粒状物质的微观均匀度及其对取样误差的影响分析

研究物质的取样属性与以取样误差之间的关系是分析化学取样学的重要内容。从微观角度探讨了物质的理论性质及其对取样误差的影响。以碳化硅为例,考察了粒度分布、组分随粒度的变化以及均匀度因子等,分析了取样误差的来源。首次通过粒度分级成功地对碳化硅进行了分层,并对分层取样和随机取样的误差进行了分析和讨论,为制定合理的取样方案提供了有利的依据。本文的研究方法可适用于所有粒状物质的取样,同时也为分析化学取样学的深     

应用Monte Carlo模拟法探讨分层性物质的组合取样精度

应用MonteCarlo模拟法研究了分层性物质的组合取样精度,探讨了组合样中组分含量的分布规律、组合取样方差的分布规律、组合取样方差估计值的精度与组合样本数目之间的关系等.考察了组分含量服从正态分布、均匀随机分布及多项分布的分层性总体.结果表明,当样本数目较多时,组合取样误差规律对于不同原始分布的总体是相似的.     

分层性物质的组合取样误差与份样数目之间的关系及其Monte Carlo模拟

本文从理论上研究了分层性物质的组合取样误差与份样数目之间的定量关系，表明份样数目与组合取样相对标准偏差的平方之积为一常数，称为组合取样常数，它与Ｉｎｇａｍ ｅｌｌｓ 和Ｓｗ ｉｔｚｅｒ 提出的取样常数是相似的，表示６８％ 置信度下组合取样的相对标准偏差达到１％ 时的份样数目。应用Ｍｏｎｔｅ Ｃａｒｌｏ 模拟技术对该理论进行了验证，结果令人满意。     

提高碘量法测定天然气中硫化氢效率的方法

碘量法是测定管道输送天然气中硫化氢的一种经典方法,而管道输送天然气中硫化氢含量较低,按照GB/T11060.1–2010方法测定,取样量较大,取样时间长,影响工作效率。针对此问题,从两方面对碘量法进行改进:减小天然气取样量进行试验,并与国标规定取样量时的实验结果进行比对,确定最佳取样量;增大取样流量进行试验,并与国标规定取样流量时的实验结果进行比对,确定最佳取样流量。对硫化氢质量浓度为7.2~14.3,14.3~28.7 mg/m~3的天然气样品进行试验测定,结果表明,将天然气取样量减少为20 L,取样时间分别由200,100 min缩短为40 min;将天然气取样流量设定为750 m L/min,取样时间分别由200,100 min缩短为133,67 min。减少取样量或者提高取样流量,均能缩短管输天然气的取样时间,提高检测效率。     

计算机模拟地质化验室分样及取样常数Ks的估算

提出了计算机模拟地质化验室取样过程,考察取样误差与取样量、样品粒度之间关系,并估算取样常数.实验所得的误差与取样量之间的关系与Ingamells的取样方程一致,取样常数及取样常数和样品粒度关系式也与Ingamells推导的相符.由于计算机模拟是一颗颗取样,不用预设分布模式,不存在分析方法误差和分样操作误差的叠加,误差完...     

计算机模拟取样确定标准物质的最小取样量

本文提出用计算机模拟取样对不同的取样量重复进行测试多次,统计其检测结果的标准偏差,做出标准偏差s对取样量m的拟合曲线,再计算最小取样量。设计的模式是一颗一颗地取样,这样不存在取样操作及测试过程带来的误差,操作是可行的,结果是可靠的。计算机运算速度快,参数转换方便,也可以取毫克甚至亚毫克样进行实验。只要有足够的岩矿鉴定的资料,可以模拟不同状态下的样品取样过程。     

