Uncertainty in probabilistic risk assessment

Dealing with uncertainty is an important and difficult aspect of analyses for complex systems. Such systems involve many uncertainties, and assessing probabilities to represent these uncertainties is itself a complex undertaking utilizing a variety of information sources. At a very basic level, uncertainty is uncertainty, and attempting to distinguish between ‘types of uncertainty’ is questionable. At a practical level, on the other hand, a close look at such distinctions suggests that they are driven by important modelling issues related to model structuring, probability assessment, information gathering, and sensitivity analysis. Anything that brings more attention to these issues should improve the state of the art. However, I would prefer to attack the issues directly instead of working indirectly through the notion of ‘types of uncertainty.’     

蔬菜中吡虫啉残留量的不确定度分析

依据NY/T 761—2008农药残留分析方法的第三部分,采用高效液相色谱法测定蔬菜中吡虫啉的残留量,对测定结果的不确定度进行了分析,并对各不确定度分量进行了评定和量化,计算了合成标准不确定度和扩展不确定度.结果表明,定量重复性误差及同一样品的重复性误差所引入的不确定度是影响残留量测定不确定度的较大因素;蔬菜中吡虫啉残留量结果表示为(C±U)mg/kg,k=2.     

ICP检测不锈钢食用器皿卫生指标的不确定度评估

为对电感耦合等离子体测定不锈钢食用器皿卫生指标实验方法的实用性作出评价，文章根据不确定度评估的通用方法对实验过程中不确定度的引入进行系统分析，在此基础上给出实验结果不确定度。     

Uncertainty analysis in the task of individual monitoring data

Assessment of internal doses is an essential component of individual monitoring programmes for workers and consists of two stages: individual monitoring measurements and interpretation of the monitoring data in terms of annual intake and/or annual internal dose. The overall uncertainty in assessed dose is a combination of the uncertainties in these stages. An algorithm and a computer code were developed for estimating the uncertainty in the assessment of internal dose in the task of individual monitoring data interpretation. Two main influencing factors are analysed in this paper: the unknown time of the exposure and variability of bioassay measurements. The aim of this analysis is to show that the algorithm is applicable in designing an individual monitoring programme for workers so as to guarantee that the individual dose calculated from individual monitoring measurements does not exceed a required limit with a certain confidence probability.     

桥梁结构工作模态分析的不确定度量化

为了量化工作模态分析的不确定度,以随机子空间识别为例,用两种方法对识别的固有频率和阻尼比不确定度进行量化：第一,用不同测试组识别的模态参数的数学期望和标准差衡量其整体大小和离散程度,构建模态参数的整体置信区间;第二,引入了以矩阵敏感性分析的单个测试组识别的模态参数不确定度量化方法,并构造带置信区间的稳定图。以菜园坝桥拱肋试验数据作为工程实例进行了验证。研究表明：构建的整体置信区间弥补了目前对模态参数的单一评价模式;带置信区间的稳定图能让测试者分辨出结构真实模态和虚假模态;两种方法能分别从整体和局部反映识别的模态参数不确定度;为评价用工作模态分析方法来识别的模态参数的可信程度提供了依据。     

Uncertainty in cost-benefit analysis based on referendum contingent valuation

Using contingent valuation methods (CVM) is increasingly common in project analysis. Referendum-type questions are thought to be easier to answer than the open-ended variety, but there is a downside: econometric techniques must be applied to the referendum data to infer the mean or median willingness to pay (WTP) of the sample and, thus, of the population of potential beneficiaries. This is not just a technical point as is demonstrated with data from a referendum CV study of a sewage and wastewater treatment project in Brazil. A factor of 4 separates lowest from highest central tendency estimates, ignoring the outlier that is 14 times larger than the largest of the other figures. This is ample variation to make a difference in the cost-benefit analysis. Analysts using referendum CV must be sensitive to the problems they buy into, and must decide how to deal with the uncertainty in the results.     

On risk and risk analysis

Currently, an increasing number of researchers and organizations are recognizing the importance of adopting a well-focused research in risk, risk analysis and risk management that will also address the establishment of new risk measures which reflect the public's concerns, and that can be demonstrated to be valid, credible and reliable. This paper gives a brief introduction to risk and classifies relevant literature related to risk and risk analysis for ease of use by the readers.     

