Uncertainty Evaluation Research Articles

New guidelines on radiation survey and sanitary assessment of residential, public and industrial buildings and facilities in terms of radiation safety indicators. Part 1

The paper (in two parts) presents an overview of the new guidelines MR 2.6.1.0333-23 (approved on 01 December 2023) that supersede guidelines MU 2.6.1.2838-11, which were used for organizing radiation surveys of residential, public and industrial buildings and facilities and their sanitary assessment in terms of radiation safety indicators over the past 12 years. Due to a large number of critical comments on the document received during this period, a need for significant revision emerged. The scope of the revised document was expanded and now covers all stages of the life cycle of buildings and facilities: commissioning; operation period; overhaul and reconstruction; demolition. In the first part of the paper, the structure and legal status of the new guidelines are considered, as well as the main innovations in terms of measuring the ambient dose equivalent rate of gamma radiation, searching and identifying local radiation anomalies and sites of radioactive contamination, measuring surface contamination levels, and determining the minimum number of premises to be surveyed. The reasons for the introduction of certain changes are outlined. The issues of evaluation of measurement uncertainty, reporting of measurement results and registration of test reports are covered in detail. In the second part of the paper, numerous innovations will be considered in terms of estimating the indoor average annual equilibrium equivalent concentration of radon isotopes.

Offshore oil spills in Brazil: An extensive review and further development

The present study offers an extensive overview on the evolution and current state of marine oil spill research in Brazil and then discusses further directions. Given the historical and current relevance of this issue, this paper also aims to summarize the exploration, geological background, design of oil spills timeline and assessment of the most important of them. Moreover, it includes a critical comparison of Brazilian oil spill models in terms of their simulation abilities, real-time field data assimilation, space and time forecasts and uncertainty evaluation. This study also presents the perspectives of the Multi-User System for Detection, Prediction, and Monitoring of Oil Spills at Sea (SisMOM) the largest and most important Brazilian project to face the offshore oil spills.

Monte Carlo method for evaluation of surface emission rate measurement uncertainty

Monte Carlo method for evaluation of surface emission rate measurement uncertainty

The Uncertainty Evaluation of Determining the Trace H2S in SF6/N2 Insulating Gas Mixture by Cavity Ring-Down Spectroscopy

Abstract H2S is one of the most important characteristic components of sulfur hexafluoride gas insulated electrical equipment. The detection of trace H2S is of great significance for early fault diagnosis of such equipment. Based on the 1578 nm wavelength distributed feedback diode laser (DFB-DL), cavity ring-down spectroscopy (CRDS) can effectively measure the concentration of trace H2S in SF6/N2 gas mixtures. Starting from the principle of methodology, this article establishes a mathematical model for evaluating the measurement uncertainty of CRDS and analyzes its sources of uncertainty: gas constant R1 , temperature T, Avogadro constant NA , gas pressure p in the optical cavity, volume V of the optical cavity, speed c of light, the absorption cross-section parameter σ(ν) of H2S molecules in the laser frequency ν, the ring-down time τ with absorption sample H2S and the ring-down time τ0 without absorption sample. After evaluating the uncertainty components, it was found that the main component was σ(ν) and the secondary components were τ and τ0. The H2S content in the 80% SF6-20% N2 mixed gas measured is (7.64 ± 0.12) × 10−6 mol/mol.

ANALYSIS OF METHODS FOR EVALUATION ESSENTIAL PERFORMANCE OF MECHANICAL TOURNIQUETS

The article is devoted to the analysis of methods for evaluating essential performance of mechanical tourniquets to improve their safety in use. According to the legislation of Ukraine and the European Union, a tourniquet is a medical device that, regardless of design, provides relief to a patient in the event of an injury by stopping bleeding in the limb by applying mechanical pressure. Tourniquets are classified as pneumatic and mechanical depending on the method of creating external pressure. The article considers a typical design of mechanical tourniquets and identifies the main structural elements: a pressure generating mechanism, a pressure element, a fixing device, and a place for recording the time of application. The analysis of scientific articles shows a significant number of studies focusing on the characteristics of pneumatic tourniquets, while methods for testing the effectiveness and safety of mechanical tourniquets have been insufficiently investigated. It is noted that the safety of medical devices is defined as the absence of an unacceptable level of risk for the operator and the patient, where risk means the effect of uncertainty in achieving the goals in the process of development, production, design, and use of a medical device. A list of essential performance of mechanical tourniquets is provided: overlapping pressure, pressure loss after application during the time of use, pressure gradient. It has been established that to date, four methods are known for obtaining measurement information on essential performance of mechanical tourniquets: a method based on converting the pressure value generated by the tourniquet during application into an electrical signal using strain sensors; a method based on measuring air pressure in a test cuff; an indirect method for determining pressure using Lamé's equation; a method for directly measuring pressure in the limb under the tourniquet using an invasive pressure sensor. Based on the identified essential performance of mechanical tourniquets, the requirements for methods of their determination are presented: measurement of overlapping pressure, determination of pressure loss after the tourniquet is applied during the time of use, determination of pressure gradient, reproducibility, repeatability, evaluation of metrological uncertainty, and evaluation of the essential performance of mechanical tourniquets based on mathematical models. Ways to improve the existing methods for evaluating essential performance are considered.

