比对实验测量结果不确定度评定

对比对实验电导率仪电子单元引用误差测量结果的不确定度因素做了分析,研究了了各主要不确定度来源及其不确定度的大小,最后得出了这次比对实验的不确定度。     

火焰原子吸收光谱法测定铝及铝合金中铬含量的不确定度评定

通过对火焰原子吸收光谱法测定铝合金中铬含量的实验过程分析,建立了该法测定铝合金中铬不确定度的数学模型,计算了各不确定度分量,合成标准不确定度和扩展不确定度,找出影响不确定度的重要因素。     

化妆品中甲氧基肉桂酸乙基己酯测量结果不确定度的评定

文章建立高效液相色谱法测定化妆品中甲氧基肉桂酸乙基己酯结果不确定度评定的数学模型,并综合了分析测量过程中的不确定度来源,同时对结果的不确定度进行分析;通过评定结果表明:该方法除了仪器设备引入的不确定度,主要因素是试样称量引入和实验过程随机效应引入的不确定度是主要来源,本研究通过实验数据可了解降低其不确定度的方式和途径。     

铜精矿中铜含量测定的不确定度评定

通过滴定法测定铜精矿中铜含量,对其测量不确定度进行评定,详尽地分析了整个实验过程中的不确定度来源,并对各部分不确定度分量进行量化计算,得出合成标准不确定度和扩展不确定度,并以不确定度的形式给出测定结果。     

ICP-AES法测定锰矿中二氧化硅含量的不确定度评定

实验部分采用标准物质与样品同时溶样,使用固体标准物质做标准曲线,ICP-AES法测定二氧化硅含量的不确定度评定,建立了该方法的定量数学模型,对整个实验过程中可能引入的各种不确定度来源进行分析,计算出合成不确定度及扩展不确定度,并对结果进行评价。     

溶剂型木器涂料中TDI含量测定结果不确定度评定

对溶剂型木器涂料中TDI含量测定值的不确定度进行不确定度评估,对影响不确定度的各个因素进行了分析。阐述了该实验不确定度的评估方法。结果表明,该法可如实反映测量的置信度和准确性。     

耐火材料体积密度的不确定度分析和评定

耐火材料体积密度测量不确定度应按国家计量技术规范JJF1059-1999《测量不确定度评定与表示》的有关规定评定。其A类不确定度可通过一个预先确定的测量模型(一次抽样子样本统计)进行估计;B类不确定度则包括了计量器具系统不确定度分量,不同测量方法不确定度分量,不同实验条件下不确定度分量和理论计算不确定度分量。     

钼酸铵分光光度法测定水中总磷含量的不确定度评定

不确定度是指测量获得的结果的不确定度程度,是对于误差分析中较好的理解和阐述。文章以钼酸铵分光光度法对水中总磷含量的测定为例,根据其实验过程的操作步骤确定了主要影响因素,对其检测结果的不确定度进行了分析,量化了影响结果的不确定度分量,求出了合成标准不确定度和扩展不确定度,最后得评定结果分析。     

水泥中游离氧化钙测量不确定度评定

根据GB/T 176—2017《水泥化学分析方法》和JJF 1059.1-2012《测量不确定度评定与表示》，对水泥中游离氧化钙测量在实验中的不确定度进行评定。以乙二醇-乙醇法为例，在实验中会产生A类不确定度和B类不确定度，根据其不同的产生原因，建立数学模型，进行计算得出扩展不确定度为0.044%，从分量到计算合成，反映了测定结果的科学性和实验结果的真实性，有利于实验的质量控制。     

水泥中游离氧化钙测量不确定度评定

根据GB/T 176—2017《水泥化学分析方法》和JJF 1059.1-2012《测量不确定度评定与表示》，对水泥中游离氧化钙测量在实验中的不确定度进行评定。以乙二醇-乙醇法为例，在实验中会产生A类不确定度和B类不确定度，根据其不同的产生原因，建立数学模型，进行计算得出扩展不确定度为0.044%，从分量到计算合成，反映了测定结果的科学性和实验结果的真实性，有利于实验的质量控制。     

Measurements of diesel soot oxidation kinetics in an isothermal flow reactor–catalytic effects using Pt based coatings

Despite the significant progress in soot oxidation studies, there is still high uncertainty regarding the rate expressions to model the reactions in diesel particulate filters (DPF). This uncertainty arises from inherent difficulties in sampling and measuring the reaction rate in a realistic way, as well as different properties of the examined soot. In this context, the scope of this study is the development of a novel experimental set-up capable of overcoming existing experimental difficulties. The developed set-up allows for real diesel soot oxidation studies in an isothermal flow reactor. The reaction of soot with oxygen and NO₂ is studied with synthetic gas and with real diesel exhaust and the reaction kinetics are derived for both bare and Pt-based catalyzed substrates by combining experimental and model results.     

氢化物原子荧光光谱法测定海产品中砷含量的不确定度评定

目的:建立氢化物原子荧光光谱法测定海产品中砷含量的不确定度评定程序和方法。方法:建立数学模型,应用测量不确定度评定理论,结合实验方法,确定和计算测定过程中各不确定度分量,计算合成不确定度和扩展不确定度。结果:本试验方法用氢化物原子荧光光谱法测定海产品中砷含量的不确定度为:5.3%。结论:测量结果与测量不确定度的同时给出,更能显示出结果的可靠。     

食用植物油中酸价测量结果的不确定度评估

应用不确定度评定方法对酸价测量结果进行不确定度分析与评估,得出样品中酸价的合成标准不确定度和扩展不确定度。根据油脂中酸价测定的原理和步骤建立数学模型,对不确定度进行评估。该方法测定油脂中酸价的合成不确定度u（X）=0.03,扩展不确定度U=0.06,滴定终点判断引入的标准不确定度影响较大。     

