SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This presentation provides an overview on integrating data quality assessments and radiometer uncertainty for determining the expanded uncertainty of three-component solar radiation measurements.
Accurate solar irradiance data are fundamental for determining the design and performance characteristics of photovoltaic systems. The uncertainty of solar irradiance measurements depends on many factors including radiometer design, calibration, installation, maintenance, and operational environment. The key contributors to this uncertainty can be classified as the measurement uncertainty of a particular radiometer and the operational uncertainty determined for the time of measurement. Radiometer measurement uncertainty estimates (U R ) can be based on well-established methods used as part of the radiometer calibration process. Estimates of operational uncertainties (U o ) require consideration of additional site-specific factors that affect data quality. A method is needed for establishing the accuracy of solar irradiance data by integrating an existing data quality process and measurement uncertainty estimates for specific radiometers. An algorithm has been developed to integrate data quality analyses and measurement uncertainty estimates for three-component solar irradiance data: global horizontal (total hemispheric) irradiance, direct normal (beam) irradiance, and diffuse horizontal (sky) irradiance collected at one- to 60-minute intervals. The algorithm has been tested using one-minute irradiance measurements. The goal of the project is to distribute a user-friendly software package based on the new algorithm.
Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms and the drivers of the projection uncertainties can help to improve decisions. Previous studies have provided important insights, but often sample only a small subset of potentially important uncertainties. Here we expand on a previous statistical modeling approach by refining the analyses of two uncertainty sources. Specifically, we assess the effects of uncertainties surrounding crop-yield model parameters and climate forcings on projected crop yield. We focus on maize yield projections in the eastern U.S.in this century. We quantify how considering more uncertainties expands the lower tail of yield projections. We characterized the relative importance of each uncertainty source and show that the uncertainty surrounding yield model parameters is the main driver of yield projection uncertainty.
In this paper, the development of a fission-gas collecting and physical-analysis-enabling instrument was proposed for small-volume determination. Analysis specifications require a design capable of accurately and repeatably determining volumes in the range of 0.07–2.5 mL. This system relies on a series of gas expansions originating from a cylinder with known internal volume. The combined gas law is used to derive the unknown volumes from these expansions. Initial system designs included one of two known volumes, 11.85 ± 0.34 mL and 5.807 ± 0.078 mL, with a manifold volume of 32 mL. Results obtained from modeling this system’s operation showed that 0.07 mL can be determined with a relative expanded uncertainty greater than 300% (k = 2) for a single replicate, which was unacceptable for the proposed experimental design. Initial modeling showed that the volume connecting the known volume and rodlet, i.e., the manifold volume, and the sensitivity of the pressure sensor were key contributors to the expanded uncertainty of the measured rodlet volume. The system’s design limited the available options for pressure sensors, so emphasis was placed on the design of the manifold volume. The final system design reduced the manifold volume to 17 mL. These changes in design, combined with replicate analysis, were able to reduce the relative expanded uncertainty by ±12% (k = 2) for the 0.07 mL volume.
The present Table of Standard Atomic Weights (TSAW) of the elements is perhaps one of the most familiar datasets in science. Unlike most parameters in physical science whose values and uncertainties are evaluated using the “Guidelines for Uncertainty in Measurement” (GUM), the majority of standard atomic-weight values and their uncertainties are consensus values, not GUM-evaluated values. The Commission on Isotopic Abundances and Atomic Weights of the International Union of Pure and Applied Chemistry (IUPAC) regularly evaluates the literature for new isotopic-abundance measurements that can lead to revised standard atomic-weight values, A r (E) for element E. The Commission strives to provide utmost clarity in products it disseminates, namely the TSAW and the Table of Isotopic Compositions of the Elements (TICE). In 2016, it was recognized by the Commission that a guideline recommending expression of uncertainty listed in parentheses following the standard atomic-weight value, e.g. A r (Se) = 78.971(8), is not in accord with the GUM, which suggests that this parenthetic notation be reserved to express standard uncertainty, not the expanded uncertainty used in the TSAW and TICE. In 2017, to eliminate this noncompliance with the GUM, a new format was adopted in which the uncertainty value is specified by the plus-minus symbol, e.g. A r (Se) = 78.971 ± 0.008. To clarify the definition of uncertainty, a new footnote has been added to the TSAW. This footnote emphasizes that an atomic-weight uncertainty is a consensus (decisional) uncertainty. Not only has the Commission shielded users of the TSAW and TICE from unreliable measurements that appear in the literature as a result of unduly small uncertainties, but the aim of IUPAC has been fulfilled by which any scientist, taking any natural sample from commerce or research, can expect their sample atomic weight to lie within A r (E) ± its uncertainty almost all of the time.
