硫氰酸盐分光光度法测定岩石中三氧化钨不确定度的评定

通过对硫氰酸盐光度法测定岩石中三氧化钨不确定度的评定,建立数学模型,分析不确定度来源,对产生不确定度分量做了较为细致的阐述,求出合成标准不确定度和扩展不确定度,给出相应的表示方法。     

Particle size distribution analysis of sand-sized particles by laser diffraction: an experimental investigation of instrument sensitivity and the effects of particle shape

Laser diffraction is now widely used for particle size distribution analysis of sediments and soils. The technique can be very precise, and offers advantages of speed and cost over many other methods when used to analyse mixtures of sand, silt and clay. This study presents the results of an experimental investigation that examined the sensitivity of the Beckman-Coulter LS230 instrument to mixtures of different grain populations and differences in particle shape. The instrument was found to have high sensitivity to coarse particles in a finer matrix (detection threshold 1–2%), but much lower sensitivity to finer particles in a coarser mixture (detection threshold 12–17%). Experiments using near-spherical ballotini showed that laser analysis provides very similar values to dry sieving for the mean, median and mode, but for a range of natural sand samples values for the mean, median and mode were offset by 8–21%, with an average of ca 15%, compared with sieving. Analysis using a Beckman-Coulter RapidVUE instrument, which provides both size and shape information, provided support for the hypothesis that the differences between laser analysis and sieving are partly attributable to the effects of particle shape. However, an additional factor is the way in which the laser software interprets the optical diffraction data. The software predicts a high degree of log-normality in the size distribution, such that highly skewed, truncated or bimodal samples are poorly represented. Experiments using sieved fractions of ballotini indicated that, even with near-perfectly spherical particles, the particle size distribution predicted by the laser software includes a relatively large percentage of particles outside the sieve class limits.     

Uncertainty analysis of HEC-HMS model using the GLUE method for flash flood forecasting of Mekerra watershed,Algeria

In this paper, the lumped quasi-distributed hydrological model HEC HMS is used to simulate the rainfall–runoff process of the Mekerra watershed, located in the northwest of Algeria. The model parameters’ uncertainty and the predictive intervals were evaluated with the generalized likelihood uncertainty estimation (GLUE) approach. According to the results, good simulations were obtained with different values of variables for many sets of parameters generated randomly by the Monte Carlo procedure, which is known as Equifinality. After the analysis, only the hydraulic conductivity at saturation parameter appears well defined, taking values within a limited range. In addition, results indicated that combinations of likelihood measures associated with multiple and different periods of observations reduce a posterior uncertainty of estimated parameters and predictive intervals in some degree. Overall, the GLUE analysis showed that there is a significant uncertainty associated with hydrological modelling of watershed Mekerra, to a great extent due to multiple sources of errors.     

地质标准物质的粒度测量与表征实践

样品粒度是粉体地质标准物质的一项重要特性指标。长期以来地质标准物质的粒度一直是采用筛分法或沉降法检测,最终大多以加工样品通过一定筛目(一般为-200目)的比例来表达;近年来超细标准物质研制引入了以激光粒度仪为代表的粒度检测与分析的现代方法,并可以直观的粒度分布图和简洁明晰的特征粒径等多种方法来表达粒度分布特征,大大提升了粉体地质标准物质粒度分布特性的测量及表征水平。文章在前期采用激光粒度仪测量超细标准物质粒度分布特征工作的基础上,用此法测量了当今广泛使用的典型地质标准物质的粒度分布,为这些标准物质的正确使用和取样不确定度评价提供了重要依据;同时就今后地质标准物质乃至地质分析样品的粒度检测与表征提出建议。     

基于海明贴近度的模糊物元模型在孝妇河水质评价中的应用

河流污染已成为全球范围内普遍存在的环境问题之一。鉴于河流水质评价中存在的不确定性和模糊性,本文在物元分析的基础上,将海明贴近度和模糊物元分析理论相结合,建立了基于海明贴近度的河流水质评价模糊物元模型。运用该模型对孝妇河水质进行评价,结果表明：得到的评价样本与标准样本两者相互接近的程度能够比较客观的反映河流的水质状况,与实际情况吻合较好;运用熵权法确定评价指标的权重,考虑了各监潮指标的差异程度,减少了计算主观性的干扰,使评价结果更加准确合理。     

饱和砂土中水层形成及演化分析

分析了饱和砂土中水层的形成过程及各相响应量的发展演化过程,结果表明:如果砂层失去骨架的强度,且未被堵塞,则不会存在稳定的水层;如果堵塞延续,则形成的水层会逐渐扩张,否则水层先张开然后逐渐闭合。孔隙水流速、颗粒速度和孔压在堵塞初期有间断,间断会随着堵塞的消失而消失。     

基于参数优化的集对分析月径流预测

采用集对分析法进行月径流预报时,针对级别划分较多时不易确定差异度分量系数的问题,建立了基于SCEM-UA算法优化该系数的月径流预报方法.研究实例表明,本方法能够有效区分集对间不同差异度的影响,优化所得的差异度分量系数是有效的、合理的,能够提高月径流预报精度并发布概率预报.此外,分析表明集对分析预报中的参数不确定性在模型不确定性中占主导地位.     

