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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.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The XMM Cluster Survey analysis of the SDSS DR8 redMaPPer catalogue: implications for scatter, selection bias, and isotropy in cluster scaling relations

ABSTRACT In this paper, we present the X-ray analysis of Sloan Digital Sky Survey DR8 redMaPPer (SDSSRM) clusters using data products from the XMM Cluster Survey (XCS). In total, 1189 SDSSRM clusters fall within the XMM–Newton footprint. This has yielded 456 confirmed detections accompanied by X-ray luminosity (LX) measurements. Of these clusters, 381 have an associated X-ray temperature measurement (TX). This represents one of the largest samples of coherently derived cluster TX values to date. Our analysis of the X-ray observable to richness scaling relations has demonstrated that scatter in the TX–λ relation is roughly a third of that in the LX–λ relation, and that the LX–λ scatter is intrinsic, i.e. will not be significantly reduced with larger sample sizes. Analysis of the scaling relation between LX and TX has shown that the fits are sensitive to the selection method of the sample, i.e. whether the sample is made up of clusters detected ‘serendipitously’ compared to those deliberately targeted by XMM. These differences are also seen in the LX–λ relation and, to a lesser extent, in the TX–λ relation. Exclusion of the emission from the cluster core does not make a significant impact on the findings. A combination of selection biases is a likely, but yet unproven, reason for these differences. Finally, we have also used our data to probe recent claims of anisotropy in the LX–TX relation across the sky. We find no evidence of anistropy, but stress this may be masked in our analysis by the incomplete declination coverage of the SDSS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Coal Fired Power Plant Configuration and Operation Impact on Plant Effluent Contaminants and Conditions

The primary objective of this project is to characterize coal contaminants in coal-fired power plant wastewater as a function of coal type, unit configurations, and unit operation profile with uncertainty analysis. This project was in response to the U.S. Department of Energy (DOE) Solicitation DE-FOA-0001842. The project duration was between September 01, 2018, and December 31, 2021 (no-cost extension filed, due to the Covid-19 pandemic restrictions, and approved). Field and lab test program was conducted with the main goal to characterize coal contaminants in coal-fired power plant wastewater as a function of coal type, unit configurations, and unit operation profile with uncertainty analysis. In this project, the team of Lehigh University (prime recipient) and Western Kentucky University identified two suitable Thermoelectric Power Plants (TTPs) firing bituminous and sub-bituminous coals respectively, designed test plans, and performed sample collection. Sampling included coal from each TTPs power generation units, Wet Flue Gas Desulfurization (WFGD) slurry material and waste-water samples taken from the outlet of the water treatment tank prior to discharge and other pertinent locations. Coal samples are dried, crushed, and pulverized according to the American Society for Testing and Materials (ASTM) methods. The prepared coal samples are analyzed for normal proximate and ultimate analysis tests in addition to the toxic metals and anions according to ASTM methods. The FGD slurry materials are analyzed for toxic metals and anions according to Electric Power Research Institute (EPRI) or Environmental Protection Agency (EPA) methods, as appropriate. The wastewater samples from the water treatment tank outlet are analyzed for toxic metals and anions according to EPA methods. The effluent species analyzed include mercury, arsenic, selenium, nitrate/nitrite, bromide, and chlorine. This project provided results of effluent conditions as a function of coal type, unit configuration, and unit operation profile, and identified the levels of uncertainty in the effluent results.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Optimization of In-Field Alpha Spectrometry for Uranium Enrichment Determination in Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (UO2F2). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2021

Optimization Of In-field Alpha Spectrometry For Uranium Enrichment Determination In Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (as a dihydrate, UO2F2·2H2O). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

Chichester, David↗
DOE OSTI2021

A Data-Driven Multi-Period Importance Sampling Strategy for Stochastic Economic Dispatch

