Estimation Of Measurement Uncertainty Research Articles

Development of algorithms for the end-end system simulation and performance analysis for a high-frequency magnetic diagnostic system: Application to ITER, JET and TCV

An innovative and very detailed end-to-end system modelling tool has been developed and applied to test on simulated data the actual measurement capabilities of any generic high frequency (HF) magnetic diagnostic systems. The main goal of this rather complex tool is to obtain estimates of the intrinsic measurement uncertainties and then assess the actual vs. intended system measurement performance for correctly detecting individual components in the frequency spectrum of HF magnetic instabilities in the plasma. This has paramount consequences not solely for off-line analyses but also, and more importantly, for any real-time application where, as an example, the mode frequency, amplitude and {toroidal, poloidal} mode numbers are used to determine whether, and which, corrective actions need to be taken to stabilize the discharge.The algorithm has been applied to some of the various ITER HF magnetic diagnostic systems, most notably the AJ (LTCC-1D sensors) system as currently designed, hence providing specific confidence levels and error bounds for detecting the modes highlighted in the ITER measurement specifications. Additional analyses have been performed for the TCV and JET HF magnetic diagnostics, providing further constraints on the results obtained with these systems.

APMP-APLAC joint proficiency testing programs for elemental analysis in food with metrological reference values: Assessment of participants' performance considering measurement uncertainties

The Asia Pacific Metrology Program (APMP) and the Asia Pacific Laboratory Accreditation Cooperation (APLAC) joint Proficiency Testing (PT) programs for toxic elements such as cadmium (Cd) and lead (Pb) or nutritional elements such as iron (Fe) and zinc (Zn) in food were organized by the Korea Research Institute of Standards and Science (KRISS) with the aim of enhancing the quality of measurement and metrological traceability in various economies of the Asia Pacific region by evaluating the performance with rigorous evaluation. Three APMP-APLAC joint PT programs for elemental analyses were carried out by KRISS sequentially, where candidate certified reference materials (CRMs) were used as the PT materials and metrologically traceable certified reference values (RVs) were used as the PT assigned values for the evaluation of participants' results, which allows reliable evaluation of participant performance. This article describes the operation of the PTs and the overall performance of the participating laboratories. The effectiveness of these joint PT programs and trends in PT performance assessment are also discussed. These PT programs confirm the significant importance of using the metrologically traceable RVs instead of the consensus values from participants as the PT assigned value for reliable assessment. The lack of understanding of the concept of coverage factor, degree of freedom, standard uncertainty, and expanded uncertainty was revealed by some participants in these PT programs. Interpreting the zeta-scores or En scores, which are derived by using measurement uncertainties, in conjunction with the z-scores is highly meaningful for assessing participants' ability in measurement capabilities and measurement uncertainty evaluation. Assessment of participants' performance considering measurement uncertainties helps the participants to check how reasonable their measurement uncertainty estimation was. The results of PTs also demonstrated that these PT programs are useful for improving the measurement capability of the laboratories, whereas more capability-building in uncertainty evaluation is required for further improvement.

Intra-GUM comparisons for the estimation of measurement uncertainty: Application to a chromatographic assay of four statins in a dry form

The chromatographic method (HPLC) is well-known for its dependability and precision in pharmaceutical analyses for assessing the quality and efficacy of drug products. However, the characteristics of the HPLC method make sense only after a careful evaluation of the measurement uncertainty. Nevertheless, it has been observed that precise identification of the sources of uncertainty resulting from the operational mode using the HPLC technique to assess their standard uncertainty based on the ISO-GUM approach is not obvious.Because of our extensive bibliographic search, we noticed that many studies published on the estimate of the uncertainty in chromatographic methods (HPLC) using the Eurachem/Citac guide are somewhat diverse in their use of this approach. The documentary research revealed four mathematical models namely, GUM1, GUM2, GUM3, and GUM4 that are most used to estimate the measurement uncertainty of the HPLC technique. Hence, a comparison between the four GUM mathematical models was carried out graphically and statistically using one-way ANOVA followed by Tuckey and Scheffe tests. The comparison results show a significant difference, which may create confusion in the reporting of measurement results as well as problems in making sound decisions. This leads to the suggestion that alternative approaches, such as the approach of a total error or ISO 11325, be used to check the ISO-GUM method's calculations of measurement uncertainty.

