Assessment of Performance and Uncertainty in Qualitative Analytical Chemistry: A Metrological Approach based on the Eurachem/CITAC guide

Status of integrated performance assessment of the waste packages and engineered barrier system : O'Connell W.J. Proct 1st Annual Topical Meeting on High Level Radioactive Waste Management, Las Vegas, 8–12 April 1990V1, P380–387. Publ. ANS/ASCE: La Grange Park, 1990

Background: The performance assessment of tests that express qualitative results in the medical laboratory is of primary importance in characterization, diagnosis, follow-up, and screening. An important contribution to this type of assessment may be the publication of the Eurachem AQA 2021 guide. The text intends to principally discuss the consistency of the subclauses of this guide with ISO 15189 and CLSI EP12-A2. Methods: The study involves a literature review within the scope of qualitative tests. Results: Tables are used for crossing AQA. with ISO 15189 and CLSI EP12-A2. Conclusions: Consistency with ISO 15189 and CLSI EP12-A2 is demonstrated in the study. Introducing “uncertainty of proportion” reflects the necessity of assessing uncertainties when dealing with qualitative results.

Assessment of Performance and Uncertainty in Qualitative Chemical Analysis

This volume is the fourth in a sequence of reports that document the December 1991 preliminary comparison with 40 CFR 191, Subpart B (the Standard; US EPA, 1985) for the Waste Isolation Pilot Plant (WIPP). The three previous volumes describe the background of the project, the performance-assessment methodology, and the 1991 results (Volume 1); the probability and consequence models used in the calculations (Volume 2); and the reference data base (Volume 3). This volume contains the results of uncertainty and sensitivity analyses conducted using the methodology, modeling system, and data described in the earlier volumes. These analysis provide quantitative and qualitative insights on the relationships between uncertainty in the models and data used in the WIPP performance assessment and the resultant uncertainty in the results of the performance assessment. Uncertainty and sensitivity analysis is an important part of the WIPP performance assessment and contributes to the overall analysis in the following areas: (1) assessment of uncertainty in performance-assessment results that must be used in comparison regulatory standards, (2) identification of modeling areas where reductions in uncertainty can significantly improve the confidence that can be a placed in performance-assessment results, and (3) verification that the models used within the performance-assessment process are operating properly.

Minimization of output uncertainty is an important control target for stochastic systems subject to bounded random inputs. Firstly, causes that prevent realization of the minimum Shannon entropy (SE) control are examined based on the analysis of the SE definition in the continuous random variable (CRV) and on this basis, a new measure of uncertainty, which is called rational entropy (RE), is proposed, and the key properties of the RE are proved. Next, results are extended to the output stochastic distribution control (SDC) systems whose output probability density functions (PDFs) are approximated by a linear B-spline basis functions model. Then, two types of minimum RE controller with the mean constraint are given and several controller performance assessment (CPA) benchmarks for output SDC systems are presented. Finally, simulations are included to discuss the feasibility and effectiveness of the proposed measure of uncertainty and performance assessment methods.

Abstract. A novel metric for rainfall-runoff model calibration and performance assessment is proposed. By integrating entropy and mutual information concepts as well as uncertainty quantification through the Brisk Local Uncertainty Estimator for Hydrological Simulations and Predictions (BLUECAT) (likelihood-free approach), the ratio of uncertainty to mutual information (RUMI) offers a robust framework for quantifying the shared information between observed and simulated streamflows. RUMI's capability to calibrate rainfall-runoff models is demonstrated using the GR4J rainfall-runoff model over 99 catchments from various macroclimatic zones, ensuring a comprehensive evaluation. Four additional performance metrics and 50 hydrological signatures are also used for performance assessment. Key findings indicate that RUMI-based simulations provide more consistent and reliable results compared to the traditional Kling–Gupta efficiency (KGE), with improved performance across multiple metrics and reduced variability. Additionally, RUMI includes uncertainty quantification as a core computation step, offering a more holistic view of model performance. This study highlights the potential of RUMI to enhance hydrological modelling through better performance metrics and uncertainty assessment, contributing to more accurate and reliable hydrological predictions.

Performance and uncertainty assessment of green roofs for urban flood reduction in a high-density catchment in Ahmedabad, India

Performance assessment and further optimization of the activation based criticality dosimetry system at the Belgian nuclear research centre SCK CEN

Besides their role as an external quality control tool, PT results or samples could be used as an alternative to fulfil some of the quality assurance requirements such as analytical precision, uncertainty assessment, and internal quality control. This additional use of proficiency testing could help laboratories to reduce the financial impact of their quality assurance process. The purpose of this paper is to highlight some practical uses of PT results or samples in the environmental analytical field, which have been implemented at ISSeP (Institut Scientifique de Service Public), either for method validation or for internal quality control.

Multi-criteria decision making under uncertainty in building performance assessment

Buildings environmental impacts' sensitivity related to LCA modelling choices of construction materials

This article explores the impact of risk attitude on the assessment of project uncertainty encompassing both risk and opportunity and expected project performance. A survey was conducted involving project risk management experts from the construction industry, and the data collected were analyzed using various statistical techniques. The findings reveal that the impact of risk attitude significantly varies across multiple dimensions of project uncertainty and project performance. To the best of the authors’ knowledge, the association between risk attitude and project uncertainty and expected performance assessments has never been explored while capturing multiple dimensions of project uncertainty and performance.

