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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) peak intensity normalization for complex mixture analyses

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a preferred technique for analyzing complex organic mixtures. Currently, there is no consensus normalization approach, nor an objective method for selecting one, for quantitative analyses of FT-ICR-MS data. We investigate a method to evaluate and score the amount of bias various normalization approaches introduce into the data. We evaluate the ability of the Statistical Procedure for the Analysis of Normalization Strategies (SPANS) to guide selection of appropriate normalization approaches for two different FT-ICR-MS datasets. Further, we test the robustness of SPANS results to changes in SPANS parameter values and assess the impact of using various normalization approaches on downstream statistical analyses. The normalization approach identified by SPANS differed for the two datasets. Normalization methods impacted the statistical significance of peaks differently, underscoring the importance of carefully evaluating potential methods. More consistent SPANS scores resulted when at least 120 significant peaks are used, where larger sets of peaks were obtained by increasing the p-value threshold. Interestingly, we show that Total Sum Scaling and highest peak normalization, used in previous studies, underperformed relative to SPANS-recommended normalization approaches. While there is no single, best normalization method for all datasets, SPANS provides a mechanism to identify an appropriate normalization method for analyzing FT-ICR-MS data quantitatively. As a result, the number of peaks used in the background distributions of SPANS contributes more significantly to the reproducibility of results than the p-value thresholds used to obtain those peaks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A physical method for downscaling land surface temperatures using surface energy balance theory

Fine-resolution land surface temperature (LST) derived from thermal infrared remote sensing images is a good indicator of surface water status and plays an essential role in the exchange of energy and water between land and atmosphere. A physical surface energy balance (SEB)-based LST downscaling method (DTsEB) is developed to downscale coarse remotely sensed thermal infrared LST products with fine-resolution visible and near-infrared data. Here, the DTsEB method is advantageous for its ability to mechanically interrelate surface variables contributing to the spatial variation of LST, to quantitatively weigh the contributions of each related variable within a physical framework, and to efficaciously avoid the subjective selection of scaling factors and the establishment of statistical regression relationships. The applicability of the DTsEB method was tested by downscaling 12 scenes of 990 m Moderate Resolution Imaging Spectroradiometer (MODIS) and aggregated Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST products to 90 m resolution at six overpass times between 2005 and 2015 over three 9.9 km by 9.9 km cropland (mixed by grass, tree, and built-up land) study areas. Three typical LST downscaling methods, namely the widely applied TsHARP, the later developed least median square regression downscaling (LMS) and the geographically weighted regression (GWR), were introduced for intercomparison. The results showed that the DTsEB method could more effectively reconstruct the subpixel spatial variations in LST within the coarse-resolution pixels and achieve a better downscaling accuracy than the TsHARP, LMS and GWR methods. The DTsEB method yielded, on average, root mean square errors (RMSEs) of 2.01 K and 1.42 K when applied to the MODIS datasets and aggregated ASTER datasets, respectively, which were lower than those obtained with the TsHARP method, with average RMSEs of 2.41 K and 1.71 K, the LMS method, with average RMSEs of 2.35 K and 1.63 K, and the GWR method, with average RMSEs of 2.38 K and 1.64 K, respectively. The contributions of the related surface variables to the subpixel spatial variation in the LST varied both spatially and temporally and were different from each other. In summary, the DTsEB method was demonstrated to outperform the TsHARP, LMS, and GWR methods and could be used as a good alternative for downscaling LST products from coarse to fine resolution with high robustness and accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2022

Cool circumgalactic gas in galaxy clusters: connecting the DESI legacy imaging survey and SDSS DR16 Mg ιι absorbers

