Evaluating the comfort of use of protective footwear: Validation of a method based on microclimate parameters and peripheral blood flow

The paper presents validation evidence for a method of evaluating the comfort of use of protective footwear based on microclimate parameters and peripheral blood flow in the lower limbs. A study involving impedance plethysmography showed that the inherent construction characteristics of protective footwear hinder heat diffusion and moisture removal, influencing peripheral blood flow in the lower limbs. The temperature and relative humidity inside the footwear, the weight of secreted sweat, and the weight of the support textiles (socks and liners) were measured and compared to the plethysmographic parameters. The components of measurement uncertainty were carefully determined for each studied parameter and uncertainty budgets were created. These results were subsequently used to identify measurement errors that could affect the quality and reliability of laboratory tests.     

Removing divergence of JCGM documents from the GUM (1993) and repairing other defects

The mission of the Joint Committee for Guides in Metrology (JCGM) is to maintain and promote the use of the Guide to the Expression of Uncertainty in Measurement (GUM) and the International Vocabulary of Metrology (VIM, second edition). The JCGM has produced the third edition of the VIM (referred to as VIM3) and a number of documents; some of which are referred to as supplements to the GUM. We are concerned with the Supplement 1 (GUM-S1) and the document JCGM 104. The signal contribution of the GUM is its operational view of the uncertainty in measurement (as a parameter that characterizes the dispersion of the values that could be attributed to an unknown quantity). The operational view promulgated by the GUM had disconnected the uncertainty in measurement from the unknowable quantities true value and error. The GUM-S1 has diverged from the operational view of the uncertainty in measurement. Either the disparities should be removed or the GUM-S1 should not be referred to as a supplement to the GUM. Also, the GUM-S1 has misinterpreted the Bayesian concept of a statistical parameter and the VIM3 definitions of coverage interval and coverage probability are mathematically defective. We offer practical suggestions for revising the GUM-S1 and the VIM3 to remove their divergence from the GUM and to repair their defects.     

Framework for sensitivity and uncertainty quantification in the flutter assessment of bridges

The phenomenon of aerodynamic instability caused by wind is usually a major design criterion for long-span cable-supported bridges. If the wind speed exceeds the critical flutter speed of the bridge, this constitutes an Ultimate Limit State. The prediction of the flutter boundary therefore requires accurate and robust models. The state-of-the-art theory concerning determination of the flutter stability limit is presented. Usually bridge decks are bluff and therefore the aeroelastic forces under wind action have to be experimentally evaluated in wind tunnels or numerically computed through Computational Fluid Dynamics (CFD) simulations. The self-excited forces are modelled using aerodynamic derivatives obtained through CFD forced vibration simulations on a section model. The two-degree-of-freedom flutter limit is computed by solving the Eigenvalue problem.A probabilistic flutter analysis utilizing a meta-modelling technique is used to evaluate the effect of parameter uncertainty. A bridge section is numerically modelled in the CFD simulations. Here flutter derivatives are considered as random variables. A methodology for carrying out sensitivity analysis of the flutter phenomenon is developed. The sensitivity with respect to the uncertainty of flutter derivatives and structural parameters is considered by taking into account the probability distribution of the flutter limit. A significant influence on the flutter limit is found by including uncertainties of the flutter derivatives due to different interpretations of scatter in the CFD simulations. The results indicate that the proposed probabilistic flutter analysis provides extended information concerning the accuracy in the prediction of flutter limits.The final aim is to set up a method to estimate the flutter limit with probabilistic input parameters. Such a tool could be useful for bridge engineers at early design stages. This study shows the difficulties in this regard which have to be overcome but also highlights some interesting and promising results.     

Laboratory evaluation of dripper performance

The catch can method is traditionally used for evaluating performance of drip systems. Two variations of this method are commonly applied in laboratory testing of drippers: the sequential and the simultaneous method. This study compared uniformity and measurement uncertainty of the two methods, with the overall aim of improving irrigation water management. The simultaneous method was found to have a lower coefficient of variation (C_v) and measurement uncertainty, indicating that it is more accurate than the sequential method. In all the tests, however, the C_v was determined to be <5%, which is acceptable as per the current reference standard.     

