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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Performant, Scalable Processing Pipeline for High‐Quality and FAIR Environmental Sensor Data

High-resolution environmental monitoring is necessary to record, understand, and predict biogeochemical and ecological changes particularly in coastal systems but brings significant challenges in processing and making rapidly available the resulting data. The COMPASS-FME project established a network of coastal observational sites across the Chesapeake Bay and western Lake Erie regions extensively instrumented with soil, vegetation, and weather sensors logging data every 15 min. Our data processing framework, written in R and completely open source, prioritizes rapid model-experiment iteration and makes biogeochemical data rapidly available for quality assurance/quality control, analysis, and model ingestion. This pipeline is distinguished by a standardized and modular approach to data curation, extensive metadata and documentation, and its high performance. These attributes combine to make biogeochemical data rapidly accessible across COMPASS-FME and the broader community. Flexible, powerful, and reproducible approaches to handling high-volume environmental data are crucial for accelerating biogeosciences research.

Pennington, Stephanie C. [Pacific Northwest Nation↗
DOE OSTI2020

Evaluating the Utility of Permethylated Polysaccharide Solution NMR Data for Characterization of Insoluble Plant Cell Wall Polysaccharides

Plant cell wall polysaccharide analysis encompasses the utilization of a variety of analytical tools, including gas and liquid chromatography, mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy. These methods provide complementary data, which enable confident structural proposals of the many complex polysaccharide structures that exist in the complex matrices of plant cell walls. However, cell walls contain fractions of varying solubilities, and a few techniques are available that can analyze all fractions simultaneously. We have discovered that permethylation affords the complete dissolution of both soluble and insoluble polysaccharide fractions of plant cell walls in organic solvents such as chloroform or acetonitrile, which can then be analyzed by a number of analytical techniques including MS and NMR. In this work, NMR structure analysis of 10 permethylated polysaccharide standards was undertaken to generate chemical shift data providing insights into spectral changes that result from permethylation of polysaccharide residues. This information is of especial relevance to the structure analysis of insoluble polysaccharide materials that otherwise are not easily investigated by solution-state NMR methodologies. The preassigned NMR chemical shift data is shown to be vital for NMR structure analysis of minor polysaccharide components of plant cell walls that are particularly difficult to assign by NMR correlation data alone. With the assigned chemical shift data, we analyzed the permethylated samples of destarched, alcohol-insoluble residues of switchgrass and poplar by two-dimensional NMR spectral profiling. Thus, we identified, in addition to the major polysaccharide components, two minor polysaccharides, namely, <5% 3-linked arabinoxylan (switchgrass) and <2% glucomannan (poplar). In particular, the position of the arabinose residue in the arabinoxylan of the switchgrass sample was confidently assigned based on chemical shift values, which are highly sensitive to local chemical environments. Furthermore, the high resolution afforded by the 1H NMR spectra of the permethylated switchgrass and poplar samples allowed facile relative quantitative analysis of their polysaccharide composition, utilizing only a few milligrams of the cell wall material. As a result, the concepts herein developed will thus facilitate NMR structure analysis of insoluble plant cell wall polysaccharides, more so of minor cell wall components that are especially challenging to analyze with current methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Observational Constraints on the Spatial Effect of Greenness and Canopy Cover on Urban Heat in a Major Midlatitude City

Abstract Urban heat stress is a critical issue, particularly in cities where dense infrastructure and limited green space exacerbate temperature extremes. This study investigates the impact of greenery (EVI2), canopy cover (CC), impervious cover (IC), and water bodies on heat index in Chicago using high‐resolution data from the Heat Watch campaign. We find that EVI2, CC and proximity to water body significantly reduce heat while IC increases heat, particularly in the afternoon when solar radiation is intense. Additionally, the effective radius that land cover impacts heat is smaller in the afternoon. The combined effect analysis indicates that enhancing total greenness, not just canopy cover, is the most effective strategy to reduce heat. This study underscores the importance of strategic vegetation management, highlighting the critical role of integrated approaches in reducing urban heat.