Uncertainty Evaluation of the TGA Oxidation Data

Thermogravimetric analysis (TGA) involves the measurement of the changes in mass that occur when a constant heat is applied to an unknown specimen as a function of time or temperature. It is used to evaluate thermal stability, oxidative stability, composition, and estimated lifetime, among other parameters. Given that accurate TGA data is important information for lifetime and stability evaluation of parts and products, an uncertainty evaluation procedure is required to ensure the reliability of the data. In this study, the uncertainty evaluation procedure was established according to the Guide to the Expression of Uncertainty in Measurement (GUM). The mathematically expression of the relationship between the measurand and the input quantities, evaluation of the standard uncertainty of each input estimate, determination of the combined standard uncertainty, and calculation of the expanded uncertainty were performed. The biggest factor affecting the uncertainty of TGA data is the uncertainty of correction factor caused by system calibration

Experiments on High-Resolution Digitizer Accuracy in Measuring Voltage Ratio and Phase Difference of Distorted Harmonic Waveforms above 2 kHz

High-resolution multi-channel digitizers are used extensively for precision low voltage measurements in numerous applications and allow the simultaneous measurement of voltage magnitude ratio and phase difference between two different waveforms in power system applications. Delta–sigma-based analog-to-digital conversion enables the use of sampling frequencies in the range of megahertz, which provides accurate measurement bandwidths for transformed high-frequency, high-voltage signals. With the increased use of power electronic converters contributing to high-frequency harmonic emissions in power systems, there is a growing interest in developing calibration systems to measure voltage ratio and phase difference of distorted fundamental frequency waveforms consisting of superimposed, high-frequency harmonics. However, information regarding the accuracy of the high-resolution digitizers in the measurement of distorted voltage waveforms is limited as characterization is typically performed under sinusoidal voltage waveform conditions. This paper presents the details of the accuracy characterization of a 24-bit resolution digitizer under both sinusoidal and distorted waveform conditions for measuring complex voltage ratio and phase error for frequencies up to 10 kHz. The detailed experimental results and the measurement uncertainty evaluations show that increased voltage ratio and phase difference errors should be allocated when these high-resolution digitizers are used to measure distorted voltage waveforms. The estimated expanded uncertainties of complex voltage ratio measurement and phase error measurement for harmonic frequencies up to 10 kHz are ±260 ppm and ±100 µrad, respectively.

Application of the adaptive Monte Carlo method for uncertainty evaluation in the determination of total testosterone in human serum by triple isotope dilution mass spectrometry

The measurement uncertainty is a crucial quantitative parameter for assessing the reliability of the result. The study aimed to propose a new budget for uncertainty evaluation of a reference measurement procedure for the determination of total testosterone in human serum. The adaptive Monte Carlo method (aMCM) was used for the propagation of probability distributions assigned to various input quantities to determine the uncertainty of the testosterone concentration. The basic principles of the propagation and the statistical analysis were described based on the experimental results of the quality control serum sample. The analysis of the number of Monte Carlo trials was discussed. The procedure of validation of the GUM uncertainty framework using the aMCM was also provided. The number of Monte Carlo trials was 2.974 × 106 when the results had stabilized. The total testosterone concentration was 16.02 nmol/L, and the standard uncertainty was 0.30 nmol/L. The coverage interval at coverage probability of 95% was 15.45 to 16.62 nmol/L, while the probability distribution for testosterone concentration was approximately described by a Gaussian distribution. The validation of results was not passed as the expanded uncertainty result obtained by the aMCM was slightly lower, about 7%, than that by the GUM uncertainty framework with consistent results of the concentration.Graphical

Simplified and Detailed Evaluations of the Uncertainty of the Measurement of Microbiological Contamination of Pharmaceutical Products.

