17.
针对浙东沿海地区陆海不同介质采样区地球化学图中出现的自然因素,以及非点源污染和点源污染等因素引起的随机变异,提出选择一种适宜的数据处理模型和色区空间分配为内容的陆海不同介质地球化学成图方法,以改善图面效果。 相似文献
18.
给出分析各向异性非均质稳定随机渗流场问题的三维有限元模型;结合实际工程问题,统计分析长江荆南干堤士性参数的分布特征,通过Kolomogorov-Smirnov统计检验表明,渗透系数呈高斯分布假设可以接受;通过对长江荆南干堤随机渗流场的三维有限元统计模拟的数值分析,研究长江荆南干堤渗流场的各种随机特性,并进一步对随机模拟结果进行统计检验,验证模拟结果的合理性;在实际的分析研究中把上下游水位的随机波动引入三维有限元的随机分析模型,分析上下游水位的变异性对渗流场矢量的随机干扰和边界条件的随机性对随机渗流场分析结果变异性的影响。在此基础上进一步考虑施加诸如垂直截渗墙、下游导渗沟等抗渗措施后,它们作为复杂边界条件的扰动,在与场内土性参数的变异性共同影响下,对渗流场水头势分布的随机干扰特性,并与相应的确定性稳定渗流场问题的结果对比,证实随机渗流场研究的必要性、可行性及实用性。实现了对长江荆南干堤的三维渗流场的较为全面的随机场模拟及特性分析,分析得到的结论通过统计检验并结合实测工程数据对照证明是可靠的,所研制的程序是适用的。 相似文献
19.
以模糊随机变量理论为指导,视模糊随机变量的均值为模糊数,基于小样本理论推导了均值模糊数模糊变化范围与样本数的关系式。采用截集敏感性分析法进行了边坡稳定的模糊随机有限元可靠度分析,得到了边坡的模糊随机可靠指标及模糊滑面的位置,研究了样本数与边坡模糊随机可靠指标的关系。分析表明,基于模糊随机变量理论的模糊随机可靠度分析方法是随机可靠度分析方法的自然推广;模糊随机可靠指标与样本数有关,随着样本数的改变,模糊随机可靠指标的中值也会发生微小变化,不是定值;在相同的置信度情况下,模糊随机可靠指标的变化范围随着样本数的增加而减小,可通过增加样本数的方式来减小模糊随机可靠指标的模糊性。 相似文献
20.
George A. Griffiths 《Mathematical Geology》1982,14(1):65-75
Bayesian inference modeling may be applied to empirical stochastic prediction in geomorphology where outcomes of geomorphic processes can be expressed by probability density functions. Natural variations in process outputs are accommodated by the probability model. Uncertainty in the values of model parameters is reduced by considering statistically independent prior information on long-term, parameter behavior. Formal combination of model and parameter information yields a Bayesian probability distribution that accounts for parameter uncertainty, but not for model uncertainty or systematic error which is ignored herein. Prior information is determined by ordinary objective or subjective methods of geomorphic investigation. Examples involving simple stochastic models are given, as applied to the prediction of shifts in river courses, alpine rock avalanches, and fluctuating river bed levels. Bayesian inference models may be applied spatially and temporally as well as to functions of a random variable. They provide technically superior forecasts, for a given shortterm data set, to those of extrapolation or stochastic simulation models. In applications the contribution of the field geomorphologist is of fundamental quantitative importance. 相似文献