Classification of mineral deposits into types using mineralogy with a probabilistic neural network

In order to determine whether it is desirable to quantify mineral-deposit models further, a test of the ability of a probabilistic neural network to classify deposits into types based on mineralogy was conducted. Presence or absence of ore and alteration mineralogy in well-typed deposits were used to train the network. To reduce the number of minerals considered, the analyzed data were restricted to minerals present in at least 20% of at least one deposit type. An advantage of this restriction is that single or rare occurrences of minerals did not dominate the results. Probabilistic neural networks can provide mathematically sound confidence measures based on Bayes theorem and are relatively insensitive to outliers. Founded on Parzen density estimation, they require no assumptions about distributions of random variables used for classification, even handling multimodal distributions. They train quickly and work as well as, or better than, multiple-layer feedforward networks. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class and each variable. The training set was reduced to the presence or absence of 58 reported minerals in eight deposit types. The training set included: 49 Cyprus massive sulfide deposits; 200 kuroko massive sulfide deposits; 59 Comstock epithermal vein gold districts; 17 quartzalunite epithermal gold deposits; 25 Creede epithermal gold deposits; 28 sedimentary-exhalative zinc-lead deposits; 28 Sado epithermal vein gold deposits; and 100 porphyry copper deposits. The most common training problem was the error of classifying about 27% of Cyprus-type deposits in the training set as kuroko. In independent tests with deposits not used in the training set, 88% of 224 kuroko massive sulfide deposits were classed correctly, 92% of 25 porphyry copper deposits, 78% of 9 Comstock epithermal gold-silver districts, and 83% of six quartzalunite epithermal gold deposits were classed correctly. Across all deposit types, 88% of deposits in the validation dataset were correctly classed. Misclassifications were most common if a deposit was characterized by only a few minerals, e.g., pyrite, chalcopyrite,and sphalerite. The success rate jumped to 98% correctly classed deposits when just two rock types were added. Such a high success rate of the probabilistic neural network suggests that not only should this preliminary test be expanded to include other deposit types, but that other deposit features should be added     

多级判别在地震综合预报中的应用

本文阐述了多级判别在地震综合预报中应用的必要性,给出该数学方法的推导过程,并且以云南多震区——滇西南地震区为例进行实际判别计算,在所计算的工6个震例中其拟合预报准确率在80％以上;对1987年11月25日讯沧外.2级地震实际预报取得较好的效果。     

An efficient finite–discrete element method for quasi‐static nonlinear soil–structure interaction problems

An efficient finite–discrete element method applicable for the analysis of quasi‐static nonlinear soil–structure interaction problems involving large deformations in three‐dimensional space was presented in this paper. The present method differs from previous approaches in that the use of very fine mesh and small time steps was not needed to stabilize the calculation. The domain involving the large displacement was modeled using discrete elements, whereas the rest of the domain was modeled using finite elements. Forces acting on the discrete and finite elements were related by introducing interface elements at the boundary of the two domains. To improve the stability of the developed method, we used explicit time integration with different damping schemes applied to each domain to relax the system and to reach stability condition. With appropriate damping schemes, a relatively coarse finite element mesh can be used, resulting in significant savings in the computation time. The proposed algorithm was validated using three different benchmark problems, and the numerical results were compared with existing analytical and numerical solutions. The algorithm performance in solving practical soil–structure interaction problems was also investigated by simulating a large‐scale soft ground tunneling problem involving soil loss near an existing lining. Copyright © 2011 John Wiley & Sons, Ltd.     

基于3D-DIC技术岩石广义应力松弛特性试验研究

基于可视化三轴压缩伺服控制试验系统和三维数字图像相关技术(简称3D-DIC技术),开展了不同流变方向系数α下的广义应力松弛试验,对广义应力松弛过程中砂岩表面的应变演化规律进行了探讨。研究结果表明:在流变过程中若砂岩有发生破坏的趋势,其表面的轴向、径向应变场的应变集中区域逐步显现,轴向应变集中区域由层状离散分布逐渐向即将出现裂纹的位置集中,而径向应变场中在裂纹即将形成区域附近应变增长速率最快。不同表面位置轴向、径向应变差异的演化速率与其整体演化速率的变化趋势呈现正相关,在即将形成裂纹附近的轴向、径向应变变化量发展经历减速、等速、加速3个阶段,而远离裂纹处的应变则可能先增大后减小,不同位置应变值的等时曲线演化则预示裂纹即将形成的区域。随着流变方向系数α由0.3、0、-3.0、∞、3.0依次变迁,流变过程中轴向、径向应变场整体演化的均值与方差均上升,说明其演化速率加快,应变集中现象更显著,且砂岩破坏前后的应变场演化差异增大。     

Viscoelastic relaxation of the upper mantle and afterslip following the 2014 MW8.1 Iquique earthquake