Power systems with high penetrations of renewable energy (e.g., wind power) require sophisticated approaches to optimize system performance due to uncertainty in short-term system generation capacity. In this paper, we combine a data-driven analog scenario selection method with importance sampling to create a novel scenario construction approach for two-stage stochastic economic dispatch problems with a large number of wind farms on a network. The proposed method produces scenarios with realistic physics by finding high-fidelity analogs that can describe future states of the system. We show how to extend this method to multi-period operations and demonstrate the effectiveness of this technique by simulating economic dispatch operations on a synthetic test system over the course of a week.

data-driven forecasting↗
DOE OSTI2022

Critical points of the random cluster model with Newman–Ziff sampling

Here, we present a method for computing transition points of the random cluster model using a generalization of the Newman–Ziff algorithm, a celebrated technique in numerical percolation, to the random cluster model. The new method is straightforward to implement and works for real cluster weight q > 0. Furthermore, results for an arbitrary number of values of q can be found at once within a single simulation. Because the algorithm used to sweep through bond configurations is identical to that of Newman and Ziff, which was conceived for percolation, the method loses accuracy for large lattices when q > 1. However, by sampling the critical polynomial, accurate estimates of critical points in two dimensions can be found using relatively small lattice sizes, which we demonstrate here by computing critical points for non-integer values of q on the square lattice, to compare with the exact solution, and on the unsolved non-planar square matching lattice. The latter results would be much more difficult to obtain using other techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Machine Learning-Based Vulnerability Analysis for Cascading Failures of Integrated Power-Gas Systems

This article proposes a cascading failure simulation (CFS) method and a hybrid machine learning method for vulnerability analysis of integrated power-gas systems (IPGSs). The CFS method is designed to study the propagating process of cascading failures between the two systems, generating data for machine learning with initial states randomly sampled. The proposed method considers generator and gas well ramping, transmission line and gas pipeline tripping, island issue handling and load shedding strategies. Then, a hybrid machine learning model with a combined random forest (RF) classification and regression algorithms is proposed to investigate the impact of random initial states on the vulnerability metrics of IPGSs. Extensive case studies are carried out on three test IPGSs to verify the proposed models and algorithms. Simulation results show that the proposed models and algorithms can achieve high accuracy for the vulnerability analysis of IPGSs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Examining the effects of chemical cleaning, leaching, and partial dissolution on zinc and cadmium isotope fractionation in marine carbonates

The application of zinc (Zn) and cadmium (Cd) isotopes as palaeo-proxies in carbonate sediment is rapidly expanding due to their potential for tracing changes in biological productivity in the modern and past oceans. However, there are limited investigations into the chemical cleaning methods required to produce the most consistent and accurate data for these novel isotope systems. This could impact their use as palaeo-proxies to reconstruct ocean-atmosphere-climate interactions throughout Earth's history. To address this concern and expand the utility of the Zn and Cd stable isotope systems as palaeo-productivity tracers, the performance of two standard chemical cleaning protocols for acquiring robust and reliable Zn and Cd isotope datasets were assessed. These include (i) the Cd-cleaning method that uses a reductive step to selectively leach contaminating secondary iron (Fe)-manganese (Mn) (oxyhydr)oxide coatings from the carbonate surface, and an oxidative step that is used to remove post-depositional organic matter and sulphide precipitates; and (ii) the magnesium/calcium cleaning protocol that includes an oxidative step only, leaving secondary Fesingle bondMn (oxyhydr)oxide coatings largely intact. Well-preserved Holocene-, and Mesozoic-aged carbonate sediments were used to test the reliability of these two chemical cleaning methods. The Holocene samples comprised not only aliquots of bulk sediment, but also individual species of planktic and benthic foraminifera. Our results show that the best practice chemical cleaning method for retrieving consistent and accurate Zn and Cd isotope, and Zn/Ca and Cd/Ca datasets for carbonate sediments, requires both reductive and oxidative cleaning following the Cd-cleaning method. This differs from most methodological approaches applied to date that remove the reductive step from the chemical cleaning protocol and apply an oxidative step only, or no chemical cleaning at all. Inclusion of the reductive step in the chemical cleaning method typically shifts δ 66 Zn by ~0.1‰ lower and δ 114 Cd by 0.3‰ higher in the solid phase, while Zn/Ca and Cd/Ca typically decrease 2-fold. The benthic foraminifera, C. wuellerstorfi, that live in ocean bottom waters where the seawater Zn and Cd isotope composition is homogeneous display evidence of Zn and Cd isotope fractionation between seawater and carbonate on the order of 0.08 ± 0.08‰ (2SE, n = 4) and -0.25 ± 0.13‰ (2SE, n = 4), respectively, in agreement with experimental constraints. Furthermore, evidence of Zn isotope fractionation effects are recorded in a naturally-dissolved carbonate sediment, together with laboratory-controlled carbonate dissolution experiments. Based on these results, we recommend the Cd-cleaning method and the application of Zn and Cd isotope fractionation factors to accurately reconstruct past seawater Zn and Cd isotope compositions from carbonate sediments.