Lee, Jangho↗
DOE OSTI2021

Error-controlled, progressive, and adaptable retrieval of scientific data with multilevel decomposition

Extreme-scale simulations and high-resolution instruments have been generating an increasing amount of data, which poses significant challenges to not only data storage during the run, but also post-processing where data will be repeatedly retrieved and analyzed for a long period of time. The challenges in satisfying a wide range of post-hoc analysis needs while minimizing the I/O overhead caused by inappropriate and/or excessive data retrieval should never be left unmanaged. In this paper, we propose a data refactoring, compressing, and retrieval framework capable of 1) fine-grained data refactoring with regard to precision; 2) incrementally retrieving and recomposing the data in terms of various error bounds; and 3) adaptively retrieving data in multi-precision and multi-resolution with respect to different analysis. With the progressive data re-composition and the adaptable retrieval algorithms, our framework significantly reduces the amount of data retrieved when multiple incremental precision are requested and/or the downstream analysis time when coarse resolution is used. Experiments show that the amount of data retrieved under the same progressively requested error bound using our framework is 64% less than that using state-of-the-art single-error-bounded approaches. Parallel experiments with up to 1, 024 cores and ~ 600 GB data in total show that our approach yields 1.36× and 2.52× performance over existing approaches in writing to and reading from persistent storage systems, respectively.

Liang, Xin↗
DOE OSTI2020

reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]

The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory’s (NREL’s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL’s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).

Maclaurin, Galen↗
DOE OSTI2024

metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics

Liquid chromatography–high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a “primary” feature list is used as a template for matching compounds in “target” feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution’s in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Measurement of Stark-split beam and carbon charge exchange emissions for simultaneous B-field and temperature/rotation analysis at DIII-D

A set of two newly designed, single-channel Czerny–Turner spectrometers has been deployed at the DIII-D tokamak for measurements of the motional Stark effect (MSE) split beam emission and the C6+ (CVI) carbon charge exchange recombination (CER) emission at high spectral (δλ = 0.13 nm) and temporal (1–5 kHz) resolution. High throughput optics (f/# = 2.8) allow for good signal-to-noise at high time resolution using fast EMCCD detectors. The MSE emission allows for spectral fitting of the magnitude and direction of the local B-field, while the carbon emission yields local ion temperature and toroidal rotation information. To reduce so-called Doppler broadening of the MSE emission, a new channel-specific variable lens-masking approach has been developed. Experimental data collected from the 2023 DIII-D experimental campaign demonstrate the signal quality and instrument fidelity for both diagnostic measurements. Moreover, initial CER data analysis shows a clear evolution of the toroidal rotation during edge localized modes. Initial progress on the advanced MSE model, including a new validated ray-trace model of the DIII-D collection optics, is shown via sensitivity analysis.

Instruments & Instrumentation↗
DOE OSTI2021

High-Resolution Regional Wave Hindcast for U.S. Pacific Island Territories

This report summarizes modeling efforts for hindcasting of wave climate within the Exclusive Economic Zone around American Samoa, Baker Island and Howland Island, Commonwealth of Northern Mariana Islands, Guam, Jarvis Island, Johnston Atoll, Palmyra Atoll and Kingman Reef, and Wake Island. The report describes the mesh development and data sources used in the process. In addition, it provides the results of a sensitivity analysis performed to determine the optimal model configuration, details the data used for model forcing, shows a detailed skill assessment, and depicts the output.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Generating Emissions Inventory for Carbon Capture and Storage Analysis for Carbon-Intensive Industrial Sectors

