Uncertainty of discharge measurement using salt dilution

2020 ◽  
Author(s):  
Alexandre Hauet ◽  
Kristoffer Florvaag-Dybvik ◽  
Mads-Peter Jakob Dahl ◽  
Frode Thorset Kvernhaugen ◽  
Knut Magne Møen ◽  
...  
Keyword(s):  
Error Sources ◽  
Discharge Measurement ◽  
Uncertainty In Measurement ◽  
Perfect Mixing ◽  
Conductivity Curve ◽  
New Sensors ◽  
Following Error ◽  
Expression Of Uncertainty ◽  
Complete Framework ◽  
New Framework

<p>Discharge measurement using salt dilution is an old method, but it has been recently more and more used thanks to the development of new sensors making it possible to measure conductivity and compute discharge in real-time. Salt dilution is very well suited for turbulent rivers, such as mountain streams. The ISO standard ISO 9555 propose a normative framework to estimate uncertainty, but it was published in 1994 and is now obsolete for new sensors and computational capabilities. In this article, we propose a complete framework to compute the uncertainty of a salt dilution gauging following the GUM (Guide to the expression of uncertainty in measurement) method that take into account the following error sources:  (i) the uncertainty in the mass of salt injected, (ii)  the uncertainty in the measurement of time, (iii) the uncertainty in the Conductivity to Concentration law, (iv) the uncertainty if a measurement conductivity is out of the range of the Conductivity to Concentration law, (v) the uncertainty in the computation of the area under the conductivity curve, (vi) the uncertainty due to a not perfect mixing of the tracer if the mixing length between injection and the probes is not reached (vii) the uncertainty due to a loss or a gain of tracer between the injection and the probes if tracer can be adsorbed for example and (viii) the uncertainty due to unsteadiness of the flow  i.e. variation of discharge during the measurement. The method for computing each uncertainty source is presented and the new framework is applied to a set of real measurements and compared to the expertise of field hydrologists.</p>

scholarly journals Critique of the Guide to the Expression of Uncertainty in Measurement Method of Estimating and Reporting Uncertainty in Diagnostic Assays

2003 ◽  
Vol 49 (11) ◽  
pp. 1818-1821 ◽  
Author(s):  
Jan S Krouwer
Keyword(s):  
Troponin I ◽  
Systematic Errors ◽  
Ease Of Use ◽  
Uncertainty Interval ◽  
Error Sources ◽  
Analytical Error ◽  
Uncertainty In Measurement ◽  
Diagnostic Assays ◽  
Medical Need ◽  
Expression Of Uncertainty

Abstract Background: The Guide to the Expression of Uncertainty in Measurement (GUM) provides instructions for constructing uncertainty intervals for a measurement. This method is usually reserved for reference materials, but GUM has been recently proposed as a way to express uncertainty for commercial diagnostic assays. Methods: Using the official GUM standard and published applications of GUM to commercial diagnostic assays, I undertook an analysis to evaluate whether applying GUM to commercial diagnostic assays is warranted. Results: Certain important assays, such as troponin I, would not be candidates for GUM because troponin I is not a well-defined physical quantity. Unlike definitive methods, in which efforts are taken to detect and eliminate all systematic error sources, commercial assays often trade off features such as ease of use and cost with accuracy and allow systematic errors to be present as long as the overall accuracy meets the medical need goal. Laboratories are hindered in preparing GUM models because the knowledge required to specify some systematic errors is often available only to manufacturers. Some non-GUM methods to estimate uncertainty rely on observed data, which include both known and unknown sources of error. The occurrence of large, unknown errors for assays in routine use (e.g., outliers) is not unusual because diagnostic assays must be chemically specific in the presence of thousands of potentially interfering substances. There is no provision in GUM to deal with unexplained outliers, which may lead to uncertainty intervals that are not wide enough. Some clinicians assume that diagnostic assay results have little uncertainty. This situation may be made worse by including an uncertainty interval, which implies certification. Conclusions: Evaluations for accuracy (total analytical error) based on describing the distribution of result differences between commercial assays and reference methods indicate that some assays have a few results with large differences (e.g., outliers). This leads to a wide accuracy interval (total analytical error limits). It is unlikely that GUM would be able to predict these wide intervals, especially because there is little or no provision for outlier treatment in GUM. Presenting too narrow GUM uncertainty intervals to clinicians would be misleading. The modeling used by practitioners of the GUM method is potentially useful in improving quality, but commercial diagnostic assays are not ready for GUM uncertainty statements.