Uncertainty analysis of thermo-hydro-mechanical coupled processes in heterogeneous porous media

In this paper we present an uncertainty analysis of thermo-hydro-mechanical (THM) coupled processes in a typical geothermal reservoir in crystalline rock. Fracture and matrix are treated conceptually as an equivalent porous medium, and the model is applied to available data from the Urach Spa and Falkenberg sites (Germany). The finite element method (FEM) is used for the numerical analysis of fully coupled THM processes, including thermal water flow, advective–diffusive heat transport, and thermoelasticity. Non-linearity in system behavior is introduced via temperature and pressure dependent fluid properties. Reservoir parameters are considered as spatially random variables and their realizations are generated using conditional Gaussian simulation. The related Monte-Carlo analysis of the coupled THM problem is computationally very expensive. To enhance computational efficiency, the parallel FEM based on domain decomposition technology using message passing interface (MPI) is utilized to conduct the numerous simulations. In the numerical analysis we considered two reservoir modes: undisturbed and stimulated. The uncertainty analysis we apply captures both the effects of heterogeneity and hydraulic stimulation near the injection borehole. The results show the influence of parameter ranges on reservoir evolution during long-term heat extraction, taking into account fully coupled thermo-hydro-mechanical processes. We found that the most significant factors in the analysis are permeability and heat capacity. The study demonstrates the importance of taking parameter uncertainties into account for geothermal reservoir evaluation in order to assess the viability of numerical modeling.     

大尺寸测量的温度误差修正的不确定度分析

文章着重讨论了大尺寸测量中影响温度误差修正精度的主要因素并深入分析了温度误差修正后的不确定度为满足大尺寸高精度的测量要求,提出了精确测定材料膨胀系数的方法,有效降低了温度误差修正后的不确定度,确保了大尺寸的高精度测量的实现。     

基于预测模型的虚拟试验不确定性分析方法

 工程系统中不可避免地存在各种参数不确定性,利用数值计算模型对系统进行虚拟试验时应进行不确定性分析.大型耗时计算模型的不确定性分析将面临严重的的计算复杂性问题,为此,针对工程应用中耗时计算模型,提出一种基于贝叶斯预测模型的不确定性分析仿真方法,采用概率分布为参数不确定性建模,研究系统响应预测不确定性的概率特征.泰勒杆撞击实例验证了该方法的高效性.     

热量表检定装置不确定度分析

热量表检定装置的性能直接影响热量表的检定结果。该文旨在通过分析热量表检定装置的不确定度,量化各环节对不确定度总量的贡献,从而寻求改善热量表检定装置性能方法。根据各不确定度分量,找到对装置性能影响较大的环节,并分别针对热水流量检测系统和温差检测系统提出可行的改进方案。     

Uncertainty analysis of the urinary excretion of plutonium

A quantitative estimate of the uncertainty of the urinary excretion of plutonium predicted by available biokinetic models is provided. Urinary excretion is primarily considered here because the monitoring of internal contamination of plutonium mainly relies on measurements of activity in urine samples. A previous paper has identified the most significant transfer rates for urinary plutonium excretion following an acute intake. That analysis is used here as a screening method to reduce the number of model parameters to be considered. A log-normal distribution was assumed for the probability distribution of the model parameters. The spread of the values, represented by the geometric standard deviation (GSD), is explicitly calculated, as few indications of the range of variation of systemic transfer rates are available. Different values for the GSD were considered. Assuming a certain GSD for all the systemic rate constants, random values of the rates were generated (by means of a Monte Carlo simulation with a Latin hypercube sampling scheme) and the resulting predictions of urine bioassay measurements were calculated. The comparison of the mean and variance of the predictions with the available data from several studies performed on different subjects provides information about the GSD of model parameters that represents the intersubject variation of transfer parameters.     

Uncertainty analysis of reliability predictions for brittle fracture

Reliability analysis of ceramic components under stationary or transient loading is generally performed on the basis of a Finite Element stress analysis from which the failure probability according to the multi-axial Weakest Link theory is calculated with the help of a suitable post-processing routine. We use the STAU post-processing routine and the general purpose Finite Element code ABAQUS. Due to scatter in the material parameters, the resulting failure probability is also prone to statistical uncertainties. We present a method of assessing this scatter using so-called resampling simulation methods. The analysis leads to confidence intervals for the failure probability which is a novel and important result especially for the purpose of design sensitivity considerations and the assessment of pooling procedures. In a simple example using a four-point bend specimen, the effect of pooling (i.e. grouping of results from different experiments by suitable scaling procedures) on the numerical result and on the scatter of failure probability is demonstrated. Here, pooling is done using results of inert strength measurements at various temperatures and scaling to room temperature values. A technologically more relevant example deals with a ceramic component in a model clutch under thermo-mechanical frictional loading. As a first step, the local risk of rupture is calculated which leads to the identification of the most critical regions of the component. As a second step, resampling confidence intervals for the failure probability are determined. As resampling data base, we use inert strength values at different temperatures as well as material data for sub-critical crack propagation.     