58 GEOSCIENCES↗
DOE OSTI2024

Classification of events from α -induced reactions in the MUSIC detector via statistical and ML methods

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other applications. From the MUSIC data produced in one experiment scientists carefully extract an order of 10 3 events of interest from about 10 9 total events, where each event can be represented by an 18-dimensional vector. However, the standard data classification process is based on expert driven, manually intensive data analysis techniques that require several months to identify patterns and classify the relevant events from the collected data. Here, to address this issue, we present a method for the classification of events originating from specific α-induced reactions by combining statistical and machine learning methods that require significantly less input from the domain scientist, relative to the standard technique. Here, we applied the new method to two experimental data sets and compared our results with those obtained using traditional methods. With few exceptions, the number of events classified by our method agrees within ±20% with the results obtained using traditional methods. With the present method, which is the first of its kind for the MUSIC data, we have established the foundation for the automated extraction of physical events of interest from experiments using the MUSIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Optimization of a Cyclone Using Multiphase Flow Computational Fluid Dynamics

The U.S. Department of Energy National Energy Technology Laboratory's (NETL) 50 kW th chemical looping reactor (CLR) has an underperforming cyclone, which was designed using empirical correlations. To improve the performance of this cyclone using computational fluid dynamics (CFD)-based modeling simulations, four critical design parameters including the vortex tube radius and length, barrel radius, and the inlet width and height were optimized. Here, NETL's open source multiphase flow with interphase exchange (MFiX) CFD code has been used to model a series of cyclones by systematically varying the geometric design parameters. To perform the optimization process, the surrogate modeling and sensitivity analysis followed by the optimization capability in nodeworks was used. The basic methodology for the process is to employ a statistical design of experiments (DOE) method to generate sampling simulations that fill the design space. Corresponding CFD models are then created, executed, and postprocessed. A response surface is created to characterize the relationship between input parameters and the quantities of interest (QoI). Finally, the CFD-surrogate is used by an optimization method to find the optimal design condition based on the objective and constraints prescribed. The resulting optimal cyclone has a larger diameter and longer vortex tube, a larger diameter barrel, and a taller and narrower solids inlet. The improved design has a predicted pressure drop 11 times lower than the original design while reducing the mass loss by a factor of 2.3.

42 ENGINEERING↗
DOE OSTI2022

WHONDRS Surface Water Chemistry and Organic Matter Characterization along the St. Lawrence River's Inland to Coastal Gradient, Eastern North America (v2)

