Calculation Of Uncertainty Research Articles

Development of calculation methods for the uncertainty of special mechanical characteristics of structural steel

Understanding of an accuracy related to the evaluation of special mechanical performances of materials is an essential part of the quality control system providing for safe operation of modern structures in severe climatic conditions in far locations where any emergency and repair activities are hindered. In absence of a priori known values of such performances the methodic basis of uncertainty calculation procedures should be developed. Relevance of the problem is supported by the requirement of Russian Accreditation Agency regarding the availability and due application of the corresponding methods in test laboratories as for directly measured parameters as for ones calculated from the test results. Uncertainty calculation procedures are suggested as a background for the developed specialized software.

Reference Material for the Composition of Fuel Oil

Electrical transformers are a key element in the process of distributing electricity from the producer to the final consumer. The reliability of electrical transformers is ensured through systematic monitoring of the structural condition using chemical analysis of fuel (transformer) oil used for electrical insulation and cooling of transformers. The working life of energy oil and paper insulation can be assessed by evaluating the content of antioxidant additive (ionol) and furan derivatives (furfuryl alcohol, furfural, 2-acetylfuran and 5-methylfurfural). The article provides a critical analysis of methods for measuring ionol and furan derivatives in oils. In particular, it has been established that the most widely used methods for the identification of ionol and furan derivatives are liquid and gas chromatography methods with preliminary isolation of analytes based on the principles of liquid/solid-phase extraction. At the same time, the need for matrix reference materials with established metrological traceability was identified for metrological support of methods for measuring the content of ionol and furan derivatives in oils. Therefore, the purpose of this study was the development of a certified reference material (CRM) for the composition of fuel oil. The technology for producing such a CRM makes it possible to prepare the material with the required concentrations of analytes. The article describes the sequence of preparation of a CRM batch and presents the conclusions of studying the stability and between-bottle homogeneity of the material. The given calculation of the standard uncertainty for the certified value of the CRM from the characterization method, heterogeneity, and instability of the material in accordance with GOST ISO Guide 35–2015 deserves attention. The metrological traceability of certified values of the CRM to the unit of value «mass fraction of a component» reproduced by the State Primary Standard of units of mass (molar) fraction and mass (molar) concentration of organic components in liquid and solid substances and materials based on liquid and gas chromatography-mass spectrometry with isotope dilution and gravimetry (GET 208–2019). The competence of the study is confirmed by the fact that the CRM was recognized as GSO 12232–2023.

Field Performance Testing and Test Codes for Gas Compressors

Abstract Field testing of gas compressor packages requires the accurate determination of efficiency, capacity, head, and power in sometimes less than ideal working environments. The results of field tests have significant implications for the compressor manufacturers and their customers, as economic considerations demand that the performance and efficiency of an installation are verified to assure a project's return on investment. Thus, for the compressor manufacturers, as well as for the end-user, an accurate determination of the compressor performance in the field is of vital interest. While field performance tests have to be executed under conditions dictated by the situation at site, factory test codes like ASME PTC10 and ISO 5389 provide guidance. The former code was recently revised, so a discussion of this revised code in the context of site performance testing is appropriate. A key change in PTC10 is the method to calculate polytropic work, which affects data reduction. It also affirms a method to calculate error propagation and test uncertainties. The discussion includes the appropriate use of Equations of State, and the definition of steady state requirements. Different methods to define valid operating conditions for the test, based on similarity considerations are compared. However, field tests, unlike factory tests, are ultimately conducted based on the conditions at site which may or may not conform with test codes, Therefore, calculation of test uncertainties, and the use of observations not covered by the codes are emphasized. The paper attempts to provide guidance for the conduct of field performance tests.

Predicting the impact of wind turbine noise: general overview and results of the PIBE project

The PIBE project aims to improve wind turbine noise prediction methods and to explore new solutions for noise reduction. This five years project brought together French experts in aeroacoustics, sound propagation, experimental noise characterization and wind engineering, and was structured around three work packages. The first one aimed to study amplitude modulation phenomena and focused particularly the characterization of dynamic stall noise. Specific aerodynamic and acoustic measurements were carried out in a wind tunnel, showing the influence of several stall regimes on noise production. The second work package focused on quantifying the uncertainties of noise prediction methods. It developed an open-access online application (WindTUNE) that quantifies uncertainties on noise prediction of a wind farm, and a parametric and uncertainties calculation tool for the engineering application Code-TYMPAN. This axe also produced an open-access database of a 400 days campaign of meteorological and acoustical measurements around a wind farm. The last work package investigated new noise reduction devices using blades with modified leading and/or trailing edges. The efficiency of the solutions were characterized in a wind tunnel, both acoustically and aerodynamically. The paper presents the main results obtained at the end of the project.