Neural network modeling for regional hazard assessment of debris flow in Lake Qionghai Watershed, China

This paper presents a neural network (NN) based model to assess the regional hazard degree of debris flows in Lake Qionghai Watershed, China. The NN model was used as an alternative for the more conventional linear model MFCAM (multi-factor composite assessment model) in order to effectively handle the nonlinearity and uncertainty inherent in the debris flow hazard analysis. The NN model was configured using a three layer structure with eight input nodes and one output node, and the number of nodes in the hidden layer was determined through an iterative process of varying the number of nodes in the hidden layer until an optimal performance was achieved. The eight variables used to represent the eight input nodes include density of debris flow gully, degree of weathering of rocks, active fault density, area percentage of slope land greater than 25° of the total land (APL25), frequency of flooding hazards, average covariance of monthly precipitation by 10 years (ACMP10), average days with rainfall >25 mm by 10 years (25D10Y), and percentage of cultivated land with slope land greater than 25° of the total cultivated land (PCL25). The output node represents the hazard-degree ranks (HDR). The model was trained with the 35 sets of data obtained from previous researches reported in literatures, and an explicit uncertainty analysis was undertaken to address the uncertainty in model training and prediction. Before the NN model is extrapolated to Lake Qionghai Watershed, a validation case, different from the above data, is conducted. In addition, the performances of the NN model and the MFCAM were compared. The NN model predicted that the HDRs of the five sub-watersheds in the Lake Qionghai Watershed were IV, IV, III, III, and IV–V, indicating that the study area covers normal hazard and severe hazard areas. Based on the NN model results, debris flow management and economic development strategies in the study are proposed for each sub-watershed.     

基于最小熵理论和未确知测度理论的泥石流敏感性分析

为了合理确定各影响因子权重,客观分析泥石流敏感性,基于最小熵分析原理和未确知测度理论建立泥石流敏感性分析模型。选取金沙江流域26条典型泥石流沟,确定9个主要影响因子,利用最小熵分析原理分析各因子对泥石流系统贡献率及权重,然后基于未确知测度理论计算各泥石流沟的多指标综合评价尺度向量,最后根据置信度识别准则确定各泥石流沟敏感度水平。将分析结果与已有成果进行对比可知,仅有7条泥石流沟敏感性结果有所差异。将评价结果与现场实际调查情况对比分析可知,22条泥石流沟的敏感度水平与泥石流实际发育情况相符,仅有4条沟评价结果偏于“保守”,因此,利用所提出的模型进行泥石流敏感度分析是十分有效的,并可对泥石流的防治提供合理的建议,可以在实际工程中推广应用。     

距离法定量评价储层地质模型的不确定性

针对目前常用的储层地质模型不确定性评价方法存在的主要问题,提出了先用距离函数计算模型之间的差异,再以差异的大小来判断不确定性大小的方法.以WZ油田西区为例,采用相控物性参数建模技术,利用顺序高斯模拟方法建立渗透率的三维模型.对各种度量差异的距离函数进行对比研究和分析,结果显示曼哈顿距离函数和欧氏距离函数能较好地刻画模型之间的差异.选用欧氏距离函数计算模型之间的差异,其原理是先计算每两个模型之间相对应的每一网格节点的渗透率值差的平方和,然后取平方根,得到一个表征各模型之间差异的矩阵.根据该矩阵可得到各个模型之间的差异程度,差异越大,不确定性就越大.最后通过对比模型过井剖面图分析结果与距离矩阵分析结果,说明了本方法的正确性,结果显示该方法能有效评价随机模拟生成的储层地质模型的不确定性.     

