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The result of a chemical measurement is consequence of a set of steps that begins with sample selection. The aim of this study was to evaluate the relative importance of the sampling in overall measurement uncertainty, taking as study case physicochemical measurements of diesel. The empirical method used was by duplicates, and the treatment of data sets was performed by four different statistical techniques: classic analysis of variance, robust analysis of variance and two different Range Statistics models. The choice must be backed by previous evaluation of data set in terms of normality, independence, presence of outliers and homogeneity of variance. It was found that Range Statistics produced most reliable results under different premises and for the variety of physicochemical parameters evaluated. Robust analysis of variance failed indicates proper influence of sampling even it is a test designed to work under the lack of some of the proper premises.

Sometimes, analytical chemicals forget that the measurement process begins with the selection of the sample; thus, it must be understood that the measurement uncertainty is constituted by the association of the uncertainty arising from the sampling and the uncertainty arising from the traditional analytical process, that which is carried out in the laboratory. The analytical process is well-controlled, so its uncertainty is well defined; however, the uncertainty arising from sampling, for not having this controlled environment, is often not evident, so that there is still no culture to consider it for the calculation of measurement uncertainty. This study discusses the importance of the sampling uncertainty concerning the analytical uncertainty and details the current approaches available in the literature, such as the classical analysis of variance, the robust analysis of variance, and the range statistics. Moreover, this work highlights the recent manuscripts that are using these mentioned approaches, correlating them to the matrices, chemical and physical-chemical analytes, and analytical techniques. Finally, some case studies using the uncertainty information in compliance assessment show that the measurement uncertainty arising from sampling in chemical and physicochemical analyses cannot always be neglected.

Historically, owing to the increase in processing capacity over the years, validation and adjustment of measurements have become imperative. In particular, concerning discussions related to data and results in analytical chemistry, there is always a need to improve their reliability. The data reconciliation technique has the objective of using measurement redundancies to obtain the best estimate of the true value and, consequently to minimize its uncertainty. Unfortunately, this powerful tool is less known and used by analytical chemists compared to other areas. This approach can be satisfactorily performed in decision-making procedures that focus on chemical analysis, chemometrics, biochemistry analysis, forensics, and environmental sciences, such as in a characterization study, regarding conformance or nonconformance with the specification, doubts related to the malfunctioning of meters and about the compatibility of test methods. This work discusses and sheds light on the importance of data reconciliation, including data reconciliation statistics and application of the technique, traditional data reconciliation in analytical chemistry, principal component analysis based on data reconciliation in analytical chemistry, and fuzzy data reconciliation in analytical chemistry.

The authors’ aims is to evaluate the reuse of microcells in a test method for sulfur in diesel fuel and gasoline–ethanol blends by monochromatic wavelength dispersive X-ray fluorescence spe...

The discrepant measurement results regarding the conformity assessment of diesel and gasoline fuels may lead to commercial dispute between producers (refinery) and consumers (storage terminal). The aim of this work was to apply data reconciliation in order to solve the discrepancy between producers’ and consumers’ measurements and allow to make decisions regarding the conformity/non-conformity assessment. Diesel and gasoline samples were analyzed in respect to total sulfur content and flash point and for sulfur content and final boiling point, respectively. Discrepant results between consumers’ and producers’ measurements were subject to data reconciliation. Data reconciliation was perform using a MS Excel spreadsheet. The sheet was divided into five sections: ‘Specification limits’, ‘Producer’s measurement’, ‘Consumer’s measurement’, ‘Reconciled measurement’, and ‘Histograms’. Data reconciliation was useful to solve the discrepancy between producer’s and consumer’s measurements in most of the studied cases, since provided reconciled values inversely weighted as function of measurement uncertainty. In addition, data reconciliation provided a reduced measurement uncertainty.

This study evaluates the results of efficiency and consumption tests on gas household appliances and their influence on the classification of the Brazilian Labeling Program. Historically, based on results in interlaboratory comparisons, there is a doubt concerning if the algorithms correct properly the differences among different altitudes. Data from efficiency and consumption tests were collected in two cities with different altitudes, and the proposed calculation methodology is compared with the traditional one. The results show that the arithmetic average, used in the calculation of the efficiency of the burners on the stove table, justifies being replaced by the weighted average, after evaluating the behaviour of the data and treating outliers. The uncertainty of the efficiency and consumption tests was not enough to change the classification range of the product's energy efficiency label. It is concluded that statistically a difference is observed between the results at sea level and at altitude above sea level; since the tests were applied by the same operator using the same apparatus, the only parameter that leaves a doubt is the algorithms for the correction of the altitude. Shortly, this study will be part of a revised Brazilian standard.