Verification of the Calculation Assumptions Applied to Solutions of the Acoustic Measurements Uncertainty

2015 ◽  
Vol 39 (2) ◽  
pp. 199-202
Author(s):  
Wojciech Batko ◽  
Renata Bal
Keyword(s):  
Normal Distribution ◽  
Confidence Intervals ◽  
Uncertainty Of Measurement ◽  
Acoustic Measurements ◽  
Uncertainty In Measurement ◽  
Sound Levels ◽  
Measurement Results ◽  
Analysis Of Results ◽  
Essential Problem ◽  
Expression Of Uncertainty

Abstract The assessment of the uncertainty of measurement results, an essential problem in environmental acoustic investigations, is undertaken in the paper. An attention is drawn to the - usually omitted - problem of the verification of assumptions related to using the classic methods of the confidence intervals estimation, for the controlled measuring quantity. Especially the paper directs attention to the need of the verification of the assumption of the normal distribution of the measuring quantity set, being the base for the existing and binding procedures of the acoustic measurements assessment uncertainty. The essence of the undertaken problem concerns the binding legal and standard acts related to acoustic measurements and recommended in: 'Guide to the expression of uncertainty in measurement' (GUM) (OIML 1993), developed under the aegis of the International Bureau of Measures (BIPM). The model legitimacy of the hypothesis of the normal distribution of the measuring quantity set in acoustic measurements is discussed and supplemented by testing its likelihood on the environment acoustic results. The Jarque-Bery test based on skewness and flattening (curtosis) distribution measures was used for the analysis of results verifying the assumption. This test allows for the simultaneous analysis of the deviation from the normal distribution caused both by its skewness and flattening. The performed experiments concerned analyses of the distribution of sound levels: LD, LE, LN, LDWN, being the basic noise indicators in assessments of the environment acoustic hazards.

Smart design of intelligent companion toys for preschool children

2020 ◽  
pp. 1-14
Author(s):  
Xin Wang ◽  
Nian Yin ◽  
Zhinan Zhang
Keyword(s):  
Artificial Intelligence ◽  
Early Childhood ◽  
Preschool Children ◽  
Essential Role ◽  
Childhood Education ◽  
Child Centered ◽  
Toy Design ◽  
Complete Framework ◽  
New Framework

Abstract Early childhood education has long-lasting influences on people, and an appropriate companion toy can play an essential role in children's brain development. This paper establishes a complete framework to guide the design of intelligent companion toys for preschool children from 2 to 6 years old, which is child-centered and environment-oriented. The design process is divided into three steps: requirement confirmation, the smart design before the sale, and the iterative update after the sale. This framework considers the characteristics of children and highlights the integration of human and artificial intelligence in design. A case study is provided to prove the superiority of the new framework. In addition to enriching the research on intelligent toy design, this paper also guides for practitioners to design smart toys and helps in children's cognitive development.

Interpretation and use of standard atomic weights (IUPAC Technical Report)

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Adriaan M. H. van der Veen ◽  
Juris Meija ◽  
Antonio Possolo ◽  
David Brynn Hibbert
Keyword(s):  
Monte Carlo ◽  
Atomic Weight ◽  
Standard Uncertainty ◽  
Uncertainty In Measurement ◽  
Propagation Of Uncertainty ◽  
A Value ◽  
The Monte Carlo Method ◽  
Technical Report ◽  
Molecular Masses ◽  
Expression Of Uncertainty

Abstract Many calculations for science or trade require the evaluation and propagation of measurement uncertainty. Although relative atomic masses (standard atomic weights) of elements in normal terrestrial materials and chemicals are widely used in science, the uncertainties associated with these values are not well understood. In this technical report, guidelines for the use of standard atomic weights are given. This use involves the derivation of a value and a standard uncertainty from a standard atomic weight, which is explained in accordance with the requirements of the Guide to the Expression of Uncertainty in Measurement. Both the use of standard atomic weights with the law of propagation of uncertainty and the Monte Carlo method are described. Furthermore, methods are provided for calculating uncertainties of relative molecular masses of substances and their mixtures. Methods are also outlined to compute material-specific atomic weights whose associated uncertainty may be smaller than the uncertainty associated with the standard atomic weights.