Radiotherapy Dose Accumulation Routine (RADAR)- A novel dose accumulation script with built-in uncertainty

PurposeTo incorporate uncertainty into dose accumulation for reirradiation. MethodsThe RADAR script for the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) is described and the voxel-wise ellipsoid search algorithm is introduced as a means of incorporating uncertainty. RADAR is first demonstrated on a test patient reirradiated to the spine illustrating the effect of the uncertainty algorithm. A summary of initial evaluation testing by 11 users, each of whom ran a separate spine reirradiation case, follows. Finally, RADAR run times are reported for different conditions. ResultsIn the demonstration case in which a 3mm ellipsoid search was used, maximum RADAR 2 Gy equivalent (EQD2) accumulated spinal cord dose increased from 7244 cGy to 12689 cGy because the ellipsoid search pulled dose from closer to the adjacent target structure. When the ellipsoid search was restricted to voxels within the spinal cord, the maximum accumulated cord dose was reduced to 6523 cGy and did not exceed the sum of the maximum EQD2 spinal cord doses of the individual plans (6730 cGy). In the evaluation cases, the RADAR EQD2 maximum dose for the spinal cord increased an average of 31.6% with uncertainty applied compared to a conventional dose accumulation and decreased an average of 16.7% compared to a conventional dose accumulation when the uncertainty calculation was restricted to voxels within the spinal cord. RADAR run times depend on the number of plans being added and the type of uncertainty being used. ConclusionRADAR offers a novel way to directly account for uncertainty in dose accumulation by means of a voxel-wise ellipsoid search algorithm. EQD2 dose accumulation with and without dose discounts is also available.

MIRD Pamphlet No. 30: MIRDfit-A Tool for Fitting of Biodistribution Time-Activity Data for Internal Dosimetry.

In nuclear medicine, estimating the number of radioactive decays that occur in a source organ per unit administered activity of a radiopharmaceutical (i.e., the time-integrated activity coefficient [TIAC]) is an essential task within the internal dosimetry workflow. TIAC estimation is commonly derived by least-squares fitting of various exponential models to organ time-activity data (radiopharmaceutical biodistribution). Rarely, however, are methods used to objectively determine the model that best characterizes the data. Additionally, the uncertainty associated with the resultant TIAC is generally not evaluated. As part of the MIRDsoft initiative, MIRDfit has been developed to offer a biodistribution fitting software solution that provides the following essential features and advantages for internal dose assessment: nuclear medicine-appropriate fit functions; objective metrics for guiding best-fit selection; TIAC uncertainty calculation; quality control and data archiving; integration with MIRDcalc software for dose calculation; and a user-friendly Excel-based interface. For demonstration and comparative validation of MIRDfit's performance, TIACs were derived from serial imaging studies involving 18F-FDG and 177Lu-DOTATATE using MIRDfit. These TIACs were then compared with TIAC estimates obtained using other software. In most cases, the TIACs agreed within approximately 10% between MIRDfit and the other software. MIRDfit has been endorsed by the MIRD Committee of the Society of Nuclear Medicine and Molecular Imaging and has been integrated into the MIRDsoft suite of free dosimetry software; it is available for download at no user cost (https://mirdsoft.org/).

Parameter identification and uncertainty evaluation in quasi-dynamic test of solar thermal collectors with Monte Carlo method

This work presents a comparison between two methods used for parameter identification and calculation of parameter uncertainty applied to the measured data of solar thermal collectors when tested according to ISO 9806:2017. One method is using a weighted least square (WLS) fit and the partial derivative approach described in the GUM (the Guide to the Expression of Uncertainty in Measurement). The second is using the Monte Carlo (MC) method, also described in GUM. Uncertainty evaluation by Monte Carlo method is based on a probabilistic approach and is an alternative way for identification of parameters and determination of the uncertainties. In this work the results were obtained according to Quasi-Dynamic Test (QDT) method for a flat plate collector and an evacuated tubular collector. The least squares (LS) method and a nonlinear regression method (MPFit) are used in the identification of parameters for each iteration of the MC method. For the implemented MC method computation times are also discussed. One disadvantage of the MC method is the computation time which depends on the number of samples in the experimental test quantity files, however with this study we think that the advantages of the MC method outweigh the disadvantages, and it is useful even as a complementary tool in QDT testing of collectors.