Herein we investigate the cool gas absorption in galaxy clusters by cross-correlating Mg II absorbers detected in quasar spectra from data release 16 of the Sloan Digital Sky Survey (SDSS) with galaxy clusters identified in the Dark Energy Spectroscopic Instrument (DESI) survey. We find significant covering fractions (⁠1–5percent within r 500 , depending on the chosen redshift interval), ~4–5 times higher than around random sightlines. While the covering fraction of cool gas in clusters decreases with increasing mass of the central galaxy, the total Mg II mass within r 500 is none the less ~10 times higher than for SDSS luminous red galaxies. The Mg II covering fraction versus impact parameter is well described by a power law in the inner regions and an exponential function at larger distances. The characteristic scale of the transition between these two regimes is smaller for large equivalent width absorbers. Cross-correlating Mg II absorption with photo–z selected cluster member galaxies from DESI reveals a statistically significant connection. The median projected distance between Mg II absorbers and the nearest cluster member is ~200 kpc, compared to ~500 kpc in random mocks with the same galaxy density profiles. We do not find a correlation between Mg II strength and the star formation rate of the closest cluster neighbour. This suggests that cool gas in clusters, as traced by Mg II absorption, is: (i) associated with satellite galaxies, (ii) dominated by cold gas clouds in the intracluster medium, rather than by the interstellar medium of galaxies, and (iii) may originate in part from gas stripped from these cluster satellites in the past.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Search for a light sterile neutrino with 7.5 years of IceCube DeepCore data

We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements |U μ⁢4 | 2 < 0.0534 and |U $\tau$⁢4 | 2 < 0.0574 at 90% CL under the assumption that Δ⁢m$^{2}_{41}$ ≥ 1 eV 2 . These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the 3+1 sterile neutrino landscape.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Improved precision in As speciation analysis with HERFD-XANES at the As K -edge: the case of As speciation in mine waste

High-energy-resolution fluorescence-detected (HERFD) X-ray absorption near-edge spectroscopy (XANES) is a spectroscopic method that allows for increased spectral feature resolution, and greater selectivity to decrease complex matrix effects compared with conventional XANES. XANES is an ideal tool for speciation of elements in solid-phase environmental samples. Accurate speciation of As in mine waste materials is important for understanding the mobility and toxicity of As in near-surface environments. In this study, linear combination fitting (LCF) was performed on synthetic spectra generated from mixtures of eight measured reference compounds for both HERFD-XANES and transmission-detected XANES to evaluate the improvement in quantitative speciation with HERFD-XANES spectra. The reference compounds arsenolite (As 2 O 3 ), orpiment (As 2 S 3 ), getchellite (AsSbS 3 ), arsenopyrite (FeAsS), kaňkite (FeAsO 4 ·3.5H 2 O), scorodite (FeAsO 4 ·2H 2 O), sodium arsenate (Na 3 AsO 4 ), and realgar (As 4 S 4 ) were selected for their importance in mine waste systems. Statistical methods of principal component analysis and target transformation were employed to determine whether HERFD improves identification of the components in a dataset of mixtures of reference compounds. LCF was performed on HERFD- and total fluorescence yield (TFY)-XANES spectra collected from mine waste samples. Arsenopyrite, arsenolite, orpiment, and sodium arsenate were more accurately identified in the synthetic HERFD-XANES spectra compared with the transmission-XANES spectra. In mine waste samples containing arsenopyrite and either scorodite or kaňkite, LCF with HERFD-XANES measurements resulted in fits with smaller R -factors than concurrently collected TFY measurements. The improved accuracy of HERFD-XANES analysis may provide enhanced delineation of As phases controlling biogeochemical reactions in mine wastes, contaminated soils, and remediation systems.

58 GEOSCIENCES↗
DOE OSTI2019

Final Report for Industrial Base Cybersecurity Initiative (IBCI) Project (FY2019)