Practical Considerations for Clinical Laboratories in Top-down Approach for Assessing the Measurement Uncertainty of Clinical Chemistry Analytes.

The top-down (TD) approach using internal quality control (IQC) data is regarded a practical method for estimating measurement uncertainty (MU) in clinical laboratories. We estimated the MU of 14 clinical chemistry analytes using the TD approach and evaluated the effect of lot changes on the MU. MU values were estimated using subgrouping by reagent lot changes or using the data as a whole, and both methods were compared. Reagent lot change was simulated using randomly generated data, and the mean values and MU for two IQC datasets (different QC material lots) were compared using statistical methods. All MU values calculated using subgrouping were lower than the total values; however, the average differences were minimal. The simulation showed that the greater the increase in the extent of the average shift, the larger the difference in MU. In IQC data comparison, the mean values and MU exhibited statistically significant differences for most analytes. The MU calculation methods gave rise to minimal differences, suggesting that IQC data in clinical laboratories show no significant shift. However, the simulation results demonstrated that notable differences in the MU can arise from significant variations in IQC results before and after a reagent lot change. Additionally, IQC material lots should be treated separately when IQC data are collected for MU estimation. Lot changes in IQC data are a key factor affecting MU estimation and should not be overlooked during MU estimation.

The Uncertainty Profile Used for Full Validation of the HPLC Method to Determine 22 Azo Amines in Fabrics.

Azo dyes are synthetic dyes that can degrade to carcinogenic amines, therefore determining their exact concentration is crucial. The purpose of this study is to demonstrate that an HPLC method may be used to quantify 22 azo dye amines in a textile matrix. The HPLC-DAD (Diode Array Detector) technique for measuring 22 amines in a textile matrix was tested using a new graphical statistical strategy based on the building of β-content, γ-confidence tolerance intervals, which allows for good qualimetry of analytical procedures. In this way, we established the approach's ability to perform a full validation of the analytical technique as well as its ability to estimate measurement uncertainty in a simple and uncomplicated way with minimum effort, utilizing only the data collected during the analytical validation. The findings suggest that this technique can properly assess the validity of the HPLC method for simultaneous determination of 22 amines, with 67-90% of compliance results falling within acceptable limits. Using the uncertainty profile methodology, the full validation of an HPLC method for the determination of 22 azo amines in a textile matrix was successfully established. The development and evaluation of an efficient HPLC technique for the simultaneous determination of 22 azo amines in a textile matrix have been completed. The total reliability of the analytical procedure was established by evaluating its measurement uncertainty at each concentration level using the suggested uncertainty profile approach and confirming proportions 67 to 90% of compliance.

Measurement uncertainty estimation technology: justification, conditions and experience of implementation in medical practice

In accordance with GOST R ISO 15189–2015 ‘Medical laboratories. Particular requirements for quality and competence’ for the report on the values of the measured value in the patient’s samples, the laboratory must determine and use the measurement uncertainty in the analytical phase. The article discusses in detail the differences between the general analytical error and measurement uncertainty. The authors have tested a typical algorithm for estimating measurement uncertainty. Mandatory conditions and an algorithm for calculating measurement uncertainty (at the analytical stage) in medical laboratories using quantitative immunochemiluminescence analysis are presented.

A MATLAB‐Based Software for Estimating Measurement Uncertainties in Capillary Viscometry

AbstractThe Mooney wall slip correction procedure is sometimes mandatory in the rheological characterization via capillary viscometry of certain complex fluids that have the tendency of slipping at solid walls. Besides making the measurement more complex, the Mooney procedure may give rise to measurement error amplification due to an imprecise knowledge of the capillary radius, even if the uncertainty is of the order of 0.01 mm. This error amplification may be so large that the result becomes grossly inaccurate, and in the worst case the procedure may even not produce a physically acceptable result. In this work a MATLAB‐based software that can help researchers determine the maximum allowable inaccuracy on the capillary diameter that can yield feasible data for fluids characterization is devised. For best results, though, the user should know in advance the constitutive characteristics of the unknown fluid in an approximate sense.