二元颗粒混合物按质量取样的误差研究

二元颗粒混合物的随机取样方式有两种：一是按颗粒数目取样,二是按质量取样本文对二元颗粒混合物按质量取样的误差进行了深入研究,详细分析了混合物的各种参对被测组分含量取样误差的影响,应用Ｍｏｎｔｅ Ｃａｒｌｏ技术对取样进行了模拟。以颗粒药品的二元混合物为例对按颗粒数目取样和按质量取样的误差进行了比较。此项研究对于分析取样理论和应用具有重要的价值。     

渐进取样法及其应用

提出了渐进取样法,通过样本数目的累积,使总方差估计值达到所需的精度。应用Ｍｏｎｔｅ Ｃａｒｌｏ模拟技术考察了满足一定取样精度的样本数目及其偏差。将该方法应用于散装生铁块中Ｓｉ、Ｍｎ、Ｃ、Ｓ、Ｐ含量分析的取样,结果令人满意。该项研究对于大宗货物的实际随机取样具有重要参考价值。     

取样量对润滑油中微量水分检测结果的影响

研究取样量对润滑油中微量水分测定结果的影响。基于卡尔·费休滴定法,在选定的测量条件下,用发生电极为有隔膜的自动库仑水分仪对基础油、有机热载体油、压缩机油、膨胀机油等新油和发动机油、汽轮机油、涡轮机油、压缩机油、齿轮油、液压油、导热油、船用油、电器绝缘油、风动工具油、金属加工油等在用油在0.1~2.0 g内各取9组不同质量的样品进行测定,得到了润滑油中微量水分准确测定所需的取样量。实验结果表明,新油取样量大于1.0 g,在用油取样量在1.0~1.5 g范围内,可以准确测定润滑油中微量水分含量。测定结果的相对标准偏差为0.83%~3.51%(n=10),样品加标回收率为95.0%~103.0%。在选择的取样量下,该方法具有良好的精密度、准确度,可连续测定多个样品,满足测定需求。     

取样方差估计值的精度与样本数目之间的关系

通过数学推导建立了取样方差估计值的精度与样本数目之间的定量关系。实验也证明,取样方差估计值的标准偏差与样本数目的平方根之积可近似为一常数。应用蒙特卡罗技术模拟随机取样,对该关系式进行了验证,并探讨了取样方差估计值的分布规律,表明其规律对于组分含量服从正态分布,均匀随机分布及多项分布总体是相似的。     

Sampling and sampling strategies for environmental analysis

Sampling errors are generally believed to dominate the errors of analytical measurement during the entire environmental data acquisition process. Unfortunately, environmental sampling errors are hardly quantified and documented even though analytical errors are frequently yet improperly reported to the third decimal point in environmental analysis. There is a significant discrepancy in directly applying traditional sampling theories (such as those developed for the binary particle systems) to trace levels of contaminants in complex environmental matrices with various spatial and temporal heterogeneities. The purpose of this critical review is to address several key issues in the development of an optimal sampling strategy with a primary goal of sample representativeness while minimizing the total number of samples and sampling frequencies, hence the cost for sampling and analysis. Several biased and statistically based sampling approaches commonly employed in environmental sampling (e.g. judgmental sampling and haphazard sampling vs. statistically based approaches such as simple random, systematic random, and stratified random sampling) are examined with respect to their pros and cons for the acquisition of scientifically reliable and legally defensible data. The effects of sample size, sample frequency and the use of compositing are addressed to illustrate the strategies for a cost reduction as well as an improved representativeness of sampling from spatially and temporally varied environmental systems. The discussions are accompanied with some recent advances and examples in the formulation of sampling strategies for the chemical or biological analysis of air, surface water, drinking water, groundwater, soil, and hazardous waste sites.     

组合取样的误差理论研究及其Monte Carlo模拟

基于多项分布理论,建立了组合取样方差与取样总体中各子区的大小及其组分含量之间的关系和计算公式,探讨了组合取样常数的物理意义.以颗粒物质为例,探讨了组合取样的逻辑质量单元的概念及其意义,为确定组合取样中的份样质量提供了理论依据.本文对于完善组合取样误差理论,保证组合取样的质量均具有重要意义.     