The authors’ aims are to compare the performance of two test methods and participants’ results with combined results from a group in the same round and limits determined by the variability of parti...

The authors’ objective is to manage sulfur content in gasoline over a multi-product pipeline using data derived from a correlation study. Sulfur content is analyzed by ultraviolet fluorescence or monochromatic wavelength dispersive X-ray fluorescence spectrometry in three different sampling points by three laboratories. At the same time, this study evaluates the homogeneity between laboratories/methods and if the analytical results of data vary in different sampling points of the pipeline. By means of two-way analysis of variance with interaction, the results show that there are variations along the multi-product pipeline besides differences between methods and laboratories.

In any commercial transaction, the presence of tolerances from specification limits is essential to ensure that the true value of the property of interest is sufficiently close to the specification value with a mutually agreed probability, so that there is no litigation between the parties. In order to meet this requirement, this tolerance is treated elegantly as a “toast” or more technically as a superior quality that the customer receives—giveaway. This work presents a new methodology for determining the tolerance limits of critical properties in some fuels, based on the reproducibility, on the difference between the averages of all acceptable results of each laboratory and on the specifications derived from the Brazilian National Agency for Oil, Natural Gas and Biofuels. Applying this approach to flash point by tag closed, final boiling point, volatility (95 % evaporated temperature), electrical conductivity and total sulfur content of some fuels and by means of a hypothesis test, the results show that this methodology was validated for most of the proposed new limits.

Calibration acceptance criteria for pressure and temperature measuring devices used in orifice plate gas flowmeters were specified. The study was motivated by the introduction of a Brazilian regulation that specifies technical and legal requirements for in-field measurements of oil and gas flows. In compliance with international best practices, the applicable regulation, which establishes uncertainty levels for flow measurements (1.5% for fiscal/custody transfer measurements and 2% for appropriation measurements), did not set up limits of acceptance of uncertainties associated with pressure and temperature measuring devices. The effects of these uncertainties in measurements were evaluated. By making use of the Design of Experiments and Response Surface Method (RSM), acceptance criteria were sought to comply with the applicable regulation. The use of the methodology proved to be very useful as low uncertainties were obtained in all ten metering stations investigated. In the worst cases (in three stations only), uncertainties were lower than 0.2% of the correspondent full-scale reading. The response surface methodology also showed that the minimum measuring capacity to meet the regulatory uncertainty requirements are 0.05% for differential pressure calibrators and 0.01% for the static pressure (relative to the full-scale reading).

This paper discusses the conception, construction and validation of a gravimetric system conceived as an alternative measurement standard for calibrating liquid flow meters. The ability to evaluate a large mass of a working fluid by measuring, with much lower uncertainty, a smaller quantity of it, reflects the innovative character of the proposed calibration system. In this work, the mass of water (over 10 tons) retained in a large squared (1.50 m × 1.50 m) cross section reservoir (5 m high) is evaluated by weighing a mass of water confined in a much smaller reservoir (0.0835 m diameter, 5 m high), hydraulically connected to the first. A low capacity weigh scale (full scale: 32 kg; resolution: 0.10 g) is used to weigh, under static condition, the water in the smaller reservoir, whose liquid level is the same of the large storage reservoir. The metrological reliability of the proposed gravimetric system—assessed through the propagation of all impacting measurement uncertainties—falls in the range 0.018 % to 0.055 %, depending on the volume of the working fluid transferred throughout the calibration process (varying from a minimum of 0.001 m3 to a maximum of 0.022 m3).

This paper discusses metrologically the best practice regarding the calibration curves applied to H2S mass fractions determination in natural gas by gas chromatography with sulfur chemiluminescence...