UNCERTAINTY EVALUATION USING LAW OF PROPAGATION AND MONTE CARLO SIMULATION METHODS WITH THE AUTORFPOWER MEASUREMENT SOFTWARE

RF power measurement is essential in RF and microwave metrology. For reliable and accurate power measurement, automatic measurement is preferred. A software application in C#, named AutoRFPower, was developed for automatic RF power measurement and uncertainty calculations at this study. According to the GUM document, this application is enhanced for uncertainty calculations by utilizing the Law of Propagation method and the Monte Carlo Simulation method. Trial measurements were performed at different RF power levels and frequencies between 50 MHz and 18 GHz using the AutoRFPower software. Law of Propagation and Monte Carlo Simulation uncertainty calculations were carried out by AutoRFPower based on the trial measurements and by the Oracle Crystal Ball simulation application. All measurements and their uncertainty calculations were compared with each other, and this study validated the uncertainty calculation of AutoRFPower. In addition, it was observed that in the Monte Carlo Simulation, uncertainty calculation results were non-symmetrical normal distribution, contrary to the assumption of symmetrical normal distribution according to the Low of Propagation method. Moreover, it has been observed that the statistical distribution of uncertainty changes depending on the dominant component of the parameters in the model function used for the uncertainty calculation with the Monte Carlo Simulation method.

Uncertainty Calculation as a Service: Integrating Cloud-Based Microservices for Enhanced Calibration and DCC Generation.

The calibration industry is renowned for its diverse and sophisticated equipment and complex processes, which necessitate innovative solutions to keep pace with rapidly advancing technology. This paper introduces an enhancement to an existing microservice-based cloud architecture, aimed at effectively managing the inherent complexity within this field. The enhanced architecture seamlessly integrates various equipment types and communication technologies, aligning diverse stakeholder expectations into a unified system that ensures efficient and accurate calibration processes. It highlights the integration of microservices to facilitate various methods of uncertainty calculation and the generation of digital calibration certificates (DCCs). A case study on RF power measurement illustrates the practical application and benefits of the enhanced architecture. Although initially focused on RF power measurement, the flexible architecture allows for future expansions to accommodate new standards and measurement techniques. The enhanced system offers a comprehensive approach to managing data flow from calibration equipment to the final generation of DCCs, utilizing cloud-based services for efficient data processing. As a future direction, this extension sets the groundwork for broader applicability across multiple measurement types, ensuring readiness for upcoming advancements in metrology.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

PurposeIn order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.Design/methodology/approachFirst, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.FindingsThe cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/valueThis study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Evaluation of a laser speckle interferometry-based diagnostic system for wall surface variation in tokamak device

The realization of high-parameter, long-pulse operation of a tokamak inevitably faces a number of safety and operational constraints, which need to be achieved through comprehensive in-situ monitoring and control of the wall materials. Laser speckle interferometry (LSI) has been proposed to diagnose changes in the surface topography of wall materials. An LSI-based experimental system has been established and a quantitative evaluation process has made for it. The accuracy, range, and uncertainty of measurement are determined by measuring the topography change resulting from laser ablation and pulsed laser deposition. The calculation of measurement uncertainty considers various sources of error such as measurement noise, residual flatness, measurement errors, and measurement repeatability. This evaluation provides an overview of the measurement performance and reliability of the experimental system and helps to clarify the advantages and limitations of LSI for wall surfaces diagnosis. The evaluation can also serve as a useful reference for optimizing the LSI-based measurement system for better adaption to the EAST diagnostic conditions.

Uncertainty Benchmarks for Time-Dependent Transport Problems

Verification solutions for uncertainty quantification (UQ) are presented for time-dependent transport problems where , the scattering ratio, is uncertain. The method of polynomial chaos expansions is employed for quick and accurate calculation of the quantities of interest (QoIs), and uncollided solutions are used to treat part of the uncertainty calculation analytically. We find that approximately six moments in the polynomial expansion are required to represent the solutions to these problems accurately. Additionally, the results show that if the uncertainty interval spans c = 1, which means it is uncertain whether the system is multiplying or not, the confidence interval will grow in time. Finally, since the QoI is a strictly increasing function, the percentile values are known and can be used to verify the accuracy of the expansion. These results can be used to test UQ methods for time-dependent transport problems.

