支架与悬杆上不同型号流速仪的安装及测流方法

一、问题的提出目前,大多数水文站的缆道测流,通常使用LS25-1型旋桨式流速仪。流速仪安装在铅鱼头部,用“I”字形或“L”字形流速仪支架(分别见图1(a)、(b)),这种安装方法对水深较深、流速较大的河流是适用的。但对受到人工调节以及宽浅型河流,水深、流速变化较大,单独用LS25-1型一种流速仪测流是不可能的,同时也保证不了测流精度。在超过LS25-1型流速仪测量范围下限时,必须用LS78-2型旋杯式低速流速仪才能测到流速。由于LS78-2型流速仪的形状结构所限,使之不能安装在图1所示     

流速仪在垂直偏角情况下测速误差的研究

悬索缆道测流,往往使流速仪形成垂直偏角,对流速有一定影响.分别率定了LS25-1型旋桨流速仪和LS68-1型旋杯流速仪在不同下倾角时与流速的关系流速仪的垂直偏角对流速有明显影响,并随偏角的加大而增加,偏角在10°以内影响不大;同时也率定了LS68-1型旋杯流速仪自动调整垂直下倾角时与流速的关系,下倾角在10°～30°以内对流速无明显变化,超过30°时,流速系统偏小.解决办法是(1)流速小有偏角时用LS68-1型旋杯流速仪,流速大时用LS25-3型旋桨流速仪,二者均有自动调平的功能;(2)合理选择铅鱼的型式和重量,本文提供了数据.     

盆地地下水流模式及其转化与控制因素

Tóth(1963)在复杂盆地给定上边界水头条件下, 推演出多级次地下水流系统.运用此方法探讨水流模式, 改变盆地介质或盆地深度等条件, 盆地水均衡会同步发生变化; 同时, 给定上边界水头也固化了盆地的势源与势汇的位置与数目, 这与实际条件不相符合, 也限制了地下水流模式的转化研究.在总结实验条件下多级水流系统特征的基础上, 提出了通量上边界的地下水流系统模拟方法(简称CUG-GWFS方法), 并进行了水流系统数值模拟.结果表明: (1)在多个可能势汇的盆地中, 可以发育5种地下水流模式, 即: 简单区域水流系统(RS)、局部+区域两级嵌套水流系统(LS+RS)、局部+中间+区域三级嵌套水流系统(LS+MS+RS)、局部+中间两级嵌套水流系统(LS+MS)和简单局部水流系统(LS).(2)盆地地下水流模式受盆地入渗强度、介质条件、盆地长度与深度比值, 以及盆地可能势汇的多少与位置的影响.(3)保持其他条件不变, 单独加大盆地入渗强度比R_ic, 或加大盆地长深比R_ld, 盆地水流模式按照上述5种模式呈现有序转化.      

Application of 3-D Geoscience Modeling Technology for the Estimation of Solid Mineral Reserves

Abstract: Applying new approaches, methods, and technologies for the estimation of reserves can effectively improve the efficiency and accuracy of assessments of solid mineral resources. After analyzing the development of 3-D geoscience modeling technology (3-D GMT), this paper discusses the application of 3-D GMT for the estimation of solid mineral reserves, emphatically introducing its workflow and two key technologies, 3-D orebody surface modeling, and property modeling. Moreover, the paper analyzes the limitations of traditional methods, such as the section method and geological block method, and points out the advantages of 3-D GMT: building more accurate 3-D orebody models, expressing the internal inhomogeneous attributes of an orebody, reducing the potential for errors in the estimation of reserves, and implementing dynamic estimations of reserves.     

Adaptive state estimation of groundwater contaminant boundary input flux in a 2-dimensional aquifer

In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative.Adaptive state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters.The ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement biases.The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional problems.Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios.Results also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise regimes.ASE's inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also noticed.The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.     