Bayesian estimation of parametric uncertainties,quantification and reduction using optimal design of experiments for CO2 adsorption on amine sorbents

Uncertainty quantification plays a significant role in establishing reliability of mathematical models, while applying to process optimization or technology feasibility studies. Uncertainties, in general, could occur either in mathematical model or in model parameters. In this work, process of CO₂ adsorption on amine sorbents, which are loaded in hollow fibers is studied to quantify the impact of uncertainties in the adsorption isotherm parameters on the model prediction. The process design variable that is most closely related to the process economics is the CO₂ sorption capacity, whose uncertainty is investigated. We apply Bayesian analysis and determine a utility function surface corresponding to the value of information gained by the respective experimental design point. It is demonstrated that performing an experiment at a condition with a higher utility has a higher reduction of design variable prediction uncertainty compared to choosing a design point at a lower utility.     

Teaching uncertainty propagation as a core component in process engineering statistics

Propagation of uncertainty refers to evaluation of uncertainty in output(s) given uncertainty in input(s). This can be across a physical process, or can be predicted based on a process model. Uncertainty can be propagated analytically, by application of Taylor series variance propagation, or numerically, through repeated Monte-Carlo simulations. Propagation of uncertainty is an important concept in process engineering statistics, which is not currently widely taught. In this paper, an approach is provided for teaching uncertainty propagation as part of a larger process engineering statistics course, applying analytical and numerical propagation principles, including consideration of correlation in inputs. A saline blending practical is used as a case study, with experimental and theoretical determination of how variability in feed pump flows determines variability in outlet conductivity. Based on a class of 132 2nd year Chemical Engineering students, learning outcomes in analytical and numerical linear and non-linear propagation models can be attained and enhanced applicability and engagement within the core statistics course. An engagement survey particularly noted that the students recognised the importance of propagation as a technical capability, but noted difficulties in linking the experimental work to theory of propagation. Overall, propagation of uncertainty allows educators to increase the direct relevance of statistics to process engineering and engage with students through their existing analytical capabilities.     

Combined Experimental and Predictive Uncertainty of Quantitative Structure Property Relationship Models

Quantitative structure property relationship (QSPR) models allow for estimation of unknown substance properties. Their accuracy is usually described by error metrics that compare the result of the estimation to an experimental value. However, it has to be kept in mind that measured values are not perfectly accurate as well. The actual reliability of a QSPR model is therefore often significantly lower than indicated by conventional error metrics. To deal with this issue, the combined experimental and predictive uncertainty (CEPU) is proposed. Analogously to error propagation in evaluation of experimental works, the reliability of estimation methods can be accessed by the root of the sum of the different squared contributions to overall uncertainty. Such a metric is able to describe the effects of experimental errors with uniform algebraic sign as well as of randomized experimental errors.     

THE EFFECT OF EXPERIMENTAL MEASUREMENT UNCERTAINTIES ON RATE MODELING AND REACTOR SIMULATION

Experimentally determined reaction rates often are used to discriminate between proposed reaction rate models. However, little emphasis has been placed upon evaluating the effect of experimental measurement uncertainties on rate model determinations. In this work, usual methods of rate model discrimination (mean-squared error criterion) are used to distinguish the best rate model. Regression occurred on three sets of rate data that contained various levels of measurement uncertainty. This uncertainty in reaction rate is reflective of the uncertainty associated with experimental measurement of pressure, temperature, and composition. Our objective was to determine whether experimental measurement uncertainties influence the selection of the best rate model.

Five rate expressions were used to regress the sets of kinetic rate data. The best rate model depended upon the level of measurement uncertainty, indicating the need for accurate kinetic data. Simulation of a plug flow reactor using the best rate models further stressed the importance of obtaining accurate rate data by showing that reactor performance depended heavily upon the rate expression.     

Entropic model for the relaxation in vitreous systems. Estimation of uncertainty in the calculation of the conformational relaxation times

Differential scanning calorimetry experiments were conducted on a thermotropic polyester. The experimental results consists of a series of thermograms measured on heating after different thermal histories that contained (or not) an isothermal stage at a temperature T_a below the glass transition with a duration t_a. The thermogram showed the characteristic peak in the region of the glass transition. The calculation of the relaxation times of the co-operative conformational rearrangements related to the glass transition and structural relaxation phenomena has been conducted by curve fitting using a phenomenological model. The curve fitting procedure was conducted simultaneously on a fixed number n of experimental thermograms. The aim of the paper is to present a method to estimate the uncertainty in the calculation of the model parameter. The results show how the computer simulated thermograms agree quite well to the experimental data. The uncertainty in the model parameters and through them the uncertainty in the calculated relaxation times is quite important when the number of experimental curves n is small but rapidly decreases as n increases and if more than five curves are used simultaneously in the fitting routine both the values of the model parameters and their uncertainty become independent on the number and thermal histories of the experimental thermograms.     

传统法建立动力学模型的不确定性和沿程法(RAPRA)建模

本文通过数值分析、参数灵敏性分析和实验研究,考察了动力学模型及参数、反应器操作方式和操作条件等因素对模拟结果的影响,认为传统研究方法建立动力学模型具有不确定性.根据反应器设计、模拟要求,提出了动力学建模方法——沿程法,该法在模拟反应器行为时可靠性优于传统法.     

分光光度法测定水质总氰化物含量的不确定度评定

根据<测量不确定度评定与表示>(JJF1059-1999)对水质总氰化物含量测定进行测量不确定度的分析与评定.分别计算各分量的不确定度,再计算出合成不确定度,并取k=2(置信概率95%)得出扩展不确定度.建立的不确定度评定方法适合于分光光度法测定水质总氰化物含量的不确定度的分析.