This dataset supports a broader study examining the inland (Lake Ontario) to coastal (North Atlantic Ocean) geochemistry gradient along the St. Lawrence River in Canada and the United States. The St. Lawrence River is unique in that it contains the convergence of multiple water masses with distinct water signatures that mix only slightly as the river flows downstream. The dataset provides dissolved organic carbon (DOC) and organic matter characterization data generated from surface water. Samples were collected by researchers on board the Lampsilis research vessel (l’Université du Québec à Trois-Rivières) and small boats (St. Lawrence River Institute of Environmental Sciences, Cornwall) at 94 locations across and along the St. Lawrence River to capture longitudinal and transverse variation. Related data were collected and will be published separately in collaboration with the MicrEAU Laboratory (François Guillemette; l’Université du Québec à Trois-Rivières) and the Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; and (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. The data package was originally published in November 202. It was updated in April 2025 (v2; modified files). See the change history section in the readme for details.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

WHONDRS Surface Water Dissolved Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2022

This dataset supports a broader study examining climatic forcing of terrestrial greenhouse gas emission through permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from 11 sites across central Svalbard. Data were also collected in 2021 and can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1888571. Additional related data were collected and will be published separately in collaboration with Yde and Kleber.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; (9) a folder of field photos; and (10) folder of high resolution characterization of organic matter via 7 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Detection of Chymotrypsin by Optical and Acoustic Methods

Chymotrypsin is an important proteolytic enzyme in the human digestive system that cleaves milk proteins through the hydrolysis reaction, making it an interesting subject to study the activity of milk proteases. In this work, we compared detection of chymotrypsin by spectrophotometric dynamic light scattering (DLS) and quartz crystal microbalance (QCM) methods and determined the limit of chymotrypsin detection (LOD), 0.15 ± 0.01 nM for spectrophotometric, 0.67 ± 0.05 nM for DLS and 1.40 ± 0.30 nM for QCM methods, respectively. The sensors are relatively cheap and are able to detect chymotrypsin in 3035 min. While the optical detection methods are simple to implement, the QCM method is more robust for sample preparation, and allows detection of chymotrypsin in non-transparent samples. We give an overview on methods and instruments for detection of chymotrypsin and other milk proteases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

In Situ High-Temperature Structural Analysis of High-Entropy Rare-Earth Sesquioxides

High-entropy rare-earth (RE) sesquioxides (RE 2 O 3 ) containing five cations in equimolar amounts have been investigated for a variety of applications, but little is known about their polymorphic behavior and coefficient of thermal expansion. Here, in this work, we evaluate the effect of the average ionic radius (AIR) on the polymorphism of high-entropy RE 2 O 3 . Powder samples of compositions 1 (Lu,Y,Ho,Nd,La) 2 O 3 (AIR = 0.938 Å) and 2 (Gd,Eu,Sm,Nd,La) 2 O 3 (AIR = 0.982 Å) were synthesized via a wet chemical method, and bead samples were prepared for aerodynamic levitation by melting the powders in a copper hearth. Structural transitions were monitored upon cooling from the melt to 1000 °C via in situ X-ray diffraction on aerodynamically levitated samples. The phase evolution was liquid, hexagonal H-type, and monoclinic B-type for composition 1 and liquid, cubic X-type, H-type, and B-type for composition 2. Based on their AIR, the general polymorphic transformations of the high-entropy RE 2 O 3 follow the trend of single-RE RE 2 O 3 , but the transition temperatures differ from those of single-RE RE 2 O 3 . The coefficient of thermal expansion values of the B-type phase of compositions 1 and 2 are similar to those of Gd 2 O 3 and previously published high-entropy RE 2 O 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reducing the Cost of Energy Differences in Variational Monte Carlo with Spotlight Sampling

Here, we investigate an approximate sampling scheme that can significantly reduce the cost scaling of variational Monte Carlo when it is employed to predict the energy differences associated with local chemical changes. Inspired by side-chaining and embedding methods, this spotlight sampling approach adopts an approximate fragmented Hamiltonian and correlated sampling to reduce cost scaling to the point that it is essentially linear with system size, with the potential to go sublinear if certain conditions are met. In tests on bond stretching energies in alcohols, hydrogen dimer chains, and molecules with various degrees of π-system delocalization, we observe the anticipated linear scaling and an explicit cost crossover with standard variational Monte Carlo.