LS1206B型旋桨式流速仪

LS12系列是总结我国江河水文测验中大量使用的LS25-1型旋桨流速仪,及其派生的小型旋桨流速仪LS10型重新设计的一种新型仪器。本系列仪器的特点是:主机设计成通用化,配备各种规格     

平衡损失下回归系数stein压缩估计的性质

在平衡损失风险函数准则下,研究线性模型中回归系数的stein估计优于最小二乘估计(LS)的充分必要条件,然后在pitman closeness(PC)准则下比较了stein估计相对于最小二乘估计的优良性。     

雷达波流速仪流量测验水面流速系数分析

以具有不同河流特征的长冈水库水库、平江和孤江流域为例,进行了雷达波流速仪和LS1206B型流速仪水面流速的比测分析,并在比测试验的基础上,得出雷达波流速仪对水面流速的试验结果可以代表LS1206B型流速仪,同时用LS1206B型流速仪进行相对水深0.6 m测点流速的相关性分析,得出冈水库水库、平江和孤江流域水面流速系数...     

城市暴雨径流模拟的参数不确定性研究

基于暴雨管理模型(SWMM),构建了澳门半岛雅廉访实验小区降雨径流模拟系统,采用generalized likelihood uncertainty estimation(GLUE)方法对复杂降雨径流模型参数的不确定性进行了分析,采用均匀分布为参数的先验分布(prior distribution),选取拉丁超立方法作为采样方法,Nash-Sutcliffe效率系数作为似然评判准则。结果表明该方法可以有效的分析降雨径流模型参数的不确定性,对降雨径流模型参数识别提供了深入分析与理解模型系统的有效途径。     

Hybrid Estimation of Semivariogram Parameters

Two widely used methods of semivariogram estimation are weighted least squares estimation and maximum likelihood estimation. The former have certain computational advantages, whereas the latter are more statistically efficient. We introduce and study a “hybrid” semivariogram estimation procedure that combines weighted least squares estimation of the range parameter with maximum likelihood estimation of the sill (and nugget) assuming known range, in such a way that the sill-to-range ratio in an exponential semivariogram is estimated consistently under an infill asymptotic regime. We show empirically that such a procedure is nearly as efficient computationally, and more efficient statistically for some parameters, than weighted least squares estimation of all of the semivariogram’s parameters. Furthermore, we demonstrate that standard plug-in (or empirical) spatial predictors and prediction error variances, obtained by replacing the unknown semivariogram parameters with estimates in expressions for the ordinary kriging predictor and kriging variance, respectively, perform better when hybrid estimates are plugged in than when weighted least squares estimates are plugged in. In view of these results and the simplicity of computing the hybrid estimates from weighted least squares estimates, we suggest that software that currently estimates the semivariogram by weighted least squares methods be amended to include hybrid estimation as an option.     

Determining the initial stage loss content of tectonic coal gas desorption via the Bayesian probability method

Mine gas disaster prediction and prevention are based on gas content measurement, which results in initial stage loss when determining coal gas desorption contents in engineering applications. We propose a Bayesian probability statistical method in the coal gas desorption model on the basis of constrained prior information. First, we use a self-made coal sample gas desorption device to test initial stage gas desorption data of tectonic coal and undeformed coal. Second, we calculate the initial stage loss of different coal samples with the power exponential function parameters by using Bayesian probability statistics and least squares estimation. Results show that Bayesian probability statistics and least squares estimation can be used to obtain regression and desorption coefficients, thereby illustrating the Bayesian estimation method’s validity and reliability. Given that the Bayesian probability method can apply prior information to constrain the model’s posterior parameters, it provides results that are statistically significant in the initial stage loss of coal gas desorption by connecting observation data and prior information.

     

Lp估计理论及应用

基于最小二乘（ＬＳ）估计对粗差或长尾分布甚为敏感，作者提出用一簇估计－Ｌｐ估计似改善之。本文主要论述了Ｌｐ估计的基本原理及修正残差法的计算，并对Ｌｐ估计的抗差性能力及效率与ｐ的关系进行了分析，最后用一算例进行了讨论。     

水文相关中的最小二乘回归问题探讨

在研究了水文相关中利用最小二乘原理进行回归分析方法的基础上，指出了传统水文回归分析方法的使用条件、局限性和存在的问题。提出了不同性质的变量在回归分析时应区别对待的概念。结合水文观测的实际情况，研究了相关变量观测值均存在误差情况下，以变量的观测误差作权进行回归分析的概念，提出了建立基于最小二乘原理基础上的双加权回归模型，并研究了该模型的解算方法。同时推导了估计参数和预测值的误差估计公式，通过估计参数和模型误差的研究，有助于提高水文变量回归的精度和误差估计水平。     