An improved understanding of postseismic crustal deformation following large subduction earthquakes may help to better understand the rheological properties of upper mantle and the slip behavior of subduction interface. Here we construct a three-dimensional viscoelastic finite element model to study the postseismic deformation of the 2014 M_W8.1 Iquique, Chile earthquake. Elastic units in the model include the subducting slab, continental and oceanic lithospheres. Rheological units include the mantle wedge, the oceanic asthenosphere and upper mantle. We use a 2 ​km thick weak shear zone attached to the subduction fault to simulate the time-dependent stress-driven afterslip. The viscoelastic relaxation in the rheological units is represented by the Burgers rheology. We carry out grid-searches on the shear zone viscosity, thickness and viscosity of the asthenosphere, and they are determined to be 10¹⁷ ​Pa ​s, 110 ​km and 2 ​× ​10¹⁸ ​Pa ​s, respectively. The stress-driven afterlsip within the first two years is up to ~47 ​cm and becomes negligible after two years (no more than 5 ​cm/yr). Our results suggest that a thin, low-viscosity oceanic asthenosphere together with a weak shear zone attached to the fault are required to better reproduce the observed postseismic deformation.     

利用概率松弛法的城市路网自动匹配

多源空间数据匹配是空间数据集成与互操作,变化检测与数据更新的重要前提。路网数据匹配在导航、智能交通和基于位置服务等领域具有重要的研究意义和实用价值。本文提出一种基于概率松弛方法的城市路网自动匹配方法,该方法首先通过路段间几何差异性估算候选路段的初始概率,然后根据邻接候选匹配路段的兼容性不断更新原概率矩阵直到收敛于某一极小值。最后基于收敛的概率矩阵计算各候选路段的结构相似性,并通过设定相应的规则选取和提炼1: 1, 1: M和M: N匹配对。实验选取中国武汉,瑞士苏黎世地区的OpenStreetMap数据与导航数据进行匹配算法的验证。结果表明：本文算法对非刚性偏差较大的路网数据能达到较高精度,不存在匹配方向性问题,且能够识别1: 0, 1: M和M: N匹配。     

统计假设检验方法在全极化SAR变化检测中的应用

本文以全极化SAR数据为研究对象。由于全极化数据相干矩阵T3或协方差矩阵C3服从复wishart分布,所以首先在此分布的基础上利用统计假设检验方法构建似然比参数,用以表征地表地物的变化程度,然后利用基于广义高斯分布模型的EM迭代算法(GGM-EM)对变化信息进行初提取,最后充分考虑上下文信息,利用概率松弛迭代算法对初检测信息进行优化。该方法不仅全自动提取变化信息,而且经过非相干平均、初始分类、分类结果优化3次降斑去噪处理,因此检测精度较高。通过与传统对数比值法的比较,证明该方法的有效性。     

Development of a probabilistic approach for rock wedge failure

For rock slope engineering, uncertainty and variability are inherent in data collected on orientation and strength of discontinuities, yielding a range of results. Unfortunately, conventional deterministic analysis based on the factor of safety concept, requires a fixed representative value for each parameter without regard to the degree of uncertainty involved. Therefore, the deterministic analysis fails to properly represent uncertainty and variability, so common in engineering geology studies. To overcome this shortcoming, the probabilistic analysis method was proposed and used for more than a decade in rock slope stability analysis. However, most probabilistic analyses included a deterministic model as part of the analysis procedure causing subsequent problems, which went uncorrected. The objectives of this paper are to develop a solution for these difficulties in probabilistic analyses and to propose an appropriate simulation procedure for the probabilistic analysis of rock wedge failures. As part of the solution, probability of kinematic instability and probability of kinetic instability are evaluated separately to provide a proper, combined evaluation for failure probability. To evaluate the feasibility of this new probabilistic approach, the procedure is applied to a practical example, a major, highway rock cut in North Carolina, USA. Results of the probabilistic approach are compared to those of the deterministic analysis; findings are significantly different, indicating that the deterministic analysis does not depict rock slope variations, particularly where significant scatter in parameter data occurs.     

Evaluation of probabilistic flow in two unsaturated soils

A variably saturated flow model is coupled to a first-order reliability algorithm to simulate unsaturated flow in two soils. The unsaturated soil properties are considered as uncertain variables with means, standard deviations, and marginal probability distributions. Thus, each simulation constitutes an unsaturated probability flow event. Sensitivities of the uncertain variables are estimated for each event. The unsaturated hydraulic properties of a fine-textured soil and a coarse-textured soil are used. The properties are based on the van Genuchten model. The flow domain has a recharge surface, a seepage boundary along the bottom, and a no-flow boundary along the sides. The uncertain variables are saturated water content, residual water content, van Genuchten model parameters alpha (α) and n, and saturated hydraulic conductivity. The objective is to evaluate the significance of each uncertain variable to the probabilistic flow. Under wet conditions, saturated water content and residual water content are the most significant uncertain variables in the sand. For dry conditions in the sand, however, the van Genuchten model parameters α and n are the most significant. Model parameter n and saturated hydraulic conductivity are the most significant for the wet clay loam. Saturated water content is most significant for the dry clay loam. Electronic Publication     

核磁测井数据弛豫谱反演软件研究

简单介绍了核磁测井数据弛豫谱反演方法原理 ,用混合编程方法和动态连接库技术 ,将用FORTRAN语言编写的核心处理模块转换为动态连接库 ,并在C++语言中动态调用。应用快速应用程序开发工具完成了图形用户界面的核磁测井数据处理软件设计。