Here we present the application of a novel analytical approach for high-speed evaluation of burn-up in spent nuclear fuel. This automated online separation–direct analysis method, which simultaneously measures the isotopic compositions and concentrations of Nd, Pu, and U using isotope dilution-inductively coupled plasma mass spectrometry, enables the determination of burnup in as little as 4.5 h per sample with expanded uncertainties as low as 1.2% using as little as 1µg of fuel. We compare the determined burn-up values, sample requirements, and analysis times with an ultra-high precision, in-house developed, methodology which employs multiple analytical techniques to measure the isotopic compositions and concentrations of Nd, Pu, and U yielding burn-up values with expanded uncertainties as low as 0.49% at the 95% confidence level, the lowest reported to date.
Destructive analytical measurements establish a nuclear facility’s nuclear material inventory and inventory differences for Nuclear Material Accountancy and Control. A nuclear laboratory’s ability to perform accurate high-precision analytical measurements is key for tracking large inventories within a facility’s material balance areas and during production to track material movement through dynamic processes. For uranium, these measurements are made by using several established high-precision measurement protocols. These include isotope dilution mass spectrometry, gravimetry, and potentiometric titrations. Whatever measurement technique a nuclear lab chooses to use, reference materials (RMs) with certified attributes and accompanying uncertainties are used to calibrate measurement systems, and are the cornerstone for accurate results. In addition to calibration, RMs provide for metrological traceability, are used for method development and validation, and thus provide critical evaluations of the appropriateness and performance of analytical processes used. Evaluations may include validation that a method is fit-for-purpose, quantification of systematic and random biases, and the evaluation of long-term and short-term performance metrics. High-precision measurement techniques require that measured attributes be certified to a high degree of precision in the RMs used—ultimately, to a higher degree than that of the measurement technique itself. The US authority on the production of special nuclear material Certified Reference Materials is the NBL Program Office (NBLPO), formally known as New Brunswick Laboratory (NBL). The NBLPO is responsible for the sales and distribution of existing NBL certified reference materials (CRMs) and for the production of the next generation of nuclear RMs. To accomplish its mission, NBLPO is establishing key base capabilities within the DOE laboratory complex that formerly existed at the NBL laboratory. The Nuclear Analytical Chemistry (NAC) section within the Chemical Sciences Division (CSD) at Oak Ridge National Laboratory (ORNL) is currently working with NBLPO to set up laboratory and measurement capabilities to provide measurements and capabilities for production and/or recertification of existing and future CRMs for uranium assay. The NBL-developed high-precision titration (HPT) method is a critically-evaluated, extremely precise and accurate primary method utilized for the determination of uranium content in a variety of uranium materials. The HPT method, combined with detailed balance weighing protocols, provides for an analytical methodology that is unsurpassed in precision and one in which all sources of error have been evaluated, a requirement of CRM certification. HPT capability within the United States was lost with the closure of the labs at NBL. The NAC has been collaborating with NBLPO to stand up and demonstrate the capability to perform uranium assay via HPT at ORNL. HPT can produce results with an expanded uncertainty of approximately 0.01% for pure uranium compounds, with typical precisions of <0.006%. The major tasks required to stand up the method at ORNL were the refurbishment of a dedicated lab and equipment setup, procedure development, analyst training, establishing method-specific quality assurance, and qualification of an analyst to perform the method. This report summarizes these tasks, outlines the documents drafted, and gives the outcome of the qualification titrations.