Comparison of two techniques for applying disjunctive kriging: The Gaussian anamorphosis model versus the direct statistical inference of the bivariate distributions

Indicator cokriging is an alternative to disjunctive kriging for estimation of spatial distributions. One way to determine which of these techniques is more accurate for estimation of spatial distributions is to apply each to a particular type of data. A procedure is developed for evaluation of disjunctive kriging and indicator cokriging for such an application. Application of this procedure to earthquake ground motion data found disjunctive kriging to be at least as accurate as indicator cokriging for estimation of spatial distributions of peak horizontal acceleration. Indicator cokriging was superior for all other types of earthquake ground motion data.     

用相关函数优化法计算离散线性水文模型参数

借助于日降雨和出流资料系列,采用相关函数优化方法确定离散线性水文模型参数是一种新的方法.文中选用4个流域8年日降雨和径流资料系列来检验相关函数优化法(6年作为率定期,2年作为验证期),所得结果与常规最小二乘法计算的结果进行比较表明:新方法计算精度比常规最小二乘法计算的精度有所提高,常规最小二乘法仅是相关函数优化法的一种特例.     

地应力测量的误差处理及精度评定

本文从地应力测量数据误差处理的角度阐述了地应力计算的最小二乘法,对地应力测量精度评定方法进行了改进。采用协方差传播律进行误差计算,使精度评定的结果更加准确。利用应力的坐标变换关系,推导出应力与应力分量之间的微分关系,使主应力的精度计算更加简便。提出了主应力的偏用误差概念及其计算方法,使主应力方向的精度评定更加真实客观。     

岩石流变参数鲁棒辨识方法研究

基于室内岩石三轴蠕变试验资料对岩石的流变本构模型及流变参数进行辨识,是研究岩石流变力学特性的重要手段。由于受到试验条件和随机噪声的影响,试验数据中经常夹杂有异常值,采用传统的最小二乘法进行参数估计其结果往往会出现较大偏差。为了克服异常值对参数辨识结果的影响,引入统计学中的稳健估计理论,通过对实测的样本资料赋予不同的权重,采用双二次加权最小二乘法对流变参数进行估计。对比试验和计算结果表明,该方法能够有效地减小异常值对辨识结果的影响,在估值精度、收敛性、鲁棒性方面均优于传统的最小二乘估计方法。     

Some limitations in the geostatistical evaluation of ore deposits

Conclusions The foregoing discussion indicates that geostatistical estimation of ore deposits is not local; it is not objective; it is not sensitive to local data trends; and it is not unrestrained by the range of data values.Kriging, as an interpolation method, is a variant of IDW least squares linear fit. As such, it suffers from the limitations of all IDW linear interpolation methods that employ only data values.The estimation variance, currently used to calculate the confidence limits of values for individual mining blocks, is hypothetical and globally derived. It is more closely related to sampling density than to local variation in the data set.Geostatistical methods, of course, have a real place in ore deposit assessment, e.g. global, comparative evaluation to assist decisions on development and investment. What is questioned here is the validity of employing a global method to assess detail (mining blocks) within an ore deposit.     

Correcting the Smoothing Effect of Estimators: A Spectral Postprocessor

The postprocessing algorithm introduced by Yao for imposing the spectral amplitudes of a target covariance model is shown to be efficient in correcting the smoothing effect of estimation maps, whether obtained by kriging or any other interpolation technique. As opposed to stochastic simulation, Yao's algorithm yields a unique map starting from an original, typically smooth, estimation map. Most importantly it is shown that reproduction of a covariance/semivariogram model (global accuracy) is necessarily obtained at the cost of local accuracy reduction and increase in conditional bias. When working on one location at a time, kriging remains the most accurate (in the least squared error sense) estimator. However, kriging estimates should only be listed, not mapped, since they do not reflect the correct (target) spatial autocorrelation. This mismatch in spatial autocorrelation can be corrected via stochastic simulation, or can be imposed a posteriori via Yao's algorithm.