Ractopamine is used as an animal feed additive, but its adverse effects led to the necessity of the current monitoring programs of ractopamine residues in food products, so its reliable quantification is indispensable. This work aims to demonstrate the stability of solutions of ractopamine used for calibration of a liquid chromatography–tandem mass spectrometry method. Naturally contaminated samples with ractopamine were quantified using solutions prepared on different days. The stability study was based on an empirical model that considered a straight line (slope = 1) to describe the degradation mechanism. No significant change in the slope was detected. It could be concluded that solutions underpinning calibration curves at two different working intervals were stable for at least 11 months and 5 months, respectively.

International standards propose maximum uncertainties for custody transfer measurements, without establishing maximum permissible differences in the operations between two systems. It is up to the suppliers and customers to negotiate this parameter, which frequently causes disputes because a fixed value is proposed. This study aims to apply a methodology to evaluate the maximum permissible differences in LPG operations for custody transfer measurements for each particular operation using hypothesis tests based on measurement uncertainty instead of using pre-established values. The results showed that, in an isolated system, unlike other methods, environmental conditions do not influence the mass measurement method and its uncertainty. No maximum permissible difference of LPG transferred mass between tank trucks and metering stations exceeds 1.0%; in contrast, when a storage sphere is part of the one of the measurement systems, this parameter depends completely upon the operational conditions, and definitely, a unique value should not be considered.

The process of measuring the performance of gas cooking appliances is based on the simple calculation of the arithmetic mean between the results obtained from different burners, without any metrological rigour related to the behavior of the data. This study proposes a new methodology and compares it against the traditional one. The proposed approach evaluates whether data are far apart on the normality, treats outliers and calculates the efficiency from the position measure inversely weighted by the dispersion measure of each burner. For the datasets studied, there may be divergences between the results found for the efficiency calculation when treated by the traditional approach and the proposed approach. However, this study recommends a detailed analysis of the algorithms used, in order to better understand the reason for the divergences found; as well as the implementation of measurement uncertainty calculation, in order to evaluate the partial overlap between specification ranges.

A computational model of the dynamic behaviour of a go-kart has been implemented as the first step in the development of an electrical vehicle advanced control system and the lateral dynamics model needed its yaw moment of inertia as input value. Therefore, this study presents experimental measurements of the yaw moment of inertia of a recreational go-kart using two similar methodologies: the ‘three cables’ (trifilar) swinging torsion pendulum and the ‘four cables’ (quadrifilar) swinging torsion pendulum. Parallel to the experimental tests carried out, yaw moment of inertia calculation was done by the traditional methodology of mechanical engineering. Also, the measurement uncertainty was calculated for each method. The trifilar method presented, in this test, the lowest measurement uncertainty.

This paper presents a method for measuring flow rates in pipelines based on the flow induced vibration principle using water as fluid, eliminating the need for interrupting the flow and opening of the pipeline for installation of traditional water flow meters. Experimental measurements are carried out in an accredited laboratory for calibration of rate flow meters and a metrological validation, followed by an uncertainty evaluation, are presented. Data analysis is accompanied by a method of optimization that minimizes adjustment errors of measurement using regression by parts and by the selection of the optimum period to estimate more accurately the flow rate. The results meet the specifications of Brazilian Metrology Institute.

A meter proving factor can be considered as a calibration parameter, by expressing the ratio the reference volume and the gross volume of liquid passed through a meter. The international guideline recommends Dixon's test for outliers to a meter proving factor set. However, the literature says that this statistic test is restricted only to data with Gaussian behavior, besides of not to be able to detect and treat two outliers at the same time. Here, Gaussian behavior of the meter proving factor set is evaluated, then different parametric and nonparametric approaches for detection and treating outliers applied to turbine meter proving factors for custody transfer of liquefied petroleum gas are compared. Afterwards, this effect is evaluated in relation to the number of outliers and how this handling affects the variable range criteria for expanded uncertainty in average meter proving factor. The results show that different average meter factors can be reached for each nonparametric and parametric test; anyway, no statistically significant effect between them is noticed.