Information security issues impact all manufacturing sectors and are particularly troublesome when designs for advanced weapons systems are lost via attacks that propagate through the relatively unprotected lower tiers of the nation's supply chains. The US Manufacturing Industrial Base (MIB) consists of suppliers and distributors that range in size from large prime contractors with extensive cybersecurity resources to small shops with little or no in-house information technology capabilities. The acquisition and maintenance of the technologies, systems, and financial resources needed to assure secure collaborations can be an overwhelming challenge for many manufacturers yet the cost of poor cybersecurity practices can lead to the compromise of national security information worth hundreds of millions of dollars. The Department of Defense Manufacturing Industrial Base Policy organization and the Department of Energy, Energy Efficiency and Renewable Energy Advanced Manufacturing Office have chartered the Los Alamos National Laboratory (LANL) and the Oak Ridge Y-12 National Security Complex (Y-12) to design, develop, and demonstrate a Manufacturing Threat Evaluation Wargaming System (MTEWS). The MTEWS concept is based on the use of a virtual model of the computer networks and cybersecurity protocols used across the MIB that will be continuously updated to reflect the dynamic threat environment. The MTEWS cyber-physical test range will demonstrate a prototype wargaming system that analyzes the impact of new and existing cybersecurity threats while also providing the information needed to sustain the integrity of the MIB supply chains. A long-term goal is the establishment of an enduring national manufacturing operations center that proactively responds to the continuously changing attacks that threaten the MIB and US national security. LANL and Y-12 have formed an Industrial Base Cybersecurity Initiative Team (IBCI), consisting of partners from the public, private and academic sectors, that is developing the MTEWS. To date, most of the project tasks have been centered on the technologies required to create a representative model of the MIB because this is a foundational element for the entire project. Modeling activities at the University of North Carolina at Charlotte (UNC Charlotte) have demonstrated a VMware-based prototype system that can accommodate a network model with up to 350 nodes and includes features such as the option to incorporate network scanning information when building the model and the ability to down select the elements of duplicative networks to a statistically significant subset that avoids redundantly duplicating network configurations. Broad Ordering Agreements have been established with UNC Charlotte and the University of West Florida (UWF) that support a variety of cybersecurity for manufacturing tasks and wide-spread endorsement has been received from government, industry and academia sectors concerning the IBCI goals and technical direction.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Understanding Biases in Sample Preparation Techniques for Coupled Scanning Electron Microscopy and MAMA PuO 2 Morphological Analysis

In this project, the scanning electron microscopy (SEM) sampling method used during the statistical design study (SDS) was investigated to determine if any sampling biases were present in the analyzed data. Using standard particle size distribution powders from the National Institute of Standards and Technology (NIST 1984 standard reference material) with the origin wet dispersion method, it was determined that a bias to smaller particles was present. This was supported by theoretical calculations using Stokes’ law to determine the settling rate of spherical particles of roughly the same size and mass as those found in the SDS. Based on the theoretical calculations, it was determined that the settling rate for each of the 76 powder sets in the SDS could be unique based on specific particle shape and mass distributions, making a universal correction factor/formula not applicable. Therefore, priority shifted to developing an improved wet dispersion method that significantly reduced the particle settling rate for all particle size and shapes. This was achieved by replacing the original solvent (isopropyl alcohol) with a heavy liquid (lithium heteropolytungstates), which dramatically slowed the settling rate and allowed for the capture of a suitable homogeneous aliquot. SEM imaging and Morphological Analysis for Material Attribution (MAMA) software analysis were conducted on the NIST standard, and the SEM/MAMA data were compared to data captured by a dynamic image analysis particle size analyzer. The resulting data confirmed that the new wet dispersion method does indeed deliver an improved representative aliquot to the SEM stub. For instance, in the NIST certificate, the average particle size is ~17.1 µm ± 2.2 µm with a normal distribution. The initial wet dispersion method resulted in a drastically reduced average particle size of 6.1 µm in addition to a non-representative heavy bi-modal distribution whereas the improved LST wet dispersion method resulting in an average particle size that was much closer to the NIST certificate (12.7 µm) with a similar normal distribution. Although the improved method was still short of the NIST certificate average, atomic force microscopy analysis determined that the resulting ~20-25% reduction in size was due to particles sinking into the carbon sticky tape used for SEM imaging. It is believed that that this bias can be calibrated in a much more predicable manner than the original settling rate bias. In addition, the matching normal distribution curves between the NIST certificate and the heavy liquid method indicate a much-improved representative aliquot has been sampled and imaged. A surrogate CeO 2 powder was used to reflect PuO 2 more accurately and to aid in implementing radiological controls and shielding. The resulting data sets from the SEM/MAMA method and the particle size analyzer give almost identical average particle sizes and particle distribution statistics. Future work will re-analyze several select runs from the SDS to determine if morphological signatures can be found with the improved sampling method.