A practical taxonomy of methods and literature for managing uncertain spatial data in geographic information systems

Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.     

Uncertainty of the fatigue damage arising from a stochastic process with multiple frequency modes

Predicting the variance of the fatigue damage due to a stochastic load process is a difficult classical problem that dates back to the 1960s. For many years, the available analytical methods for tackling this problem have been limited to the linear oscillator response under Gaussian white noise excitation. In a recent prior work, the author developed an improved method for calculating the damage variance for a general narrowband Gaussian process. From a fatigue uncertainty perspective, a narrowband process is particularly crucial as the amplitude correlation magnifies the variance. This paper extends the analysis to a multimodal process comprising two or more narrowband components. The proposed method is tractable, involving a single summation for an arbitrary spectral density. Moreover, closed form expressions are available for two special cases, i.e. the components are all linear oscillator responses or the spectral density of each is rectangular. The equations also yield insight on the multilayered correlation mechanisms produced by different narrowband components. The accuracy of the method is verified by rainflow counting of simulated time history stresses.     

Particle size measurement of reference particle candidates and uncertainty region of count and mass based cumulative distribution

In order to confirm reliable particle size measurement technique and to prepare standard reference particles for calibrating particle size measurement devices, uncertainty region of count and mass based size distribution have been theoretically examined. The uncertainty region of count base cumulative size distribution is smaller than that of the mass base cumulative distribution.The uncertainty region of count base cumulative size distribution is nearly constant over wide range of particle diameter and the region is nearly constant for sample size greater than about 20,000.On the other hand, the uncertainty region of mass base cumulative distribution increases with the increase of particle diameter.The reliability of theoretical uncertainty region is confirmed by the experimental data of particle size measurement.     

A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation

The purpose of this work is the analysis of the uncertainties affecting an electric transmission network with wind power generation and their impact on its reliability. A stochastic model was developed to simulate the operations and the line disconnection and reconnection events of the electric network due to overloads beyond the rated capacity. We represent and propagate the uncertainties related to consumption variability, ambient temperature variability, wind speed variability and wind power generation variability. The model is applied to a case study of literature. Conclusions are drawn on the impact that different sources of variability have on the reliability of the network and on the seamless electric power supply. Finally, the analysis enables identifying possible system states, in terms of power request and supply, that are critical for network vulnerability and may induce a cascade of line disconnections leading to massive network blackout.     

学生用品胶粘剂中甲醛含量的不确定度评估

依据GB 21027—2007对学生用品胶粘剂中甲醛含量的不确定度进行了研究。建立了数学模型,详细分析了测定过程中影响结果的各个分量,并对各不确定度分量进行评定,计算出了该法的合成不确定度和扩展不确定度。对分析测试胶粘剂中甲醛含量结果的准确度有重要的指导意义。     

Mechanism optimization based on reaction rate rules

Accurate chemistry models form the backbone of detailed computational fluid dynamics (CFD) tools used for simulating complex combustion devices. Combustion chemistry is often very complex and chemical mechanisms generally involve more than one hundred species and one thousand reactions. In the derivation of these large chemical mechanisms, typically a large number of reactions appears, for which rate data are not available from experiment or theory. Rate data for these reactions are then often assigned using so-called reaction classes. This method categorizes all possible fuel-specific reactions as classes of reactions with prescribed rules for the rate constants. This ensures consistency in the chemical mechanism. In rate parameter optimizations found in the published literature, rate constants of single elementary reactions are usually systematically optimized to achieve good agreement between model performance and experimental measurements. However, it is not kinetically reasonable to modify the rate parameters of single reactions, because this will violate consistency of rate parameters of kinetically similar reactions. In this work, the rate rules, that determine the rates for reaction classes are calibrated instead of the rates of single elementary reactions leading to a chemically more consistent model optimization. This is demonstrated by optimizing an n-pentane combustion mechanism. The rate rules are studied with respect to reaction classes, abstracting species, broken C–H bonds, and ring strain energy barriers. Furthermore, the uncertainties of the rate rules and model predictions are minimized and the pressure dependence of reaction classes dominating low temperature oxidation is optimized.