ISO/TS 20914:2019 – a critical commentary

2020 ◽  
Vol 58 (8) ◽  
pp. 1182-1190 ◽  
Author(s):  
Ian Farrance ◽  
Robert Frenkel ◽  
Tony Badrick
Keyword(s):  
Measurement Uncertainty ◽  
Measurement Data ◽  
International Normalized Ratio ◽  
Medical Laboratory ◽  
Uncertainty In Measurement ◽  
Medical Laboratories ◽  
Functional Relationships ◽  
Critical Commentary ◽  
Combined Uncertainty ◽  
Expression Of Uncertainty

AbstractThe long-anticipated ISO/TS 20914, Medical laboratories – Practical guidance for the estimation of measurement uncertainty, became publicly available in July 2019. This ISO document is intended as a guide for the practical application of estimating uncertainty in measurement (measurement uncertainty) in a medical laboratory. In some respects, the guide does indeed meet many of its stated objectives with numerous very detailed examples. Even though it is claimed that this ISO guide is based on the Evaluation of measurement data – Guide to the expression of uncertainty in measurement (GUM), JCGM 100:2008, it is with some concern that we believe several important statements and statistical procedures are incorrect, with others potentially misleading. The aim of this report is to highlight the major concerns which we have identified. In particular, we believe the following items require further comment: (1) The use of coefficient of variation and its potential for misuse requires clarification, (2) pooled variance and measurement uncertainty across changes in measuring conditions has been oversimplified and is potentially misleading, (3) uncertainty in the results of estimated glomerular filtration rate (eGFR) do not include all known uncertainties, (4) the international normalized ratio (INR) calculation is incorrect, (5) the treatment of bias uncertainty is considered problematic, (6) the rules for evaluating combined uncertainty in functional relationships are incomplete, and (7) specific concerns with some individual statements.

scholarly journals XML-based IUPAC standard for experimental, predicted, and critically evaluated thermodynamic property data storage and capture (ThermoML) (IUPAC Recommendations 2006)

2006 ◽  
Vol 78 (3) ◽  
pp. 541-612 ◽  
Author(s):  
Michael Frenkel ◽  
Robert D. Chiroco ◽  
Vladimir Diky ◽  
Qian Dong ◽  
Kenneth N. Marsh ◽  
...  
Keyword(s):  
Data Storage ◽  
Chemical Reactions ◽  
Data Communication ◽  
Thermochemical Property ◽  
Uncertainty In Measurement ◽  
Communication Processes ◽  
Property Data ◽  
Extensible Markup ◽  
Pure Compounds ◽  
Expression Of Uncertainty

ThermoML is an Extensible Markup Language (XML)-based new IUPAC standard for storage and exchange of experimental, predicted, and critically evaluated thermophysical and thermochemical property data. The basic principles, scope, and description of all structural elements of ThermoML are discussed. ThermoML covers essentially all thermodynamic and transport property data (more than 120 properties) for pure compounds, multicomponent mixtures, and chemical reactions (including change-of-state and equilibrium reactions). Representations of all quantities related to the expression of uncertainty in ThermoML conform to the Guide to the Expression of Uncertainty in Measurement (GUM). The ThermoMLEquation schema for representation of fitted equations with ThermoML is also described and provided as supporting information together with specific formulations for several equations commonly used in the representation of thermodynamic and thermophysical properties. The role of ThermoML in global data communication processes is discussed. The text of a variety of data files (use cases) illustrating the ThermoML format for pure compounds, mixtures, and chemical reactions, as well as the complete ThermoML schema text, are provided as supporting information.

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