Deep-learned estimation of uncertainty in measurements of apparent diffusion coefficient from whole-body diffusion-weighted MRI

PurposeTo use deep learning to calculate the uncertainty in apparent diffusion coefficient (σADC) voxel-wise measurements to clinically impact the monitoring of treatment response and improve the quality of ADC maps. Materials and methodsWe use a uniquely designed diffusion-weighted imaging (DWI) acquisition protocol that provides gold-standard measurements of σADC to train a deep learning model on two separate cohorts: 16 patients with prostate cancer and 28 patients with mesothelioma. Our network was trained with a novel cost function, which incorporates a perception metric and a b-value regularisation term, on ADC maps calculated by combinations of 2 or 3 b-values (e.g. 50/600/900, 50/900, 50/600, 600/900 s/mm2). We compare the accuracy of the deep-learning based approach for estimation of σADC with gold-standard measurements. ResultsThe model accurately predicted the σADC for every b-value combination in both cohorts. Mean values of σADC within areas of active disease deviated from those measured by the gold-standard by 4.3% (range, 2.87–6.13%) for the prostate and 3.7% (range, 3.06–4.54%) for the mesothelioma cohort. We also showed that the model can easily be adapted for a different DWI protocol and field-of-view with only a few images (as little as a single patient) using transfer learning. ConclusionDeep learning produces maps of σADC from standard clinical diffusion-weighted images (DWI) when 2 or more b-values are available.

Estimation of Measurement Uncertainty of Additive Manufacturing Parts to Investigate the Influence of Process Variables

Estimation of Measurement Uncertainty of Additive Manufacturing Parts to Investigate the Influence of Process Variables

Evaluating chemicals of emerging concern in the Ganga River at the two major cities Prayagraj and Varanasi through validated analytical approaches.

Evaluating environmental water quality means to assess and protect the environment against unfriendly impacts from various organic impurities emerging from industrial emissions and those released during harvesting. Potential risks related with release of polycyclic aromatic hydrocarbons (PAHs), pesticides and pharmaceuticals (PhAcs), and personal care products (PCPs) into the environment have turned into an increasingly serious issue in ecological safety. Monitoring helps in control of chemicals and ecological status compliance to safeguard specific water uses, for example, drinking water abstraction. A longitudinal review was carried out for 55 different persistent organic pollutants (POPs) for the Ganga River which passes through the urban areas of Prayagraj and Varanasi, India, through validated analytical approaches and measurement uncertainty (MU) estimation to assess their potential use for routine analysis. Furthermore, environmental risk assessment (ERA) carried out in the present study has revealed risk quotient (RQ) higher than 1 in a portion of the aquatic bodies. Using a conservative RQ strategy, POPs were assessed for having extensive risks under acute and chronic exposure, proposing that there is currently critical ecological risk identified with these compounds present in the Ganga River. In general, these outcomes demonstrate a significant contribution for focusing on measures and feasible techniques to minimize the unfavorable effects of contaminants on the aquatic environment.

Evaluation of Fire Models by Using Local and Global Metrics and Experimental Uncertainty Estimates: Application to OECD/NEA Prisme Door Tests

The use of numerical methods in fire safety investigations for civil buildings and nuclear facilities has received enormous attention in recent years. To evaluate quantities—such as gas temperatures—in fire models, local metrics using single points (e.g. comparing maximum or minimum peak value of two time series) are well-established. Experimental (measurement and model input) uncertainty estimates can be used to quantify the model uncertainty. Although the peak value is a relevant and well-defined quantity, global metrics comparing the entire course of two time series can often provide additional information for the validation of fire models. A comparative methodology COMET for evaluating the predictive power of fire models is developed and presented in this paper. In the methodology, both local and global metrics are combined to incorporate the explanatory power of both quantities in the validation process. While uncertainty analysis is well established for peak values, to the best of our knowledge, there are no analytic results on quantifying the uncertainty of the global metric in the literature. We address the latter based on experimental measurements and derive confidence regions for both metrics. Finally, this paper summarizes the results using COMET to validate the Fire Dynamics Simulator (FDS) version 6 for a room fire scenario. Validation examples are tests 3, 4 and 5 of the DOOR series of the international OECD/NEA PRISME project, in which the transport of heat and flue gases through a door between two rooms was examined. Using COMET, we can easily identify sensors with high level of agreement between model and experimental results with respect to the local and/or the global metric.