Decarbonizing the industrial sector is critical to achieve carbon dioxide (CO2) emissions reductions goals of the Biden Administration. Currently available decarbonization options include electrification, fuel switching to zero carbon fuels like green hydrogen (H2) and carbon capture and storage (CCS). Application of post-combustion carbon capture (PCCC) technology in the power sector, as well as research at the U.S. Department of Energy's Fossil Energy and Carbon Management (FECM) Office has shown that its application in the industrial sector could have co-benefits in the form of emissions reductions of non-CO2 regulated pollutants. For example, solvent based PCCC systems require pre-conditioning of flue gas to remove sulfur and particulate matter (PM) upstream of the CO2 absorber. However, there is a lack of understanding about the type of non-CO2 pollutants which can be captured and the amount of reduction possible. PCCC application differs across industrial sectors as it depends on the availability of decarbonization options, characteristics of industrial processes and the amount and composition of pollutant flows. Certain facilities can also have multiple effluent flows with or without a CO2 stream. As such, understanding industrial processes and their effluent flows in detail is required to quantify the co-benefits opportunities presented by PCCC. Considering this requirement, the goal of this analysis is to develop a high-resolution inventory of effluent flows from facilities of 8 industrial sectors in the U.S. These industrial sectors - ethanol, ammonia, cement, steel, natural gas processing, hydrogen, petroleum refining and wood and pulp products - have carbon-intensive effluent flows, and thus are prime candidates for PCCC applications. In this study, we map the composition of pollutant flow from flue stacks across the identified facilities. Using data available in three Environmental Protection Agency (EPA) databases - the Green House Gas Reporting Program (GHGRP), the National Emissions Inventory (NEI) and the Toxic Release Inventory (TRI), we create a combined inventory which lists the type, amount, and concentration of pollutant flows. Using total weight of the pollutant flow back calculated from observed data for CO2 concentrations in flue gas for individual sectors, we calculate the concentration of each pollutant in the flue gas stream. Thus, the resultant emissions inventory includes the following details for each facility in the sector: facility-level and if possible, process-level pollutant flows, concentrations of pollutants in the flue gas, and geographical coordinates of the facilities. A detailed statistical analysis and summary allows us to search for erroneous data and remove them from the final inventory. The generation of the inventory is achieved using a python-based framework which can recreate this inventory for other industrial sectors as well as using newer releases of emission inventories from EPA. The statistical analysis performed on the inventory is also calibrated and automated to identify outliers efficiently.

air pollutants↗
DOE OSTI2026

Search for low-mass electron-recoil dark matter using a single-charge sensitive SuperCDMS-HVeV detector

We present constraints on low-mass dark matter electron scattering and absorption interactions using a SuperCDMS high-voltage eV-resolution (HVeV) detector. Data were taken underground in the NEXUS facility located at Fermilab with an overburden of 225 meters of water equivalent. The experiment benefits from the minimizing of luminescence from the printed circuit boards in the detector holder used in all previous HVeV studies. A blind analysis of 6.1 g · days of exposure produces exclusion limits for dark matter-electron scattering cross sections for masses as low as 1 MeV/𝑐 2 , as well as on the photon-dark photon mixing parameter and the coupling constant between axionlike particles and electrons for particles with masses >1.2 eV/𝑐 2 probed via absorption processes.

dark matter direct detection↗
DOE OSTI2022

Lowest-energy broad 𝛼-cluster resonances in 19 F

There is strong astrophysical interest in the structure of 19 F states near the α-decay threshold, as their properties are important for understanding the development of α clustering in the 20 Ne region. The emergence of clustered states, and more generally of states that couple strongly to reaction channels near their decay thresholds, is also a topic of current interest in theoretical nuclear physics. In this work, we determine the parameters of broad low-spin states in 19 F near the α-decay threshold and present a theoretical study of these states. The analysis is restricted to ℓ = 0 and 1 resonances in the α + 15 N system close to the α threshold in 19 F. Excitation functions for 15 N(α,α) elastic scattering were measured using the Thick Target Inverse Kinematics (TTIK) method, and these new data, together with older high–energy-resolution measurements, were analyzed within the R-matrix framework. The nuclear structure of 19 F was calculated using configuration-interaction methods with a recently developed effective interaction Hamiltonian. As a result, we identify a sequence of α-cluster resonances in 19 F and map the distribution of clustering strength, which is relevant for astrophysical reaction modeling and for the theoretical understanding of many-body dynamics and the emergence of clustering in loosely bound or unstable nuclei. Furthermore, the work advances theoretical insight into the origins of clustering and highlights open questions for future theoretical and experimental studies.

19F↗
DOE OSTI2020

X-ray photoelectron spectroscopy data from lightly Pd doped TiO 2 anatase nanoparticles

Here, two sets of XPS spectra from ≈13 nm slightly Pd-doped anatase TiO 2 particles are reported. Anatase is the most stable form of TiO 2 for small particles, and these spectra are the first spectra from nano-sized anatase to appear in Surface Science Spectra. The high resolution Ti 2p spectrum has an extended range showing important loss features not appearing in most of the earlier data records. The O 1s spectrum also has loss features often ignored, and in this case, the loss features are overlapped by some of the Ti 2s peak features that complicate quantitative analysis. The spectra reported here were used as example spectra in a guide to backgrounds in XPS, and the availability of these spectra in digital form allows LRH-analysts to compare their background selections and analysis approach to those discussed in the guide.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Investigation into the transport properties of planetary interiors through inelastic X-ray scattering experiments and quantum molecular dynamics (Final Technical Report)