Sound speed data measured using a dual-path pulse-echo instrument are reported for pure trans-1,2-dichloroethene (R-1130(E)) and an azeotropic blend of cis-1,1,1,4,4,4-hexafluorobutene (R-1336mzz(Z)) and R-1130(E) with a composition of 74.8 mass % R-1336mzz(Z) with the balance being R-1130(E). The azeotropic blend of R-1336mzz(Z)/1130(E) is classified as R-514A in ANSI/ASHRAE standard 34. Liquid phase speed of sound data are reported from just above the saturation pressure of pure R-1130(E) or the bubble point pressure of R-514A to a maximum pressure of 26.7 MPa. The relative combined expanded uncertainty in the speed of sound varies from 0.032 % to 0.148 % with the greatest deviations occurring at the lowest sound speeds. At present, no reference Helmholtz-energy-explicit equation of state (EOS) is available for R-1130(E). Therefore, the reported data for pure R-1130(E) are compared to an extended corresponding states (ECS) model. Deviations between the pure R-1130(E) sound speed data and the ECS model were found to be consistently negative ranging between − 4.1 % and − 3.5 %. The R-514A data are compared to a multifluid model inclusive of the established reference Helmholtz-energy-explicit EOS for R-1336mzz(Z) and ECS model for R-1130(E) with estimated binary interaction parameters. Deviations between the experimental speed of sound data and the multifluid model were also found to be consistently negative. However, deviations from the multifluid model were found to be as great as − 17.1 %. The large deviations from the ECS model and multifluid model underscore the need for a robust Helmholtz-energy-explicit EOS for R-1130(E).
Candidate certified reference material (CRM) U196 was prepared by gravimetrically mixing and dissolving NNSA NRMP CRM 112-A (natural uranium metal) and CRM 116-A (highly enriched 93.2% 235 U metal) to achieve a high-assay low-enriched uranium (HALEU) isotopic abundance reference material. CRM U196 will be certified for the 233 U/ 238 U, 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios. Gravimetrically determined uranium isotope amount ratios and values derived from the isotope data were calculated from the buoyancy corrected mass data and from certified values for the metal CRMs used to create the solution. The 235 U isotope amount fraction (·100) and expanded uncertainty is 19.5846 ± 0.0028. For attribute verification, total evaporation and modified total evaporation isotope ratio measurements were performed. In conclusion, the reference material is to be distributed as a unit containing 5 mg uranium as dry uranyl nitrate.
Cryogenic decay energy spectrometry provides high energy resolution and enables absolute decay counting, offering an alternative measurement technique for radiochronometry. A cryogenic decay energy spectrometry experiment was conducted using a magnetic microcalorimeter to determine the age of a plutonium sample. The energy resolution was measured at 0.05% from 5 to 6 MeV. The time since sample purification was determined using the measured concentration ratio of the 241 Am/ 241 Pu radiochronometer. Sample age estimates based on 241 Pu alpha-decay and beta-decay counts, along with 241 Am decay counts, align with the expected sample age within expanded uncertainty (k = 2), supporting the accuracy of cryogenic decay energy spectrometry as a radiochronometric method.
Here, calcium fluoride formed by the reaction between ammonium bifluoride and calcium chloride was investigated as a dominating matrix for quantitative analysis by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Transformation from a solid sample to the calcium fluoride-based matrix permitted quantitative analysis based on calibration standards made from elemental standards. A low abundance stable calcium isotope, i.e. 44 Ca + , was monitored as the internal standard for quantitative analysis by LA-ICP-MS. Correlation coefficient factors for multiple elements were obtained with values over 0.999. The results for multiple elements in a certified reference material of soil (NIST SRM 2710a) agreed with the certified values in the range of expanded uncertainty, indicating the present method was valid for quantitation of elements in solid samples.