Improper mixtures of: motor oil with crude oil; and derivatives mixed with other derivatives of lesser commercial value were identified in Brazil by companies in the energy sector. This study shows the great response that a portable NIR spectrometer had to discriminate crude oils and derivatives and to quantify them in blends (crude oils with used motor oil; and naphtha, gasoline, diesel, and kerosene). NIR spectra set were acquired in triplicate using a microNIR™ portable spectrometer, where it was possible to discriminate crude oil from used motor oil with 100% sensitivity, specificity, and precision. Regression models can quantify the oil content of a ternary mixture containing two crude oils (light and heavy oil) and a used motor oil with root mean square error of prediction (RMSEP) of 6.2 and 4.8 wt%, and R2p = 0.9871 and 0.9870 for support vector regression (SVR) and partial least squares (PLS), respectively. About the NIR spectra of naphtha, gasoline, diesel, and kerosene, partial least squares discriminant analysis (PLS-DA) allows the identification of any of these products with sensitivity, specificity, and precision of 100%. For the blends of gasoline and naphtha, the limit of detection (LOD), limit of quantification (LOQ), and RMSEP were 1.3, 4.4, and 1.4 wt%, respectively. Likewise, for diesel and kerosene blends, the PLS model allows the identification of the diesel with LOD, LOQ, and RMSEP of 2.8 wt%, 9.3 wt%, and 11.4 wt%, respectively.

The low-quality of automotive fuels may lead to the generation of pollutants harmful to both environmental and human health. The quality evaluation of automotive fuels requires a multiparameter conformity assessment, which may lead to an increased total risk of false conformity decisions even if all parameters comply with the acceptance limits. Thus, the aim of this work was to propose the establishment of multivariate acceptance limits in order to ensure a reduced total risk of false conformity decisions applied to automotive fuels analysis. Particular and total (consumers’ and/or producers’) risks were estimated using frequentist (specific) and Bayesian (global) approaches. Multivariate acceptance limits were estimated using Monte Carlo method, adopting an appropriate multivariate coverage factor (k’) defined using MS Excel Solver function. The definition of multivariate acceptance limits ensures a total risk below the maximum admissible risk (typically 5%) and was successfully employed in the conformity assessment of automotive fuels (diesel and gasoline). The employment of the multivariate acceptance limits may be useful in the conformity assessment of several multiparameter products.

The goal of this manuscript is the use of the statistical methods to analyze differences caused by the application of the correction methods defined on different standards for the measurement of the volume of liquid petroleum derivatives. This correction is necessary because pressure and temperature variations can cause differences between measurements made by the customer and supplier due to operational condition variations. To standardize this measurement, it was established that all volumes used on transactions in Brazil should be corrected to a base condition (20 °C and 101.325 kPa). To study these possible differences, the applied methodology uses statistical distributions that model the density of the products during the production process and, i.e., uses data collected during certain periods. Corrected density values are then obtained for each method. With these values in hand, a hypothesis test based on measurement uncertainty shows that numerical differences don’t always have statistical significance.

The economic impact that results from the reliability of measurements associated with natural gas (flow rate and fluid properties) and caveats related to custody transfer contracts demands vigilant control of the net balance in the delivery systems. The methodology for data reconciliation has proved to be an effective tool to reduce uncertainties associated with measurements used in the calculations of the net balance in distribution networks such as gas pipelines. The intrinsic nature of the calculation algorithm, founded on the redundancy of measurements, qualifies the technique for increasing confidence in the measurement, thus reducing the individual uncertainty associated with each physical magnitude capable of affecting the measurement. This Brazilian gas pipeline study discusses the adequacy of the data reconciliation technique. The proposed technique proves to be very effective as it generates lower uncertainties than those obtained by traditional techniques: the level of 1% associated with the accountability of the unaccounted for gas was reduced to less than 0.3% when the data reconciliation methodology was used.

Literature describes several procedures based on statistical principles to validate whether the degree of agreement between the results produced by a stream analyzer system—systems for determining chemical and physical characteristics by continual sampling, automatic analysis, and recording or otherwise signaling of output data—and those produced by an independent test measurement procedure, which purports to measure the same property, meets user-specified requirements. However, these documents always consider that the data gathered during validation procedure are normally distributed, and this supposition it is not always true. The aim of this manuscript is to develop four different procedures applied to data with nonparametric behavior. The most representative validation procedure compares measures of position and dispersion, using typical process samples, while the less representative one compares only measures of position, using a reference sample. These nonparametric data are also treated using parametric statistics for comparison. The results show that different conclusions can be reached when the nonparametric data are treated as parametric. A new Brazilian standard is being carried out based on this subject, in order to complement the international standards.