The control of the microbial contamination of pharmaceutical products (PP) is crucial to ensure their safety and efficacy. The validity of the monitoring of such contamination depends on the uncertainty of this quantification. Highly uncertain quantifications due to the variability of determinations or the magnitude of systematic effects affecting microbial growth or other analytical operations make analysis unfit for the intended use. The quantification of the measurement uncertainty expressing the combined effects of all random and systematic effects affecting the analysis allows for a sound decision about quantification adequacy for their intended use. The complexity of the quantification of microbial analysis uncertainty led to the development of simplified ways of performing this evaluation. This work assesses the adequacy of the simplified quantification of the uncertainty of the determination of the microbial contamination of PP by log transforming microbial count and dilution factor of the test sample whose uncertainty is combined in a log scale using the uncertainty propagation law. This assessment is performed by a parallel novel bottom-up and accurate evaluation of microbial analysis uncertainty involving the Monte Carlo method simulation of the Poisson log-normal distribution of counts and of the normally distributed measured volumes involved in the analysis. Systematic effects are assessed and corrected on results to compensate for their impact on the determinations. Poisson regression is used to predict precision affecting determinations on unknown test samples. Simplified and detailed models of the uncertainty of the measurement of the microbial contamination of PP are provided, allowing objective comparisons of several determinations and those with a maximum contamination level. This work concludes that triplicate determinations are required to produce results with adequately low uncertainty and that simplified uncertainty quantification underevaluates or overevaluates the uncertainty from determinations based on low or high colony numbers, respectively. Therefore, detailed uncertainty evaluations are advised for determinations between 50 and 200% of PP's maximum admissible contamination value. User-friendly tools for detailed and simplified evaluations of the uncertainty of the measurement of microbial contamination of PP are provided together with the understanding of when simplifications are adequate.

Approaches for the production of reference materials with qualitative properties—The new International Standard ISO 33406

The number of reference materials (RMs), including certified reference materials (CRMs) characterized for qualitative properties, has steadily increased in recent years. In response, the Technical Committee for Reference Materials of the International Organization for Standardization, ISO/TC 334, developed ISO 33406 to provide guidance to reference material producers (RMPs) on producing qualitative RMs. ISO 33406 builds on the general requirements in ISO 17034:2016 for RMP competence and offers specific guidance on value assignment, assessment of homogeneity and stability, statement of metrological traceability, and measurement uncertainty evaluation for RMs with qualitative property values.

Reliable segmentation of multiple lesions from medical images.

Focusing on the complicated pathological features, such as blurred boundaries, severe scale differences between symptoms, and background noise interference, we aim to enhance the reliability of multiple lesions joint segmentation from medicalimages. Propose a novel reliable multi-scale wavelet-enhanced transformer network, which can provide accurate segmentation results with reliabilityassessment. Focusing on enhancing the model's capability to capture intricate pathological features in medical images, this work introduces a novel segmentation backbone. The backbone integrates a wavelet-enhanced feature extractor network and incorporates a multi-scale transformer module developed within the scope of this work. Simultaneously, to enhance the reliability of segmentation outcomes, a novel uncertainty segmentation head is proposed. This segmentation head is rooted in the SL, contributing to the generation of final segmentation results along with an associated overall uncertainty evaluation scoremap. Comprehensive experiments are conducted on the public database of AI-Challenge 2018 for retinal edema lesions segmentation and the segmentation of Thoracic Organs at Risk in CT images. The experimental results highlight the superior segmentation accuracy and heightened reliability achieved by the proposed method in comparison to other state-of-the-art segmentationapproaches. Unlike previous segmentation methods, the proposed approach can produce reliable segmentation results with an estimated uncertainty and higher accuracy, enhancing the overall reliability of the model. The code will be release on https://github.com/LooKing9218/ReMultiSeg.

Evaluation of uncertainty in personal dose measured using CaSO4:Dy-based TLD badge at different workplaces.

The metrological quality of a measurement is characterised by evaluating the uncertainty in the measurement. In this paper, uncertainty in personal dose measured using individual monitoring CaSO4:Dy-based thermoluminescence dosimeter badge is evaluated by application of the guide to the expression of uncertainty in measurement method. The present dose reporting quantity, whole body dose (WBD) and the proposed quantity, personal dose equivalent, Hp(10) has been used as measurands. The influence of various input quantities on the measurement were analyzed through tests that conform to the requirements of the International Electrotechnical Commission IEC 62387. The study found that the expanded uncertainties for WBD and Hp(10) measurements were 63.4% and 41.4%, respectively, corresponding to a 95% coverage probability for workplace fields covering a wide photon energy range (33-1250keV). However, the uncertainty estimates were quite lower for the type of workplaces that are identified using the dose evaluation algorithm. The input quantities, namely, the response to a mixture of photon beam qualities and photon energy and angular dependence contribute the most to the total uncertainty.