Conceptual and numerical models for sustainable groundwater management in the Thaphra area, Chi River Basin, Thailand

Sustainable management of groundwater resources is vital for development of areas at risk from water-resource over-exploitation. In northeast Thailand, the Phu Thok aquifer is an important water source, particularly in the Thaphra area, where increased groundwater withdrawals may result in water-level decline and saline-water upconing. Three-dimensional finite-difference flow models were developed with MODFLOW to predict the impacts of future pumping on hydraulic heads. Four scenarios of pumping and recharge were defined to evaluate the system response to future usage and climate conditions. Primary model simulations show that groundwater heads will continue to decrease by 4–12?m by the year 2040 at the center of the highly exploited area, under conditions of both increasing pumping and drought. To quantify predictive uncertainty in these estimates, in addition to the primary conceptual model, three alternative conceptual models were used in the simulation of sustainable yields. These alternative models show that, for this case study, a reasonable degree of uncertainty in hydrostratigraphic interpretation is more impactful than uncertainty in recharge distribution or boundary conditions. The uncertainty-analysis results strongly support addressing conceptual-model uncertainty in the practice of groundwater-management modeling. Doing so will better assist decision makers in selecting and implementing robust sustainable strategies.     

基于模糊-集对分析理论的泥石流危险性评价

集对分析理论是一种处理确定性和不确定性的定量系统分析方法。本文通过模糊联系度对集对分析理论中的差异度系数做进一步挖掘和分析,建立了模糊-集对分析算法,即通过模糊联系度挖掘样本数据讨论类别与相邻类别间的接近程度,得出该类别与相邻类别之间的同异反信息。为了验证模型的适用性,通过实测北京房山区和门头沟区6条泥石流小流域基础数据,进行了危险性评价,并将评价结果与传统评价理论进行对比分析。得出结论：模糊-集对分析理论可以深度挖掘样本类别与相邻类别之间的同异反关系,通过对比现场调查数据发现模糊-集对分析法对泥石流小流域的评价结果更切合实际,且评价结果与可拓学等评价结果基本一致,该方法具有较高的准确性和严密性。     

Uncertainty Evaluation of the Surface Water’sHeavy Metal Health Risk in Baiyun Mountain

The water environmental health risk assessment relates environmental pollution with human health, taking its risk degree as evaluation index, quantitatively describing the risk that pollution does great harm to human body. To understand the surface water’s heavy metal health risk in Guangzhou Baiyun Mountain, this study measured the nine sampling points in Baiyun Mountain’s south mountain and north mountain, including these physical and chemical indicators, such as water temperature, pH value, Cd, As, Cr, Hg, Pb, Mn, Cu,Zn and Ni, constructing the uncertainty evaluation model of the surface water’s heavy metal health risk in Baiyun Mountain(heavy metal including radioactive substances, chemical carcinogens and body toxic substances, etc.), having a fuzzy classification of the health risk assessment standard of the surface water’s heavy metal, further determining the membership degree and the belonging of the risk grade. By comparing the evaluation results of the uncertainty model and the deterministic model, the study found that: the surface water’s heavy metal health risk level was higher in Guangzhou Baiyun Mountain in 2012, being of the high grade and above, even achieving the highest grade; the surface water’s heavy metal health risk level of the north mountain was higher than the south mountain; the uncertainty evaluation model of the surface water’s heavy metal health risk was more reasonable and comprehensive to reflect the real situation of the surface water’s heavy metal quality concentration than the deterministic model. Besides, in the relevant references these questions on the total score of the health risk of the uncertainty evaluation model, the membership degree formula of the risk grade, etc. need further discussion.     

激光粒度仪测试结果及其与沉降法、筛析法的比较

分析了Cilas 940L激光粒度仪的测试结果,并与沉降法、筛析法进行了比较。激光粒度仪测试结果的重复性较好,测量精度较高。对于玻璃珠样品,激光粒度仪和筛析法测试结果十分接近,对于天然沉积物,激光粒度仪测定的平均粒径偏粗,分选偏差。和沉降法相比,激光粒度仪测定的粘土组份 (<8%)的含量为沉降法的 46.7%～ 70.5 %,平均为 6 0 %,测定的平均粒径较沉降法偏粗,分选偏差。造成激光粒度仪与沉降法、筛析法之间差异的原因主要在于这些测试方法原理的不同和天然沉积物不规则的形状。     

A probabilistic model to improve reconciliation of estimated and actual grade in open-pit mining

Many of the open-pit mines suffer from the lack of reconciliation between estimated and actual grades. In a mining operation, grade reconciliation is the comparison between the values of the estimated grade calculated in exploration stage and the actual grade obtained from more reliable data such as blast holes?? samples. Many different factors affect the degree of reconciliation in a mining operation. In this paper, the factors related to estimated grade which affect the reconciliation process in the exploration stage of the orebody are investigated. These factors constitute the sources of uncertainty for the upcoming phases of the mining life. Among these parameters, the inherent variability, statistical uncertainty, and systematic uncertainty are the most important factors. In this work, these parameters are studied in further detail, and, accordingly, for each of these uncertainties, a correction factor is determined in the proposed model. The model was applied to the study of real data taken from an iron open-pit mine in Iran. The results of the case study indicated that the systematic uncertainty, inherent variability, and statistical uncertainty are, in order, the main sources of uncertainty on grade reconciliation process. Applying the correction factors to estimated grade values has increased the amount of grade reconciliation from 10%, at original condition, to 50%, at new condition, in the case study.     