ON-SITE ACCURACY COMPARISON OF CAPACITOR AND INDUCTIVE VOLTAGE TRANSFORMERS

In this paper an on-site accuracy comparison of capacitor and inductive voltage transformers is presented. A 400/110 kV transformer substation in Croatia has been chosen as an appropriate location for the comparison as both types of transformers (capacitor and inductive) operate there simultaneously. Each transformer type is a part of one of the two existing measuring chains for measurement of electrical energy. Their accuracy comparison is, therefore, carried out indirectly, by actually comparing the energies measured by the first and the second measuring chain and then estimating the measurement uncertainty of their difference. Without measurement uncertainty, a parameter that shows the quality of any measurement result, it is generally not possible to conclude about the accuracy of measurement or to compare measurement results mutually. In this measurement uncertainty estimation real on-site conditions in transformer substation, especially those which effect voltage transformer accuracy, have been taken into account (voltage, transformer load, frequency, temperature, etc.)

Practical approach for an easy determination of the limit of detection and uncertainty budget associated with on-line measurements of gas and aerosols by ion chromatography

The Monitor for Aerosols and Gases in Ambient air (MARGA) is an on-line gas and aerosol sampling and analysis system based on ion chromatography (IC) that allows the monitoring at 1-h time resolution of major water-soluble atmospheric species in the gas phase (NH3, HCl, HONO, HNO3, SO2) and the particle phase (NH4+, Na+, K+, Ca2+, Mg2+, Cl−, NO3−, SO42−). The lack of a common procedure among users to determine the LOD and the uncertainty of measurements for each species led to the comparison of four different operational approaches for the LOD determination, one manual and three automatic. This comparison highlighted the high NO3− blank values around 0.6 μg m−3 when using a HNO3-based cation eluent, so the p-TSA-based eluent was proposed instead. A model for an easy estimation of measurement uncertainties is suggested based on main sources of uncertainty (liquid sample volume, air volume, representativeness of the sample, accuracy of the internal standard preparation, chemical background, repeatability), applied to a real dataset acquired in a rural site in the North of France. It gives relative average uncertainties between 5 and 30% for NH3, HONO, HNO3, SO2, NH4+ NO3− and SO42−, while Na+, K+, Ca2+, Mg2+ and Cl− range between 45% and >100%. A comparison between our dataset and other studies confirmed that the variation of the uncertainty budget depends on environmental concentrations of the species and site typology. The practical recommendations drawn in this paper may be helpful to the user community of gas and aerosol online samplers coupled to IC analysis.

Determination of alpha factors for monitoring of aeration systems with the ex situ off-gas method: experience from practical application and estimation of measurement uncertainty

Performance of aeration systems in wastewater treatment plants (WWTP) under process conditions can be monitored with off-gas tests. The ex situ off-gas method transfers activated sludge from an adjacent aeration tank into aerated columns to determine oxygen transfer parameters (e.g., the α-factor). This method is an alternative to in situ off-gas testing with hoods at the tank surface; however, its application and measurement uncertainty have not been examined yet. We outline our experience from long-term off-gas testing with two pilot-scale test reactors (8.3 m3 volume). Global variance-based sensitivity analysis using Sobol’ indices revealed oxygen concentration in off-gas and dissolved oxygen as the most important input quantities to determine α-factors accurately. Measurement uncertainty of other instruments was negligible. These findings are transferable to in situ off-gas hoods because the methods are similar. Random measurement error of α-factors was estimated with uncertainty analysis and comparison measurements to a relative standard deviation of about ± 2.8% for our ex situ pilot setup. Diffuser fouling, biofilm growth, or sensor drift caused systematic errors avoidable by maintenance. Additional mixing of bubble column due to sludge inflow into ex situ tanks led to a systematic overestimation of α-factors at lower airflow rates. Hence, the ex situ off-gas method is not suitable to determine α-factors for the design of aeration systems but offers unique possibilities for research of oxygen transfer dynamics and development of aeration equipment because ex situ columns can be operated independently from a full-scale activated sludge tank.

To the Editor.