Fully ab-initio all-electron calculation of dark matter-electron scattering in crystals with evaluation of systematic uncertainties

We calculate target-material responses for dark matter–electron scattering at the all-electron level using atom-centered Gaussian basis sets. The all-electron effects enhance the material response at high momentum transfers from dark matter to electrons, q≳O(10αme), compared to calculations using conventional plane wave methods, including those used in ; this enhances the expected event rates at energy transfers E≳10 eV, especially when scattering through heavy mediators. We carefully test a range of systematic uncertainties in the theory calculation, including those arising from the choice of basis set, exchange-correlation functional, number of unit cells in the Bloch sum, k-mesh, and neglect of scatters with very high momentum transfers. We provide state-of-the-art crystal form factors, focusing on silicon and germanium. Our code and results are made publicly available as a new tool, called (“”). Published by the American Physical Society 2024

Analysis of Long-Distance Geometric Error Measurement and Uncertainty Based on PSD Laser Collimation Principle

Due to the limitations of traditional geometric error measurement, the measurement accuracy of long-stroke geometric errors is generally not high and the operation is complicated. In response to the above situation, in this study, a geometric error measurement system is built with a laser beam as the reference line and 2D position sensitive detector as the photoelectric conversion device. The single measurement range is 40 m, and the measurement range is further expanded through the principle of segmented splicing. Using an ultra-long guide rail as the measurement object for straightness measurement, the experimental results are similar to those of a laser interferometer. The uncertainty analysis model was obtained through the analysis of quantity characteristics, and based on this, the variance synthesis theorem and probability distribution propagation principle were studied to form two uncertainty synthesis methods. The measurement evaluation results showed that the two methods were basically consistent. The work provided a reference method for the uncertainty evaluation of position-sensitive detector measurement systems in the future.

Bayesian linearized amplitude variation with offset and azimuth inversion and uncertainty analysis in horizontal transversely isotropic media

AbstractThe stratum can be modelled as a horizontal transversely isotropic medium when a single set of vertically parallel fractures embedded in an isotropic background medium, which facilitates efficient study for fractured reservoirs. Elastic parameters and fracture weaknesses are important parameters to describe the characteristics of fractured reservoirs, and seismic inversion plays a significant role in parameters estimation. The commonly used deterministic inversion methods do not fully utilize the prior information and fails to present the uncertainty analysis of inversion results. To address these shortcomings, we propose a Bayesian linearized amplitude variation with offset and azimuth inversion method tailored for horizontal transversely isotropic media, enabling a more robust analysis of uncertainty. Within the framework of Bayesian inversion, the proposed method successfully derives analytical expressions for the posterior mean and covariance of both elastic parameters and fracture weaknesses. The response characteristics of the anisotropic reflection coefficient are analysed, and it is found that the perturbations of elastic parameters have a greater effect on reflection coefficient compared to fracture weaknesses. Synthetic data examples confirm that the accuracy of estimated P‐ and S‐wave velocities and density surpasses that of fracture weaknesses, and the proposed method still performs well for the case of moderate noise. A field data example demonstrates that the inverted profiles agree well with the logging curve, and the estimated fracture weaknesses display significantly high values in the reservoir area. The estimated reservoir parameters not only contribute to a more accurate representation of the fractured gas‐bearing reservoir but also provide insights into the target gas reservoir through its posterior distribution. Both synthetic and field data examples demonstrate the stability and reliability of the proposed method in characterizing fractured reservoirs. We determine that the proposed method provides an available tool for nuanced evaluation of uncertainty for the inversion results, and it is helpful for the fine description of fractured hydrocarbon‐bearing reservoirs.