Uncertainty analysis and allocation of joint tolerances in robot manipulators based on interval analysis

Many uncertain factors influence the accuracy and repeatability of robots. These factors include manufacturing and assembly tolerances and deviations in actuators and controllers. The effects of these uncertain factors must be carefully analyzed to obtain a clear insight into the manipulator performance. In order to ensure the position and orientation accuracy of a robot end effector as well as to reduce the manufacturing cost of the robot, it is necessary to quantify the influence of the uncertain factors and optimally allocate the tolerances. This involves a study of the direct and inverse kinematics of robot end effectors in the presence of uncertain factors. This paper focuses on the optimal allocation of joint tolerances with consideration of the positional and directional errors of the robot end effector and the manufacturing cost. The interval analysis is used for predicting errors in the performance of robot manipulators. The Stanford manipulator is considered for illustration. The unknown joint variables are modeled as interval parameters due to the inherent uncertainty. The cost-tolerance model is assumed to be of an exponential form during optimization. The effects of the upper bounds on the minimum cost and relative deviations of the directional and positional errors of the end effector are also studied.     

Integrating human health and ecological concerns in risk assessments

The interconnections between ecosystems, human health and welfare have been increasingly recognized by the US government, academia, and the public. This paper continues this theme by addressing the use of risk assessment to integrate people into a single assessment. In a broad overview of the risk assessment process we stress the need to build a conceptual model of the whole system including multiple species (humans and other ecological entities), stressors, and cumulative effects. We also propose converging landscape ecology and evaluation of ecosystem services with risk assessment to address these cumulative responses. We first look at how this integration can occur within the problem formulation step in risk assessment where the system is defined, a conceptual model created, a subset of components and functions selected, and the analytical framework decided in a context that includes the management decisions. A variety of examples of problem formulations (salmon, wild insects, hyporheic ecosystems, ultraviolet (UV) radiation, nitrogen fertilization, toxic chemicals, and oil spills) are presented to illustrate how treating humans as components of the landscape can add value to risk assessments. We conclude that the risk assessment process should help address the urgent needs of society in proportion to importance, to provide a format to communicate knowledge and understanding, and to inform policy and management decisions.     

Uncertainty and sensitivity analysis for models with correlated parameters

When conducting sensitivity and uncertainty analysis, most of the global sensitivity techniques assume parameter independence. However, it is common that the parameters are correlated with each other. For models with correlated inputs, we propose that the contribution of uncertainty to model output by an individual parameter be divided into two parts: the correlated contribution (by the correlated variations, i.e. variations of a parameter which are correlated with other parameters) and the uncorrelated contribution (by the uncorrelated variations, i.e. the unique variations of a parameter which cannot be explained by any other parameters). So far, only a few studies have been conducted to obtain the sensitivity index for a model with correlated input. But these studies do not distinguish between the correlated and uncorrelated contribution of a parameter. In this study, we propose a regression-based method to quantitatively decompose the total uncertainty in model output into partial variances contributed by the correlated variations and partial variances contributed by the uncorrelated variations. The proposed regression-based method is then applied in three test cases. Results show that the regression-based method can successfully measure the uncertainty contribution in the case where the relationship between response and parameters is approximately linear.     

包装件振动可靠性的不确定度量化及灵敏度分析

研究包装件参数不确定性对振动可靠性变化的影响,并分析振动可靠性指标对各不确定参数的灵敏度.采用Karhunen-Loeve展开将具有一定谱特征的平稳随机振动表示在标准正态随机变量空间中,应用一阶可靠性方法分析线性包装件振动可靠性指标.考虑缓冲材料弹性特性、阻尼特性、产品主体和脆弱部件之间的弹性特性、阻尼特性四个随机参数...     

Uncertainty analysis and reliability estimation of clamp band joints

In this paper, a mathematical model is developed to estimate specifications of a clamp band joint by taking into account full effects of the uncertainty of the joint parameters with a reasonable amount of computational cost. In the model, the clamp band joint is partitioned into sectors which are substituted with equivalent springs. The mathematical formulation of the stiffness and load bearing capacity of the joint is derived under combination of the loads. Nonlinear finite-element analysis is conducted to verify the proposed formulation, where all parameters have their nominal value. Finally, a procedure is introduced, in which one can specify the uncertainty of the joint parameters and the safety factor to obtain a desired reliability level from a table.