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

Optimizing the combustion synthesis of FeAlxOy catalysts for microwave-assisted thermocatalytic dehydrogenation of fossil fuels

The growing demand for hydrogen requires the development of clean and energy-efficient technologies for its synthesis. Microwave-assisted thermocatalytic dehydrogenation of fossil fuels has demonstrated the potential to produce H2 with high yield and selectivity, and simultaneously generate valuable nanostructured carbon byproducts. In prior work, iron-based alumina (FeAlxOy) catalysts for this process were made via solution combustion synthesis (SCS). However, the effect of SCS parameters on the dehydrogenation performance is not well understood. The present study investigates this by varying the SCS fuel, Fe:Al molar ratio, and heating mode. The results show subtle changes of these parameters can result in significant differences in the phase composition, specific surface area, and microwave absorbing properties of FeAlxOy, which all affect microwave-assisted dehydrogenation. Notably, H2 selectivity can be increased from 30% to 74%. Statistical testing determined that the SCS fuel used was the most significant SCS parameter affecting dehydrogenation performance.

Chanoi, Zachary A.↗
DOE OSTI2018

Geometry tagging for heavy ions at JLEIC

Geometry tagging is an experimental analysis technique for selecting event samples where one can, on a statistical basis, control the geometry of the collision in order to make more incisive physics measurements. Several physics measurements at the EIC would benefit significantly from the use of this technique, including studies of gluon anti-shadowing, studies of parton propagation, attenuation and hadronization in the nucleus, and ultimately the search for parton saturation. The JLEIC full-acceptance detector, with full acceptance to forward-going neutrons, protons and nuclear fragments and a high data-taking rate is ideally suited to such geometry tagging. We improve, tune, and apply existing modeling codes, BeAGLE, Sartre, and GEMC, and detector descriptions to study this physics.

Morozov, Vasiliy↗
DOE OSTI2025

One Galaxy Sample to Rule Them All: Halo Occupation Distribution Modeling of DES Year 3 Source Galaxies

Abstract For the joint analysis of second-order weak-lensing and galaxy clustering statistics, so-called 3 × 2 analyses, the selection and characterization of optimal galaxy samples is a major area of research. One promising choice is to use the same galaxy sample as lenses and sources, which reduces the systematics parameter space that describes the uncertainties related to galaxy samples. Such a “lens-equal-source” analysis significantly improves the self-calibration of photo- z systematics, leading to improved cosmological constraints. With the aim of enabling a lens-equal-source analysis on small scales, we investigate the halo–galaxy connection of DES Year 3 source galaxies. We develop a technique to construct mock source galaxy populations by matching COSMOS/UltraVISTA photometry to U niverse M achine galaxies. These mocks predict a source halo occupation distribution (HOD) that exhibits significant redshift evolution, nontrivial central incompleteness, and galaxy assembly bias. We produce multiple realizations of mock source galaxies drawn from the U niverse M achine posterior, with added uncertainties in the measured Dark Energy Survey photometry and galaxy shapes. We fit a modified HOD formalism to these realizations to produce priors on the galaxy–halo connection for cosmological analyses. We additionally train an emulator that predicts this HOD to ∼2% accuracy from redshift z = 0.1−1.3 that models the dependence of this HOD on (1) observational uncertainties in galaxy size and photometry and (2) uncertainties in the U niverse M achine predictions.

Salcedo, Andrés N. (ORCID:000000031420527X)↗
DOE OSTI2023

The Chocolate Chip Cookie Model: Dust-to-metal Ratio of H ii Regions

Using a sample of face-on star-forming galaxies selected from the Sloan Digital Sky Survey, we statistically derive the typical optical depth $\tau$ cl of individual H II regions based on the "Chocolate Chip Cookie" model of Lu et al. (2022). By binning galaxies into stellar mass and gas-phase metallicity bins and interpreting $\tau$ cl as the dust-to-gas ratio (DGR) of H II regions, we further investigate the correlations between DGR and stellar mass and between DGR and gas-phase metallicity, respectively. We find that DGR increases monotonically with the stellar mass of galaxies. At a given stellar mass, DGR shows a linear correlation with the gas-phase metallicity, which implies a constant dust-to-metal ratio (DTM) of galaxies at a given stellar mass. These results adequately indicate that the DTM of galaxies is simply a function of their stellar masses. In terms of gas-phase metallicity, because of the mass–metallicity relation, DTM increases with increasing metallicity with a power-law index 1.45 in the low-metallicity region, while it remains constant at the high-metallicity end.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Evaluation of electroexplosive devices by nondestructive test techniques and impulsive waveform firings