Modern ground water characterization and remediation projects routinely require calibration and inverse analysis of large three-dimensional numerical models of complex hydrogeological systems. Hydrogeologic complexity can be prompted by various aquifer characteristics including complicated spatial hydrostratigraphy and aquifer recharge from infiltration through an unsaturated zone. To keep the numerical models computationally efficient, compromises are frequently made in the model development, particularly, about resolution of the computational grid and numerical representation of the governing flow equation. The compromise is required so that the model can be used in calibration, parameter estimation, performance assessment, and analysis of sensitivity and uncertainty in model predictions. However, grid properties and resolution as well as applied computational schemes can have large effects on forward-model predictions and on inverse parameter estimates. We investigate these effects for a series of one- and two-dimensional synthetic cases representing saturated and variably saturated flow problems. We show that "conformable" grids, despite neglecting terms in the numerical formulation, can lead to accurate solutions of problems with complex hydrostratigraphy. Our analysis also demonstrates that, despite slower computer run times and higher memory requirements for a given problem size, the control volume finite-element method showed an advantage over finite-difference techniques in accuracy of parameter estimation for a given grid resolution for most of the test problems.

It has been recognized that there are significant advantages on combining low salinity waterflooding (LSW) with other enhanced oil recovery (EOR) techniques such as polymer or low tension surfactant flooding. This paper proposes a novel concept of low salinity water-alternating-CO2 (CO2 LSWAG) injection under CO2 miscible displacement conditions. While LSW is an emerging EOR method based on alteration of wettability from oil-wet to water-wet conditions, WAG is a proven method for improving gas flooding performance by controlling the gas mobility. Therefore, LSWAG injection promotes the synergy of the mechanisms underlying these methods (i.e., ion-exchange, wettability alteration, and CO2 miscible displacement and mobility control) that further enhances oil recovery and overcomes the late production problem frequently encountered in the conventional WAG. These features are demonstrated in this work based on a field case study. To investigate the advantages of CO2 LSWAG, a comprehensive ion exchange model associated with geochemical processes has been developed and coupled to the multi-phase multi-component flow equations in an equation-of-state compositional simulator. Laboratory core flood simulations of different CO2 LSWAG schemes are conducted to understand the combined effects of solubility of CO2 in brine, dissolution of carbonate minerals, ion exchange, and wettability alteration. CO2 LSWAG performance is then evaluated on a field scale through an innovative workflow that includes geological modeling, multi-phase multi component reservoir flow modeling and process optimization. The simulation results indicate that CO2 LSWAG has the highest oil recovery compared to conventional high salinity waterflood, high salinity WAG, and low salinity waterflood. A number of geological realizations are generated to assess the geological uncertainty effect, in particular clay distribution uncertainties, on CO2 LSWAG efficiency. Finally, CO2 LSWAG injection strategies are optimized by identifying key WAG parameters. The proposed workflow demonstrates the synergy between CO2 WAG and LSW. Built in a robust reservoir simulator, it serves as a powerful tool for screening, design, optimization, and uncertainty assessment of the process performance from laboratory to and field scales. CO2 LSWAG is a promising EOR technique as it not only combines the benefits of CO2 injection and low salinity water floods but also promotes the synergy between these processes through the interactions between geochemical reactions associated with CO2 injection, ion exchange process, and wettability alteration. This paper demonstrates the merits of this process through modeling, optimization and uncertainty assessment.

NASA created the Observational Products for End-Users from Remote Sensing Analysis (OPERA) project to develop satellite-based analysis ready data products for resource management, environmental protection, and science. The OPERA product that is focused on inland surface water detection, Dynamic Surface Water Extent (DSWx), will be produced using data from both optical and synthetic aperture RADAR systems. The first DSWx product release (DSWx-HLS) relies on Harmonized Landsat Sentinel-2 (HLS) data to yield a median observation frequency of 3 days at the equator with near-global coverage. Subsequent DSWx releases will be based on inputs from Sentinel-1, Surface Water Ocean Topography (SWOT), and NASA-ISRO Synthetic Aperture Radar (NISAR).DSWx accuracy in monitoring open water bodies is estimated through comparison with coincident, higher spatial resolution satellite imagery for locations around the globe. DSWx product suite algorithms also target the detection of mixtures of water and vegetation at input data subpixel scale as well as water under vegetation. The accurate assessment of algorithm performance given these especially challenging targets requires the development and analysis of databases that have as a foundation, data collected in the field.A DSWx predecessor (USGS DSWE) and provisional DSWx data have been combined with in situ data on river discharge, aquatic species occurrence, water quality, and wetland processes to test and develop product utility. At sites spread across the US, low-cost sensors have been employed to record surface inundation. Trail cameras adapted for scientific research are providing useful information on weather, vegetation, and water conditions. Imagery from multiple high-resolution remote sensing instruments, including uncrewed aerial systems and commercial satellites, as well as sensors on-board the International Space Station, are being periodically collected. During intensive field campaigns, vegetation structure is being measured at each site. The imagery and in situ data are combined to improve DSWx development, uncertainty assessment, and application.