Delineation of groundwater protection zones by the backward particle tracking method: theoretical background and GIS-based stochastic analysis

The backward particle tracking method, an effective and powerful tool that can be used to delineate groundwater protection zones, is presented. The theoretical background and insights on the applicability of this method are provided. Moreover, the present work enriches the backward particle tracking method with an uncertainty analysis concerning the porosity values, applying a Monte Carlo (MC) approach, coupled with the use of geographical information systems (GIS). As an application example, a wellfield in the Komotini area, Greece, is investigated. The present study may serve as a potential guideline for wellfield delineation, particularly in areas like Greece where lack of data related to the hydrogeological system is often a problem.     

Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations

The 2004 Chuetsu earthquakes of Niigata (Japan) triggered numerous landslides, and the most widespread types of landslides were highly disrupted, relatively shallow slides and soil (debris) flows. This paper presented a method to evaluate slope instability using Newmark displacement on a pixel-by-pixel basis in a given area. The proposed method was able to integrate Newmark displacement modeling and Monte Carlo simulations within geographical information systems. In the modeling, an empirical attenuation relationship was utilized to calculate Arias intensity over this study area, and the variability of geotechnical parameters was taken into account to calculate coseismic landslide displacement. Before deriving the displacement from related inputs, the Monte Carlo simulations ran 1,500 times and generated 1,500 displacement values for each grid cell, and then means and standard deviations of displacement were calculated and probabilistic distributions can be obtained. Finally, given 10 cm as a threshold value of displacement, estimated probabilities of displacement exceeding 10 cm were shown as a map of seismic landslide hazards. The resulting hazard map was classified into four categories from very low to high level.     

随机误差传递与合成的蒙特卡罗模拟

对分析测试过程中随机误差的传递与合成进行了蒙卡罗模拟,并偏制了ＢＡＳＩＣ程序。该方法解决了当被合成误差不相互独立时泰勒级数公式所遇到的困难,当被合成误差相互独立时,与泰勒公式计算结果一致。     

江西永平铜矿区古构造应力场与构造演化

利用多重反演方法(Multiple Inverse Method,MIM)恢复永平铜矿多期古构造应力场,该方法可以划分形成断层擦痕的多个古构造应力期次.研究表明,永平矿区印支期以来至少受到3期古构造应力场作用,进而探讨了永平铜矿构造演化历史.第一期构造应力场为EW方向的近水平挤压,形成轴向近SN的褶皱,以及走向近南北的逆断层;第二期构造应力场为NW-SE方向近水平挤压,伴随着岩体的侵入,导致层间破碎带的矽卡岩化和矿体形成;第三期构造应力场为EW方向的再次挤压作用,造成控矿断层推覆距离加大,混合岩和矽卡岩破碎带向西逆冲推覆到晚古生代地层之上.     

地下水模型的Neumann展开Monte-Carlo随机有限元法

讨论了求解地下水模型(水流模型和水质模型)的Neumann展开Monte-Carlo随机有限元法。从基本的随机变量入手,避免了过程中随机变量的增多问题,给出结点水头(浓度)的均值、方差和水头在某区间的概率计算方法;改进了矩阵求逆的效率,对输入随机变量较多、随机变量变异较大的非稳定地下水问题特别有效。同时选取二维承压地下水水流问题(有解析解)作为例子,进行了随机数值模拟实验。     

示波极谱法测量电锌液中微量镍

提出在丁二酮肟-亚硝酸钠-氨水-氯化铵体系中,准确测定电锌液中微量镍的新方法:克服原子吸收光谱法测定微量镍回收率偏低问题。     

矿物晶体形态统计方法探讨

矿物晶体形态标型研究广泛应用于矿床成因研究和成矿预测工作,是成因矿物学研究中一个很重要的方面。文章以黄铁矿晶体形态统计为例,介绍了适用于简单晶体形态统计的形态统计法、适用于复杂晶体形态统计的习性统计法,以及根据实际观测实践提出的权重统计法。通过对这3种方法的比较,指出了不同方法的利弊,给出了根据不同研究目的及样品实际情况选择不同方法的建议。     

Importance sampling based algorithm for efficient reliability analysis of axially loaded piles

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. The local averaging subdivision technique is employed to generate random fields. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load–displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed importance sampling algorithm while maintaining the same accuracy as in the crude Monte Carlo method. Two examples are given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed importance sampling method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.     

Efficient generation of conditional simulations by chebyshev matrix polynomial approximations to the symmetric square root of the covariance matrix

Consider the problem of generating a realization y₁ of a Gaussian random field on a dense grid of points ₁ conditioned on field observations y₂ collected on a sparse grid of points ₂. An approach to this is to generate first an unconditional realization y over the grid =_{1 2}, and then to produce y₁ by conditioning y on the data y₂. As standard methods for generating y, such as the turning bands, spectral or Cholesky approaches can have various limitations, it has been proposed by M. W. Davis to generate realizations from a matrix polynomial approximations to the square root of the covariance matrix. In this paper we describe how to generate a direct approximation to the conditional realization y₁, on ₁ using a variant of Davis' approach based on approximation by Chebyshev polynomials. The resulting algorithm is simple to implement, numerically stable, and bounds on the approximation error are readily available. Furthermore we show that the conditional realization y₁ can be generated directly with a lower order polynomial than the unconditional realization y, and that further reductions can be achieved by exploiting a nugget effect if one is present. A pseudocode version of the algorithm is provided that can be implemented using the fast Fourier transform if the field is stationary and the grid ₁ is rectangular. Finally, numerical illustrations are given of the algorithm's performance in generating various 2-D realizations of conditional processes on large sampling grids.     

高拱坝施工初-中期导流风险模型及应用

面向工程设计阶段,采用高拱坝施工动态仿真技术获取施工初-中期挡水度汛面貌数据,综合考虑水文、水力随机性因素,构建高拱坝施工初-中期导流风险模型,提出采用Monte Carlo方法耦合挡水度汛面貌数据和主要随机因素进行风险模型求解的方法。基于风险分析原理提出了导流洞设计的风险判别方法,给出导流洞尺寸设计优化的数学模型和具体步骤。通过金沙江上游某高拱坝工程案例分析的结果表明:所提风险模型及求解方法是适用的、有效的,该模型能够得到整个施工初-中期导流风险率,较为客观地反映高拱坝施工中期度汛可能存在的两种挡水情况,克服了初期导流风险模型的局限性;施工中期导流风险率随导流洞尺寸增大而减小,导流洞尺寸设计的可行方案集存在界限,即优化方案。研究成果可为高拱坝施工导流的风险决策和设计优化提供理论支撑。