Special requirements of the space industry for more detailed knowledge of the quality and reliability of each electroexplosive device (EED) selected for use aboard a spacecraft are described. Statistical methods do not practically demonstrate the high reliability needed. To close this gap, nondestructive test techniques and instrumentation for 1-W/1-A no-fire devices have been developed. Several lots of squibs have been evaluated using these techniques and instrumentation. They yield data as to the quality and normal behavior of each electroexplosive device without firing or degrading the unit. Performance data were obtained by initiating the EED's with an impulsive waveform and sensing the initiation characteristics, sensitivity, and output.

Menichelli, V. J.↗
NASA NTRS1973

Reflectance of vegetation, soil, and water

The author has identified the following significant results. The ability to read the 24-channel MSS CCT tapes, select specified agricultural land use areas from the CCT, and perform multivariate statistical and pattern recognition analyses has been demonstrated. The 5 optimum channels chosen for classifying an agricultural scene were, in the order of their selection the far red visible, short reflective IR, visible blue, thermal infrared, and ultraviolet portions of the electromagnetic spectrum, respectively. Although chosen by a training set containing only vegetal categories, the optimum 4 channels discriminated pavement, water, bare soil, and building roofs, as well as the vegetal categories. Among the vegetal categories, sugar cane and cotton had distinctive signatures that distinguished them from grass and citrus. Acreages estimated spectrally by the computer for the test scene were acceptably close to acreages estimated from aerial photographs for cotton, sugar cane, and water. Many nonfarmable land resolution elements representing drainage ditch, field road, and highway right-of-way as well as farm headquarters area fell into the grass, bare soil plus weeds, and citrus categories and lessened the accuracy of the farmable acreage estimates in these categories. The expertise developed using the 24-channel data will be applied to the ERTS-1 data.

Wiegand, C. L.↗
NASA NTRS1974

ASTEP user's guide and software documentation

The Algorithm Simulation Test and Evaluation Program (ASTEP) is a modular computer program developed for the purpose of testing and evaluating methods of processing remotely sensed multispectral scanner earth resources data. ASTEP is written in FORTRAND V on the UNIVAC 1110 under the EXEC 8 operating system and may be operated in either a batch or interactive mode. The program currently contains over one hundred subroutines consisting of data classification and display algorithms, statistical analysis algorithms, utility support routines, and feature selection capability. The current program can accept data in LARSC1, LARSC2, ERTS, and Universal formats, and can output processed image or data tapes in Universal format.

Gliniewicz, A. S.↗
NASA NTRS1976

An evaluation of grease ball bearing lubricants in vacuum

Because many future spacecraft will require mechanisms to operate for long periods of time in environments which are inimical to most bearing lubricants, a series of tests has been started to evaluate 25 grease type lubricants in R-4 size bearings in vacuum at ambient temperature for a 1 year period. Four repetitions of each test are made to provide statistical samples. These tests will be used to select from two to five lubricants for 5 year tests in the same environment. At the present time fifteen test sets have been completed and five sets are being tested. The best results to date have been obtained with perfluoropolyether greases.

Demorest, K. E.↗
NASA NTRS1976

An evaluation of grease type ball bearing lubricants operating in various environments /Status report no. 2/

Because many future spacecraft or space stations will require mechanisms to operate for long periods of time in environments which are inimical to most bearing lubricants, a series of tests has been started to evaluate 25 grease type lubricants in R-4 size bearings in five different environments for a 1 year period. Four repetitions of each test are made to provide statistical samples. These tests will be used to select from two to five lubricants for 5 year tests in the same environments. At the present time, approximately 30 test sets have been completed and 25 sets are underway. To date, best results in all environments have been obtained with a high viscosity index perfluoropolyether grease.

Demorest, K. E.↗