To the Editor: We read with interest the article by Tababa et al1 describing differences between recommended surgical margins and measured histological margins in melanoma. In the discussion, they do mention in passing that among other factors, discordance between histologic and surgical margins may be due to differences in interpretation of histological margins between pathologists. We would like to highlight the importance of measurement uncertainty in histopathologic margin measurement. There are no measurements, especially in medicine, which are exact—every laboratory measurement, whether it is sodium measured in plasma, the number of white cells in a smear, Breslow depth,2 or histological measurement to margins has some degree of error. In clinical chemistry and laboratory medicine, measurement uncertainty assessment is required in accordance with ISO 17025 and ISO 151893 but seems often ignored in anatomical pathology measurements. For example, we have recently shown that there is measurement uncertainty in measuring margins for basal cell carcinoma and that this uncertainty is dependent on pathologist factors such as which pathologist measures the margins and specimen factors, for example, which actual cross-section is being examined.4 The different methods used to measure margins, for example, graticule, stage micrometer, or eyepiece field diameter may also contribute to error. We have no reason to believe that melanoma margin assessment would be any different. Melanoma margins, especially the in situ component, are more complicated by the fact that there is often debate about what is the “last”' malignant cell and that this assessment could potentially bring about a large variation in assessed margins. We note that 2 different dermatopathologists measured the margins in this study, but no estimates of measurement uncertainty (including differences between pathologist measurements of the same slide) were made. In addition, the number quoted in the current article for specimen shrinkage (15%) seems not to be an absolute number but a range. In the report referenced, the actual range for width change after immersion in formalin was 18.75% (indicating expansion) to 37.50%,5 again adding to the uncertainty of the real histological margins. In summary, it is difficult to interpret the measurement made by 1 pathologist, and how close to the margin it actually is in truth, and how this relates statistically to the clinical (surgical) measurement. It behoves pathologists in any laboratory specialty to appreciate that no measurement is exact, including histologic measurements. Measures of uncertainty should be established for appropriate interpretation of histopathologic margin measurements and included in studies such as the current one.

Temperature rise of power transformers: comments and proposals to IEC 60076-2:2011

Two years ago, a new, third edition of IEC 60076-2 standard was published [1]. Over a period of two years, we have had the opportunity to evaluate this new standard in practice. In the paper, it is shown that the criterion for stagnation 1K/ h + 3h is not entirely satisfying. Better criterion is 1K/3h, or extrapolation to stagnation - as given in second edition of the standard. A formula for hot-spot determination is not complete and it is suggested how to improve it. In the new standard, three formulas for winding average temperature determination are given. Based on experiments, we conclude that the best formula is the simplest one, and two additional formulas are without any benefit. According to [1], paragraph 7.11, measurement uncertainty estimates of results should be given in test reports - but only as information. No procedure for measurement uncertainty estimation is given, and measurement uncertainty is not used in decision-making. Therefore, the third edition of the standard is uncompleted and not motivating in terms of efforts to increase the quality of the measurement results. In the paper, the procedure for measurement uncertainty estimation is proposed and suggestion is given for appropriate decision making.

Comparison of GUM and Monte Carlo Methods for Measurement Uncertainty Estimation of the Energy Performance Measurements of Gas Stoves

Abstract The paper presents the comparison of uncertainty measurement estimations of the energy performances of gas stoves. The Guide to the Expression of Uncertainty in Measurement (GUM) framework and two Monte Carlo Simulation (MCM) approaches: ordinary and adaptive MCM were applied for the energy performance uncertainty: thermal energy and efficiency measurement uncertainties. The validation of the two MCMs is performed by comparing the MCM estimations to the GUM estimations for the thermal energy and efficiency measurement results. A test method designed in Indonesia National Standard SNI 7368:2011 was employed for the thermal energy and efficiency determinations. The results of the GUM and two MCM methods are in good agreement for the estimation of the thermal energy value. Significant differences of the uncertainty estimations for the thermal energy and efficiency results are observed for both GUM and MCM methods. Both the ordinary and adaptive MCM estimations give larger coverage interval compared to the GUM method. The adaptive MCM can give similar estimations with a much lower number of iterations compared to the ordinary MCM. From the estimation difference between the GUM and MCM methods, suggestions are needed for the improvement in measurement models for thermal energy and efficiency of the standard.