Calculation of Reaction Rate and Uncertainty for d(p,γ)3He and 3He(d,p)4He Using Bayesian Statistical Approach in Astrophysics

Calculation of Reaction Rate and Uncertainty for d(p,γ)3He and 3He(d,p)4He Using Bayesian Statistical Approach in Astrophysics

О расчете неопределенности показателя токсичности продуктов горения полимерных материалов

A testing lab must evaluate and determine the contribution of the uncertainty of measurements for each testing methodology in order to implement the reliability and accuracy of tests. In addition, the uncertainty index must be specified in the test (measurement) protocols. Uncertainty can be calculated by using various methods; however, when the desired value of the output parameter is determined from a graph, the method of least squares should be used. In order to determine the toxicity index of combustion products, a series of tests using white laboratory mice have been conducted. Based on the test results, a graph of the dependence of lab mice lethality on the concentration of toxic combustion products has been built; the dose causing the lethality of 50 % of lab mice has been determined. Using the method of least squares, confidence limits of the estimate of measured value have been calculated and graphically shown. As a result of calculations, the uncertainty of toxicity of combustion products was determined as around 25 %. The wide range of data has been caused by the error of measuring equipment, heterogeneity of the test sample and its composition, as well as the characteristics of lab mice and their biological features. The results of uncertainty calculation provided in the article can be used by laboratories conducting fire safety tests of materials.

Unsupervised Fusion Feature Matching for Data Bias in Uncertainty Active Learning.

Active learning (AL) aims to sample the most valuable data for model improvement from the unlabeled pool. Traditional works, especially uncertainty-based methods, are prone to suffer from a data bias issue, which means that selected data cannot cover the entire unlabeled pool well. Although there have been lots of literature works focusing on this issue recently, they mainly benefit from the huge additional training costs and the artificially designed complex loss. The latter causes these methods to be redesigned when facing new models or tasks, which is very time-consuming and laborious. This article proposes a feature-matching-based uncertainty that resamples selected uncertainty data by feature matching, thus removing similar data to alleviate the data bias issue. To ensure that our proposed method does not introduce a lot of additional costs, we specially design a unsupervised fusion feature matching (UFFM), which does not require any training in our novel AL framework. Besides, we also redesign several classic uncertainty methods to be applied to more complex visual tasks. We conduct rigorous experiments on lots of standard benchmark datasets to validate our work. The experimental results show that our UFFM is better than the similar unsupervised feature matching technologies, and our proposed uncertainty calculation method outperforms random sampling, classic uncertainty approaches, and recent state-of-the-art (SOTA) uncertainty approaches.

AN APPLICATION FOR THE CALIBRATION OF THE TWO-PRESSURE HUMIDITY GENERATOR

Two-pressure humidity generator (2-PHG) has capability to produce environments of known humidity with the “two pressure” method that is proven by NIST. The 2-PHG is supplied with known humidity values, the values can be used for instrument calibration, verification and such as other processes. The set point values can be entered from the device’s front panel by an operator. 2-PHG calculates the relative humidity from the pressure and temperature measurements with the formula. The computer controls the ratios on the formula to generate a known humidity value. 2-PHG has to have traceability for using on calibration processes of other devices; 2-PHG must be calibrated. This study represents an application of the 2-PHG calibration by using the guides and articles in the literature about the device. Calibration of the 2-PHG contains examination of the each parameter of the formula that was given for humidity calculation. Four temperature and two pressure probes that are saturation temperature probe, pre-saturation temperature probe, expansion valve temperature probe, chamber temperature probe, low pressure probe, high pressure probe help 2-PHG to calculate the formula. Calibration of the 2-PHG, also, contains the calibration of the temperature probes and the pressure probes. This study expresses an application of the calibration of a 2-PHG which is located in Turkish Standard Institution Gebze Calibration Laboratories and the uncertainty calculation of this application can be seen on this paper. Each uncertainty parameter of the formula and uncertainty parameters of the probes that are affected to the total uncertainty were calculated. For different temperatures and different relative humidities, the measurement uncertainty of this application was given on this paper. This study can be used as a supplementary document in the calibrations of the 2-PGH and in the new studies.