Measurement uncertainty evaluation in soil liquid limit testing

Measurement uncertainty evaluation in soil liquid limit testing

Artificial neural network assisted spectral scatterometry for grating quality control

Spectral scatterometry is a technique that allows rapid measurements of diffraction efficiencies of diffractive optical elements (DOEs). The analysis of such diffraction efficiencies has traditionally been laborious and time consuming. However, machine learning can be employed to aid in the analysis of measured diffraction efficiencies. In this paper we describe a novel system for providing measurements of multiple measurands rapidly and concurrently using a spectral scatterometer and an artificial neural network (ANN) which is trained utilising transfer learning. The ANN provides values for the pitch, height, and line widths of the DOEs. In addition, an uncertainty evaluation was performed. In the majority of the studied cases, the discrepancies between the values obtained using a scanning electron microscope (SEM) and artificial neural network assisted spectral scatterometer (ANNASS) for the grating parameters were below 5 nm. Furthermore, independent reference samples were used to perform a metrological validation. An expanded uncertainty (k = 2) of 5.3 nm was obtained from the uncertainty evaluation for the measurand height. The height value measurements performed employing ANNASS and SEM are demonstrated to be in agreement within this uncertainty.

Uncertainty estimation and evaluation of deformation image registration based convolutional neural networks

Objective. Fast and accurate deformable image registration (DIR), including DIR uncertainty estimation, is essential for safe and reliable clinical deployment. While recent deep learning models have shown promise in predicting DIR with its uncertainty, challenges persist in proper uncertainty evaluation and hyperparameter optimization for these methods. This work aims to develop and evaluate a model that can perform fast DIR and predict its uncertainty in seconds. Approach. This study introduces a novel probabilistic multi-resolution image registration model utilizing convolutional neural networks to estimate a multivariate normal distributed dense displacement field (DDF) in a multimodal image registration problem. To assess the quality of the DDF distribution predicted by the model, we propose a new metric based on the Kullback–Leibler divergence. The performance of our approach was evaluated against three other DIR algorithms (VoxelMorph, Monte Carlo dropout, and Monte Carlo B-spline) capable of predicting uncertainty. The evaluation of the models included not only the quality of the deformation but also the reliability of the estimated uncertainty. Our application investigated the registration of a treatment planning computed tomography (CT) to follow-up cone beam CT for daily adaptive radiotherapy. Main results. The hyperparameter tuning of the models showed a trade-off between the estimated uncertainty’s reliability and the deformation’s accuracy. In the optimal trade-off, our model excelled in contour propagation and uncertainty estimation (p <0.05) compared to existing uncertainty estimation models. We obtained an average dice similarity coefficient of 0.89 and a KL-divergence of 0.15. Significance. By addressing challenges in DIR uncertainty estimation and evaluation, our work showed that both the DIR and its uncertainty can be reliably predicted, paving the way for safe deployment in a clinical environment.

Empirical uncertainty evaluation for the pose of a kinematic LiDAR-based multi-sensor system

Abstract Kinematic multi-sensor systems (MSS) describe their movements through six-degree-of-freedom trajectories, which are often evaluated primarily for accuracy. However, understanding their self-reported uncertainty is crucial, especially when operating in diverse environments like urban, industrial, or natural settings. This is important, so the following algorithms can provide correct and safe decisions, i.e. for autonomous driving. In the context of localization, light detection and ranging sensors (LiDARs) are widely applied for tasks such as generating, updating, and integrating information from maps supporting other sensors to estimate trajectories. However, popular low-cost LiDARs deviate from other geodetic sensors in their uncertainty modeling. This paper therefore demonstrates the uncertainty evaluation of a LiDAR-based MSS localizing itself using an inertial measurement unit (IMU) and matching LiDAR observations to a known map. The necessary steps for accomplishing the sensor data fusion in a novel Error State Kalman filter (ESKF) will be presented considering the influences of the sensor uncertainties and their combination. The results provide new insights into the impact of random and systematic deviations resulting from parameters and their uncertainties established in prior calibrations. The evaluation is done using the Mahalanobis distance to consider the deviations of the trajectory from the ground truth weighted by the self-reported uncertainty, and to evaluate the consistency in hypothesis testing. The evaluation is performed using a real data set obtained from an MSS consisting of a tactical grade IMU and a Velodyne Puck in combination with reference data by a Laser Tracker in a laboratory environment. The data set consists of measurements for calibrations and multiple kinematic experiments. In the first step, the data set is simulated based on the Laser Tracker measurements to provide a baseline for the results under assumed perfect corrections. In comparison, the results using a more realistic simulated data set and the real IMU and LiDAR measurements provide deviations about a factor of five higher leading to an inconsistent estimation. The results offer insights into the open challenges related to the assumptions for integrating low-cost LiDARs in MSSs.

Comparison of voltage transformer measuring systems at 110 kV and 10 kV

Comparison of voltage transformer measuring systems at 110 kV and 10 kV