This was a two-year research project for the period 08/15/2018 - 08/14/2020 conducted at the University of Nevada, Reno using Pronghorn, a newly built high-performance cluster located at the University. The short-term project goal was to provide computational support for the experimental campaigns at LCLS through data analysis of previous and upcoming scheduled experiments, along with performing state-of-the-art atomistic simulations of dense plasmas. The longer-term goal was to create a new computational high energy density physics group located at the University of Nevada, Reno. Guided by results from past and future high-resolution scattering experiments, we aimed to research and develop non-equilibrium and non-adiabatic atomistic simulations of dense plasmas that went beyond the Born-Oppenheimer approximation

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Combining Astrometry and Elemental Abundances: The Case of the Candidate Pre-Gaia Halo Moving Groups G03-37, G18-39, and G21-22

While most moving groups are young and nearby, a small number have been identified in the Galactic halo. Understanding the origin and evolution of these groups is an important piece of reconstructing the formation history of the halo. Here we report on our analysis of three putative halo moving groups: G03-37, G18-39, and G21-22. Based on Gaia EDR3 data, the stars associated with each group show some scatter in velocity (e.g., Toomre diagram) and integrals of motion (energy, angular momentum) spaces, counter to expectations of moving-group stars. We choose the best candidate of the three groups, G21-22, for follow-up chemical analysis based on high-resolution spectroscopy of six presumptive members. Using a new Python code that uses a Bayesian method to self-consistently propagate uncertainties from stellar atmosphere solutions in calculating individual abundances and spectral synthesis, we derive the abundances of α- (Mg, Si, Ca, Ti), Fe-peak (Cr, Sc, Mn, Fe, Ni), odd-Z (Na, Al, V), and neutron-capture (Ba, Eu) elements for each star. We find that the G21-22 stars are not chemically homogeneous. Based on the kinematic analysis for all three groups and the chemical analysis for G21-22, we conclude the three are not genuine moving groups. The case for G21-22 demonstrates the benefit of combining kinematic and chemical information in identifying conatal populations when either alone may be insufficient. Comparing the integrals of motion and velocities of the six G21-22 stars with those of known structures in the halo, we tentatively associate them with the Gaia-Enceladus accretion event.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Database to Enable Facial Analysis for Driving Studies (DEFADS)

Naturalistic Driving Studies (NDS) collect and utilize data on drivers in real-world environments in instrumented vehicles. A common problem with such studies is driver privacy. In this work we collected a dataset of 77 human subjects performing scripted driving-related activities. We used three camera systems for the collection, including two high-resolution webcam devices as well as a third system from an actual NDS (the Second Strategic Highway Research Project, or SHRP2). This report covers the data collection process and summarizes the dataset, which will be made publicly available to researchers under a data usage license.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Analysis of several high-resolution infrared bands of perdeutero-spiropentane, C5D8

Perdeutero-spiropentane (C5D8) has been synthesized and infrared spectra were taken from 400 to 4000 cm-1 at low sample pressures in a 22 meter multipass cell. The spectral resolution (0.0015 cm-1) reveals thousands of individual rovibrational transitions for several fundamental bands occurring in the spectral region of 500 to 1100 cm-1. C5D8 ground state constants reported in a previous study of a ?15 parallel band at 1054 cm-1 [1] were improved significantly in the present work by adding combination-differences derived from ?16 parallel and ?24 perpendicular band analyses. The larger data set at higher J values also allowed determination of the ground state K? = 2 splitting constant (?2? = 0.76(2) ×10-9 cm-1). For ?16, the band origin is 847.16933(5) cm-1 and changes in upper state rotational constants are ?A = –0.0013411(5) and ?B = –0.0002021(1) (in units of cm-1). Overlapping, and in Fermi resonance with ?16, is a second parallel band which, from Gaussian calculations at the anharmonic level, is assigned as the b2 combination ?8+?12, with band origin of 840.5434(1) and ?A = –0.0003500(7) and ?B = –0.0003502(1) cm-1. For ?24 analogous values are 556.41453(2) and ?A = –0.00032295(9) and ?B = –0.00016782(4) cm-1. The analyses also yields accurate values for the changes in both quartic and sextic centrifugal distortion constants and, for ?24, values for the l-doubling constants q+ and q-. Theoretical calculations of the rovibrational parameters aided in the analysis and the numerical values are in good agreement with experimental results.

Nibler, Joseph W.↗