A Study of a Miniature TDLAS System Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions from Oil and Gas Production Assets and Other Industrial Emitters

In recent years, industries such as oil and gas production, waste management, and renewable natural gas/biogas have made a concerted effort to limit and offset anthropogenic sources of methane emissions. However, the state of emissions, what is emitting and at what rate, is highly variable and depends strongly on the micro-scale emissions that have large impacts on the macro-scale aggregates. Bottom-up emissions estimates are better verified using additional independent facility-level measurements, which has led to industry-wide efforts such as the Oil and Gas Methane Partnership (OGMP) push for more accurate measurements. Robust measurement techniques are needed to accurately quantify and mitigate these greenhouse gas emissions. Deployed on both fixed-wing and multi-rotor unmanned aerial vehicles (UAVs), a miniature tunable diode laser absorption spectroscopy (TDLAS) sensor has accurately quantified methane emissions from oil and gas assets all over the world since 2017. To compare bottom-up and top-down measurements, it is essential that both values are accompanied with a defensible estimate of measurement uncertainty. In this study, uncertainty has been determined through controlled release experiments as well as statistically using real field data. Two independent deployment methods for quantifying methane emissions utilizing the in situ TDLAS sensor are introduced: fixed-wing and multi-rotor. The fixed-wing, long-endurance UAV method accurately measured emissions with an absolute percentage difference between emitted and mass flux measurement of less than 16% and an average error of 6%, confirming its suitability for offshore applications. For the quadcopter rotary drone surveys, two flight patterns were performed: perimeter polygons and downwind flux planes. Flying perimeter polygons resulted in an absolute error less than 36% difference and average error of 16.2%, and downwind flux planes less than 32% absolute difference and average difference of 24.8% when flying downwind flux planes. This work demonstrates the applicability of ultra-sensitive miniature spectrometers for industrial methane emission quantification at facility level with many potential applications.

A fusion approach to improve accuracy and estimate uncertainty in cuffless blood pressure monitoring

A substantial barrier to the clinical adoption of cuffless blood pressure (BP) monitoring techniques is the lack of unified error standards and methods of estimating measurement uncertainty. This study proposes a fusion approach to improve accuracy and estimate prediction interval (PI) as a proxy for uncertainty for cuffless blood BP monitoring. BP was estimated during activities of daily living using three model architectures: nonlinear autoregressive models with exogenous inputs, feedforward neural network models, and pulse arrival time models. Multiple one-class support vector machine (OCSVM) models were trained to cluster data in terms of the percentage of outliers. New BP estimates were then assigned to a cluster using the OCSVMs hyperplanes, and the PIs were estimated using the BP error standard deviation associated with different clusters. The OCSVM was used to estimate the PI for the three BP models. The three BP estimations from the models were fused using the covariance intersection fusion algorithm, which improved BP and PI estimates in comparison with individual model precision by up to 24%. The employed model fusion shows promise in estimating BP and PI for potential clinical uses. The PI indicates that about 71%, 64%, and 29% of the data collected from sitting, standing, and walking can result in high-quality BP estimates. Our PI estimator offers an effective uncertainty metric to quantify the quality of BP estimates and can minimize the risk of false diagnosis.

An approach and discussion of a simulation based measurement uncertainty estimation for a floating lidar system

In recent years, floating lidar systems (FLS) have been used in increasing numbers for project planning and design of offshore wind farm projects. To assess the quality of the measured data or the wind resources, an exact knowledge of the measurement uncertainty of the FLS is important. However, this is difficult because there is usually no reference measurement system at the offshore sites where FLSs are to be used to assess wind resources. In order to estimate the quality of the measurements or the measurement uncertainty for a site without a reference measurement system, in this case only measurement uncertainties from measurement campaigns or trial campaigns that have already been carried out can be used. However, the respective wind and wave conditions differ from location to location. In this respect, a direct transfer of the measurement uncertainty from one measurement location to another location is again subject to a certain uncertainty.In this paper, we explore the possibilities of a different, simulation-based, approach. First, we discuss which parts of the measurement uncertainty of the FLS can be investigated in the context of simulations. Additionally, we present a workflow for the simulation of an FLS for different wind and wave conditions and an approach to determine and compare the simulated bin-averaged deviations for these conditions with real measurement data. Finally, we show a comparison of the simulated uncertainties with measurement uncertainties determined during a six-month measurement campaign of an FLS against an offshore measurement mast and a fixed reference lidar and give an outlook on possible further use cases of this simulation-based methodology.