A theoretical method for determining sample mass in a sieving test

Obtaining a representative particle size distribution for soil is a common challenge in earth works and is affected by the size of sieving samples. While the current standards usually specify a minimum sample mass, there is no scientific justification for the specification. Treating the preparation of sieving samples as a process of random sampling, a new method is proposed for determining the minimum mass of a sieving test sample. The proposed method is validated via laboratory tests and will improve standard specification and engineering practice.     

Modelling Short‐Scale Variability and Uncertainty During Mineral Resource Estimation Using a Novel Fuzzy Estimation Technique

For mineral resource assessment, techniques based on fuzzy logic are attractive because they are capable of incorporating uncertainty associated with measured variables and can also quantify the uncertainty of the estimated grade, tonnage etc. The fuzzy grade estimation model is independent of the distribution of data, avoiding assumptions and constraints made during advanced geostatistical simulation, e.g., the turning bands method. Initially, fuzzy modelling classifies the data using all the component variables in the data set. We adopt a novel approach by taking into account the spatial irregularity of mineralisation patterns using the Gustafson–Kessel classification algorithm. The uncertainty at the point of estimation was derived through antecedent memberships in the input space (i.e., spatial coordinates) and transformed onto the output space (i.e., grades) through consequent membership at the point of estimation. Rather than probabilistic confidence intervals, this uncertainty was expressed in terms of fuzzy memberships, which indicated the occurrence of mixtures of different mineralogical phases at the point of estimation. Data from different sources (other than grades) could also be utilised during estimation. Application of the proposed technique on a real data set gave results that were comparable to those obtained from a turning bands simulation.     

核废物处置场岩体断裂的遥感分析

本文利用ＴＭ和ＳＩＲ－Ａ遥感图像对甘肃北山区４个预选的核废物处置场址的岩体断裂进行了解释和编图。并运用线性构造统计分析方法，对岩体断裂发育程度进行了统计分析。     

Quantifying the effects of subsurface heterogeneity on hillslope runoff using a stochastic approach

The role of heterogeneity and uncertainty in hydraulic conductivity on hillslope runoff production was evaluated using the fully integrated hydrologic model ParFlow. Simulations were generated using idealized high-resolution hillslopes configured both with a deep water table and a water table equal to the outlet to isolate surface and subsurface flow, respectively. Heterogeneous, correlated random fields were used to create spatial variability in the hydraulic conductivity. Ensembles, generated by multiple realizations of hydraulic conductivity, were used to evaluate how this uncertainty propagates to runoff. Ensemble averages were used to determine the effective runoff for a given hillslope as a function of rainfall rate and degree of subsurface heterogeneity. Cases where the water table is initialized at the outlet show runoff behavior with little sensitivity to variance in hydraulic conductivity. A technique is presented that explicitly interrogates individual realizations at every simulation timestep to partition overland and subsurface flow contributions. This hydrograph separation technique shows that the degree of heterogeneity can play a role in determining proportions of surface and subsurface flow, even when effective hillslope outflow is seen. This method is also used to evaluate current hydrograph separation techniques and demonstrates that recursive filters can accurately proportion overland and base-flow for certain cases.     

Influence of sieving time on the efficiency and accuracy of grain‐size analysis of beach and dune sands

Grain size is a fundamental property of sediments and is commonly used to describe sedimentary facies and classify sedimentary environments. Among the various conventional techniques utilized to determine grain‐size frequency distributions, sieving is the most widely applied procedure. The accuracy of such analyses is, among other factors, strongly dependent on the sieving time. However, despite a substantial amount of research in this field, optimal sieving times for different types of sediments have, to date, not been established. In this article, the influence of sieving time on grain‐size analyses of medium‐grained microtidal and mesotidal beach and dune sands has been determined. To assess the precision of important textural parameters, such as median grain size, sorting, skewness and kurtosis, an error analysis was carried out for different sieving times (2, 5, 10, 15 and 20 minutes). After calibrating the analytical and sampling methodologies, significant deviations were registered when sieving time was less than 10 minutes. However, such deviations were very small and grain‐size distributions remained almost identical for sieving times of 10 minutes and longer, relative errors being as low as 0% in some cases.