Agar diffusion microbiological assay measurement using a smartphone device and its measurement uncertainty using the bootstrapping method

Usually, inhibition zone sizes in agar diffusion microbiological assay of antibiotics are measured using regular callipers. In this study, we proposed the use of a smartphone app for measuring inhibition zone sizes. The smartphone app allows for standardized measurements with a reference scale, which provides measured values comparable to those obtained using regular callipers. The main uncertainty source associated with antibiotic potency is inhibition zone size variability. Here, we suggest using the bootstrapping method, a resampling technique, to estimate measurement uncertainty without complex calculations. This simplifies the process and yields comparable results to the usual measurement uncertainty calculations. Both improvements were successfully applied to determine the potency of gentamicin, linezolid, and cefazolin. The results showed that smartphone-based measurements and the bootstrapping approach are valuable tools in agar diffusion microbiological assays.

Semantic analysis of two-syllabic terms of metrology. Part 1: The Types of measurements and methods of measurements

Two-syllabic terms of metrology are considered, which have become so firmly embedded in the mentality and practice of metrologists that the inadequacy of these terms manifests itself only when it is not possible to solve any important problem. Such a problem within the framework of the moment approach to estimating accuracy turned out to be the calculation of definitive uncertainty, and the term-phrase direct measurements causes a number of paradigmatic associations – indirect, cumulative, joint and other pseudomorphic measurements, similar in form of names and different in definition. But the errors of the results of these measurements can no longer be estimated in the same way as the errors of measuring instruments are estimated. The semantics of such two-syllabic terms is analyzed. The role of the direct and figurative meaning of the word measurement in the problem of the inadequacy of models is shown, the solution of which, within the framework of the compositional approach to assessing accuracy, is indicated by the word method before the two-syllabic names listed above. Bringing the term measuring problem into line with the semantics of the word problem has become the simplest correction of this terminological misunderstanding. At the same time, the inconsistency of the subordinate terms measurement method and method of solving the measurement problem has been eliminated.

Uncertainty Analysis of Time-Integrated Activity Coefficient in Single-Time-Point Dosimetry Using Bayesian Fitting Method.

Calculation of the uncertainty of the individual time-integrated activity coefficient (TIACs) is desirable in molecular radiotherapy. However, the calculation of TIAC's uncertainty in single-time-point (STP) method has never been reported in the literature. This study presents a method based on the Bayesian fitting (BF) to calculate the standard deviation (SD) of individual TIACs in the STP dosimetry. Biokinetic data of 177Lu-DOTATATE in kidneys were obtained from PMID33443063. BF methods with extended objective function, which optimize the fitting using prior knowledge of the function's parameters, were used. Reference TIACs (rTIACs) were calculated by fitting a mono-exponential function to the all-time-point data. The goodness of fit was checked based on the visual inspection and the coefficient of variations (CV) of the fitted parameters < 0.5. BF with relative (BFr) and absolute-based (BFa) variance methods were used to obtain the calculated TIACs (cTIACs) from the STP dosimetry. Performance of the STP method was obtained by calculating the relative deviation (RD) between cTIACs and rTIACs. Visual inspection showed a good fit for all patients with CV of fitted parameters less than 50%. The mean ± SD of cTIAC's %RD were 7.0 ± 25.2 for BFr and 2.6 ± 8.9 for BFa. The range of %CV of the individual cTIAC's SD for BFr and BFa methods was 36-78% and 22-33%, respectively, while the %CV of the rTIAC SD was 0.8-49%. We introduce the BF method to calculate the SD of individual TIACs in STP dosimetry. The presented method might be used as an alternative method for uncertainty analysis in STP dosimetry. The online version contains supplementary material available at 10.1007/s13139-024-00851-8.

Real-Time Evaluation of the Uncertainty in Weather Forecasts Through Machine Learning-Based Models

Meteorological events have always been of great interest because they have influenced everyday activities in critical areas, such as water resource management systems. Weather forecasts are solved with numerical weather prediction models. However, it sometimes leads to unsatisfactory performance due to the inappropriate setting of the initial state. Precipitation forecasting is essential for water resource management in semi-arid climate and seasonal rainfall areas such as the Ebro basin. This research aims to improve the estimation of the uncertainty associated with real-time precipitation predictions presenting a machine learning-based method to evaluate the uncertainty of a weather forecast obtained by the Weather Research and Forecasting model. We use a model trained with ground-truth data from the Confederación Hidrográfica del Ebro, and WRF forecast results to compute uncertainty. Experimental results show that Decision Tree-based ensemble methods get the lowest generalization error. Prediction models studied have above 90% accuracy, and root mean square error has similar results compared to those obtained with the ground truth data. Random Forest presents a difference of -0.001 concerning the 0.535 obtained with the ground truth data. Generally, using the ML-based model offers good results with robust performance over more traditional forms for uncertainty calculation and an effective alternative for real-time computation.