探讨二元颗粒混合物取样误差的新的数学模型

采用新的数学模型研究二元颗粒混合物的取样误差,首次提出了取样的逻辑质量单元的理论,探讨了逻辑质量单元的物理意义,建立了按质量取样的标准偏差的计算公式.应用颗粒药品二元混合物的取样实验,证实了该公式的正确性.     

Effect of missing values in estimation of mean of auto-correlated measurement series

Sampling and uncertainty of sampling are important tasks, when industrial processes are monitored. Missing values and unequal sources can cause problems in almost all industrial fields. One major problem is that during weekends samples may not be collected. On the other hand a composite sample may be collected during weekend. These systematically occurring missing values (gaps) will have an effect on the uncertainties of the measurements. Another type of missing values is random missing values. These random gaps are caused, for example, by instrument failures. Pierre Gy's sampling theory includes tools to evaluate all error components that are involved in sampling of heterogeneous materials. Variograms, introduced by Gy's sampling theory, have been developed to estimate the uncertainty of auto-correlated process measurements. Variographic experiments are utilized for estimating the variance for different sample selection strategies. The different sample selection strategies are random sampling, stratified random sampling and systematic sampling. In this paper both systematic and random gaps were estimated by using simulations and real process data. These process data were taken from bark boilers of pulp and paper mills (combustion processes). When systematic gaps were examined a linear interpolation was utilized. Also cases introducing composite sampling were studied. Aims of this paper are: (1) how reliable the variogram is to estimate the process variogram calculated from data with systematic gaps, (2) how the uncertainty of missing gap can be estimated in reporting time-averages of auto-correlated time series measurements. The results show that when systematic gaps were filled by linear interpolation only minor changes in the values of variogram were observed. The differences between the variograms were constantly smallest with composite samples. While estimating the effect of random gaps, the results show that for the non-periodic processes the stratified random sampling strategy gives more reliable results than systematic sampling strategy. Therefore stratified random sampling should be used while estimating the uncertainty of random gaps in reporting time-averages of auto-correlated time series measurements.     

Vacuum-assisted headspace solid phase microextraction: Improved extraction of semivolatiles by non-equilibrium headspace sampling under reduced pressure conditions

A new headspace solid-phase microextraction (HSSPME) procedure carried out under vacuum conditions is proposed here where sample volumes commonly used in HSSPME (9 mL) were introduced into pre-evacuated commercially available large sampling chambers (1000 mL) prior to HSSPME sampling. The proposed procedure ensured reproducible conditions for HSSPME and excluded the possibility of analyte losses. A theoretical model was formulated demonstrating for the first time the pressure dependence of HSSPME sampling procedure under non equilibrium conditions. Although reduced pressure conditions during HSSPME sampling are not expected to increase the amount of analytes extracted at equilibrium, they greatly increase extraction rates compared to HSSPME under atmospheric pressure due to the enhancement of evaporation rates in the presence of an air-evacuated headspace. The effect is larger for semivolatiles whose evaporation rates are controlled by mass transfer resistance in the thin gas film adjacent to the sample/headspace interface. Parameters that affect HSSPME extraction were investigated under both vacuum and atmospheric conditions and the experimental data obtained were used to discuss and verify the theory. The use of an excessively large headspace volume was also considered. The applicability of Vac-HSSPME was assessed using chlorophenols as model compounds yielding linearities better than 0.9915 and detection limits in the low-ppt level. The repeatability was found to vary from 3.1 to 8.6%.     

一种新型动力学被动采样技术—化学捕收器

化学捕收器（Chemcatcher）是一种新型可原位、连续、动态监测水环境污染物的被动采样技术。它以Fick扩散定律为定量基础,测定对象分为极性有机物、非极性有机物和无机物。本文介绍了该技术的装置组成、定量原理及其在水环境研究中的应用,并对此被动采样技术进行了评价与展望。