Here, in this study, data from thirteen laboratories from around the world are presented for a successful certification of uranium isotope ratios in uranium ore concentrate (UOC) certified reference materials from the National Research Council Canada. Different mass spectrometric measurement principles (including SF-ICP-MS, quadruple ICP-MS, TIMS, MC-ICP-MS, SIMS and AMS) and measurement procedures were employed. In general, data from all sources exhibit good consistency with TIMS and MC-ICP-MS showing superior performance. The three candidate UOC CRMs (UCLO-1, UCHI-1 and UPER-1) have natural uranium isotope ratios with certified values of 0.5304(7) x 10 -4 , 0.5475(2) x 10 -4 and 0.5361(4) x 10 -4 for n( 234 U)/n( 238 U) and 0.007 2563(13), 0.007 2563(10) and 0.007 2542(11) for n( 235 U)/n( 238 U), respectively, with expanded uncertainty (k = 2) applicable to the last digit of the value given in the parentheses. Information values for n( 236 U)/n( 238 U) in these three CRMs, measured by AMS, are also provided: 10 x 10 -12 , 200 x 10 -12 and 22 x 10 -12 . The uncertainties of the proposed certified values of uranium isotope ratios in UOC CRMs are superior to available reference materials, and the values of n( 234 U)/n( 238 U) and n( 236 U)/n( 238 U) show significant variation among the three CRMs.
In this work the isotopic ratios and weight percentages of 238 Pu, 239 Pu, 240 Pu, 241 Pu and 242 Pu were determined using Isotope Dilution Mass Spectrometry. Two samples of C136A and C138A were sent to the Analytical Research laboratories by the National Nuclear Security Administration Nuclear Reference Material Program. The four samples were dissolved in concentrated hydrochloric acid. From the parent solutions, eight aliquots were taken, diluted, spiked with 244 Pu and submitted to separations. After the samples were separated, they were analyzed using Multicollector Inductively Coupled Plasma Mass Spectrometry. Along with the samples, two C126A Quality Control Samples were analyzed each day. Mass bias standards were also analyzed at the beginning, during and at the end of the analysis. GUM Workbench Pro software Version 2.4.1.406 was used to calculate the isotopic ratios relative to 239 Pu, and total Pu mass and the correlated expanded uncertainties.
The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform
SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report (the first of six in the Data Quality and Uncertainty Integration project) reviews and evaluates the software to determine its suitability for determining the estimated expanded measurement uncertainty of solar measurement data by including operational factors. Using redundancy incorporated in three-component (global, direct, diffuse) solar measurements, SERI QC can quantify the standard uncertainty estimates for estimating uncertainty. With minor modifications, SERI QC will provide an operational uncertainty to be used in conjunction with the National Renewable Energy Laboratory method for instrument uncertainty to provide an integrated estimate of solar measurement data sets. These modifications will capitalize on SERI QC's evaluation of data quality, including data input validation and a variety of built-in solar routines, and will further develop the utility of the software.
Calibrated values of many devices exhibit predictable drift over time. To provide an uncertainty statement valid over the entire calibration interval, one must account for drift. In this article, a method of accounting for drift is proposed based on guidance in the Guide to Expression of Uncertainty in Measurement. An additional uncertainty term is computed using a linear regression of historical measurement data, which is included along with the time-of-test uncertainty. This method is evaluated by analyzing its average out-of-tolerance (OOT) rate using a Monte Carlo simulation, which results in the desired 5% average OOT rate when the total uncertainty is expanded to a 95% confidence interval.
The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.
We introduce a robust verification tool for computational codes, which we call Stochastic Robust Extrapolation based Error Quantification (StREEQ). Unlike the prevalent Grid Convergence Index (GCI) [1] method, our approach is suitable for both stochastic and deterministic computational codes and is generalizable to any number of discretization variables. Building on ideas introduced in the Robust Verification [2] approach, we estimate the converged solution and orders of convergence with uncertainty using multiple fits of a discretization error model. In contrast to Robust Verification, we perform these fits to many bootstrap samples yielding a larger set of predictions with smoother statistics. Here, bootstrap resampling is performed on the lack-of-fit errors for deterministic code responses, and directly on the noisy data set for stochastic responses. This approach lends a degree of robustness to the overall results, capable of yielding precise verification results for sufficiently resolved data sets, and appropriately expanding the uncertainty when the data set does not support a precise result. For stochastic responses, a credibility assessment is also performed to give the analyst an indication of the trustworthiness of the results. Furthermore, this approach is suitable for both code and solution verification, and is particularly useful for solution verification of high-consequence simulations..