This work aims to evaluate the influences of the water content dissolved in crude oil and of the meter factor on the uncertainty of the fiscal oil measuring system using ultrasonic flow meters, considering that the overall uncertainty of the measuring system shall not exceed 0.3%. The development of this work was motivated by the fact that the Brazilian Technical Regulation for the Measurement of Oil and Natural Gas (RTM) limits which methodologies can be used for water analysis and defines the maximum permissible uncertainty for the oil flow meter in which this analysis is inserted. However, the RTM does not define the uncertainty required for the water analysis. There is a risk of adopting one of the permitted methods of analysis and, even so, the measurement uncertainty of the flow meter exceeding the values defined by the legislation. In addition, the RTM adopts a repeatability criterion when validating the calibration of ultrasonic meters, thus the influence of this aspect on the oil uncertainty is also evaluated. The methodology used is the design of experiments and response surfaces. The results demonstrate that it is possible to simulate the influence of the water content and of the meter factor uncertainties on the overall uncertainty of the oil flow measuring system. Finally, the conclusions show that the average uncertainties currently observed for the water content are adequate to keep the oil measuring system uncertainty within the range allowed by the RTM, but small variations may cause this limit to be exceeded. The influence of the meter factor uncertainty was less than or similar to the influence of the water content. Finally, adoption of an acceptance criterion for the ultrasonic meters based on the uncertainty instead of repeatability is suggested.

The meter factor is the ratio between the reference volume and the indicated test meter volume for a particular flow rate. In some applications, a final and a single meter factor that covers all the flow meter rates is required, and there are several approaches to calculate it. However, none of them are specific to rotary-type natural gas displacement meters. In this paper, certain established approaches, such as AGA 7, AGA 9, non-weighted and weighted regression lines were applied to calibration data of this type of meter and their results were compared. An Excel spreadsheet was developed to calculate the final meter factors using all these approaches and to indicate users the one with the lowest uncertainty, based on input data in order to configure the flow computer. In the specific case studies shown, the approaches using linear regression were found to be more suitable.

Chemical analysts use analytical blanks in their analyses, but seldom is this source of uncertainty evaluated. Generally, there is great confusion. Although the numerical value of the blank, in some situations, can be negligible, its source of uncertainty cannot be. This article discusses the uncertainty contribution of the analytical blank using a numerical example of the copper content in waters by flame atomic absorption spectrometry. The results indicate that the uncertainties of the analytical blank can contribute up to 50% when the blank sample is considered in this analysis, confirming its high impact. This effect can be primarily observed where the analyte concentration approaches the lower range of the analytical curve. Even so, the blank is not always computed. Therefore, the relevance of the analytical blank can be confirmed by uncertainty evaluation.

This work presents a contactless ammeter prototype based on GMR magnetometers, able to measure direct and alternating electrical currents. Two techniques nonlinear curve fitting and artificial neural networks, were used to solve the inverse problem, which is, given the output voltages of the GMR sensors, to estimate the electric current flowing through the conductor - nonlinear curve fitting and artificial neural networks. The performance of both techniques was compared based on the standard uncertainty of the data calculated by each one. The results obtained with the neural networks are significantly better.

The measurement uncertainty is a parameter that marks the reliability and can be divided into two large groups: sampling and analytical variations. Analytical uncertainty is a controlled process, performed in the laboratory. The same does not occur with the sampling uncertainty, which, because it faces several obstacles and there is no clarity on how to perform the procedures, has been neglected, although it is admittedly indispensable to the measurement process. This paper aims at describing the state of the art of sampling uncertainty and at assessing its relevance to measurement uncertainty.

The composition and physicochemical parameters of natural gas can vary in space and time depending upon the gas source and blending. The key parameters of natural gas are important to know for transportation and efficient consumption. Thus, a natural gas quality measurement is required for technical and economic reasons. The data reconciliation technique has the objective of using measurement redundancies to obtain the best estimate of the conventional true value and, consequently, to minimize its uncertainty. This work discusses this subject in analytical applications related to the natural gas industry. This methodology shows to be more suitable than the traditional ones when it is applied to a characterization study, a dispute between supplier and customer, an operation diagnosis in industrial unit, and an among day homogeneity study.