Bumann, Sonja [University of California, Berkeley,↗
DOE OSTI2022

On the thermal oxidation of nuclear graphite relevant to high-temperature gas cooled reactors

Thermal oxidation of nuclear graphite components is highly undesirable because it can cause structural and property degradation that negatively affect a reactor's intended operation. In this work, the body of knowledge of nuclear graphite oxidation is highlighted, including when O 2 , H 2 O, and/or CO 2 are the oxidant. Oxidation conditions relevant to high-temperature gas-cooled reactors (i.e., when oxidation could occur either as an acute or chronic phenomenon) are emphasized. Here, the objective is to summarize graphite oxidation data in a practical and accessible way to inform future research and regulatory requirements. Although each grade of nuclear graphite is different, the oxidation mechanism has underlying commonalities. Although oxidation behavior is grade dependent, the general temperature dependence is well described by a sequence of elementary steps which become rate limiting. Because the regime transition temperature depends on sample microstructure, size, and oxidant supply rate, extrapolating results beyond the experimental range should be done cautiously. Gravimetric oxidation rate measurements generally replicate well. However, caution must be exercised when rates are estimated by other methods or for samples that deviate significantly in size. Air oxidation data for IG-110, NBG-18, and PCEA graphite is critically reviewed to emphasize this point. Despite the amount of experimental data, gaps remain. Sample size and shape effects are not fully explained. Data on the oxidant penetration depth are insufficient. Analytical assessments demonstrate that lower temperature oxidation does not necessarily imply that oxidation is uniform throughout the bulk. Oxidation occurs faster at higher temperature but is more localized to the exposed surface. Paradoxically, at equal mass loss percentage, low temperature oxidation leads to greater property degradation than at high temperature. The isolated effect of oxidation is important; however, a gap remains in the systematic understanding of any potential effect of neutron irradiation on graphite structure and reactivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The LLNL nuclear data infrastructure for the GNDS data format

The next generation of nuclear data infrastructure tools at the Livermore National Laboratory (LLNL) consists of pipeline of codes that read and process nuclear data from evaluated files saved in the new GNDS (Generalised Nuclear Data Structure) nuclear data format. The processing code FUDGE (For Updating Data and Generating Evaluations) is at the front-end of this pipeline as it reads and process the evaluated data for use in downstream transport codes. FUDGE is Python based with C and C++ extensions for computationally intensive tasks. As is the case for the evaluated data, the processed output is also saved in the GNDS format and the GIDI+ API is provided as the interface between the processed data and the transport codes. GIDI+ is a C++ based suite of codes and it includes GIDI (General Interaction Data Interface), a library for reading and writing GNDS data, and MCGIDI which is the cross section lookup, and reaction and product distribution sampling interface between Monte Carlo transport codes and the GNDS data. GIDI provides methods for easy access to the multi-group processed GNDS data and this is demonstrated through its implementation in ARDRA, the LLNL deterministic transport code. The evaluation and sampling methods in MCGIDI are available as both CPU and GPU methods which facilitates the use of MCGIDI in both traditional CPU-based as well as the next generation mixed model computational architectures. This is demonstrated through the GIDI+ implementation in MERCURY, the LLNL Monte Carlo transport code. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Nature of native atomic defects in ZrTe 5 and their impact on the low-energy electronic structure

Over the past decades, investigations of the anomalous low-energy electronic properties of ZrTe 5 have reached a wide array of conclusions. An open question is the growth method's impact on the stoichiometry of ZrTe 5 samples, especially given the very small density of states near its chemical potential. In this work, we report on high-resolution scanning tunneling microscopy and spectroscopy measurements performed on samples grown via different methods. Using density functional theory calculations, we identify the most prevalent types of atomic defects on the surface of ZrTe 5 , namely, Te vacancies and intercalated Zr atoms. Finally, we precisely quantify their density and outline their role as ionized defects in the anomalous resistivity of this material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