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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Determining tolerance requirements for spray-duct alignment in ducted fuel injection

Several ducted fuel injection (DFI) studies have highlighted the importance of accuracy in aligning the duct axis with that of its corresponding spray for optimal effectiveness, as misalignment adversely impacts the method’s performance. The need for accurate alignment could lead to added manufacturing complexity via tighter tolerances. This study systematically explores cases of horizontal, vertical, and rotational misalignment, analyzing their respective effects on DFI performance. Vertical and horizontal misalignments at the duct inlet plane were varied at magnitudes of 6.25%, 12.5%, and 25.0% of the duct diameter, corresponding to 0.125, 0.25, and 0.5 mm, respectively. Rotational misalignments were set at 1°, 2°, and 4°, corresponding to 3.65%, 7.30%, and 14.6%, respectively, of the duct diameter at its inlet plane. The investigation yields spray-duct alignment tolerance limits and highlights the influence of misalignment direction on emissions due to the interactions with swirl and squish inside the combustion chamber. The results indicate that the tolerance limits for the alignment are within 4° and 0.5 mm relative to the geometrically aligned position. If the misalignment exceeds 4°of rotation or 0.5 mm in the horizontal direction, the beneficial effects on soot reduction using this method are no longer observed. The findings contribute to an understanding that can be used to optimize DFI for cleaner and more efficient combustion in compression-ignition engines.

Şener, Ramazan↗
DOE OSTI2015

Efficient calibration for imperfect computer models

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The in vivo structure of biological membranes and evidence for lipid domains

Examining the fundamental structure and processes of living cells at the nanoscale poses a unique analytical challenge, as cells are dynamic, chemically diverse, and fragile. A case in point is the cell membrane, which is too small to be seen directly with optical microscopy and provides little observational contrast for other methods. As a consequence, nanoscale characterization of the membrane has been performed ex vivo or in the presence of exogenous labels used to enhance contrast and impart specificity. Here, we introduce an isotopic labeling strategy in the gram-positive bacterium Bacillus subtilis to investigate the nanoscale structure and organization of its plasma membrane in vivo. Through genetic and chemical manipulation of the organism, we labeled the cell and its membrane independently with specific amounts of hydrogen (H) and deuterium (D). These isotopes have different neutron scattering properties without altering the chemical composition of the cells. From neutron scattering spectra, we confirmed that the B. subtilis cell membrane is lamellar and determined that its average hydrophobic thickness is 24.3 ± 0.9 Ångstroms (Å). Furthermore, by creating neutron contrast within the plane of the membrane using a mixture of H- and D-fatty acids, we detected lateral features smaller than 40 nm that are consistent with the notion of lipid rafts. These experiments—performed under biologically relevant conditions—answer long-standing questions in membrane biology and illustrate a fundamentally new approach for systematic in vivo investigations of cell membrane structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Multimodal Event Catalog and Waveform Data Set That Supports Explosion Monitoring from Nevada, U.S.A.

Multimodal, curated data sets and nuisance event catalogs remain rare in the explosion monitoring community relative to curated seismic data sets. The source of this relative absence is the difficultly in deploying multimodal receivers that sense the seismic, acoustic, and other modalities from multiphysics sources. We provide such a data set in this study that delivers seismic, infrasound, and electromagnetic (magnetometer) sensor records collected over a two–week period, within 255 km of a 10 ton buried chemical explosion called DAG–4 that was located at 37.1146°, –116.0693° on 22 June 2019 21:06:19.88 UTC. This catalog includes 485 seismic, seismoacoustic, and infrasound–only events that an expert analyst manually built by reviewing waveforms from 29 seismic and infrasound sensors. Our data release includes waveforms from these 29 seismic, infrasound, and seismoacoustic stations and two magnetometer stations and their station metadata. We deliver these waveforms in NNSA KB Core CSS.w format (i4) with a corresponding wfdisc table that provides the header information. Here, we expect that this data set will provide a valuable, benchmark resource to develop signal processing algorithms and explosion monitoring methods against manual, human observations.

58 GEOSCIENCES↗
DOE OSTI2024

Seismic Monitoring near Ithaca, New York, Reveals Nonuniform Distribution of Microseismicity in an Intraplate Region

Abstract Cornell University intends to use a deep direct-use geothermal system to heat its Ithaca, New York, campus. In preparation for this project, the Cornell Seismic Network has been monitoring the background seismicity in this intraplate region since 2019. From January 2020 to June 2023, 95 events were detected within 20 km of the proposed geothermal well site, with local magnitudes ranging from −1.02 to 0.56. None of these events appear in regional or national catalogs. Events locate in a narrow geographic band, with one-fourth exhibiting multimodal hypocentral probability peaks both near the surface and at 1–4 km depth. We relocate events with a joint hypocenter and 1D velocity model inversion, in addition to a fully nonlinear method, and then compare observations with synthetic waveforms. Together, these approaches provide strong evidence for >95% of events locating at the surface or within the 3-km-thick sedimentary sequence. We explore how anthropogenic activity and regional topographic stress may contribute to frequent surficial events. This information is critical for characterizing the background microseismicity for comparison during future geothermal operations. Ithaca’s geology of Paleozoic sediments overlying Precambrian crystalline basement is typical of many continental interiors, so these results also provide insight into intraplate microseismicity patterns.

Geochemistry & Geophysics↗
DOE OSTI2014

Creating Optimal Fracture Networks

The primary goal of this project is the development of a multi-physics, multi-scale simulation capability to predict the initiation, propagation and maintenance of hydraulically driven fracture networks in heterogeneous geologic materials. The development and validation of integrated code capability, GEOS, that accurately captures the phenomenology of these complex physical processes across a wide range of time-­ (~10 -6 to ~10 8 s) and length- (~10 -3 to ~10 4 m) scales is the main scientific objective of the proposed initiative. GEOS constitutes a new analytical framework incorporating the underlying physics that drives fracture development – e.g. dynamically changing fracture network topologies, fluid/solid interactions taking place along discrete interfaces, and complex matrix/fracture transport processes. Enhanced seismic observational tools and inversion methods will also be developed. This initiative has positioned LLNL to play a leading role in the development of Enhanced Geothermal Systems, unconventional gas energy resources, risk assessment associated with geologic sequestration of CO 2 and the detection of radioactive gases from clandestine nuclear tests, impacting both energy and national security.

02 PETROLEUM↗
DOE OSTI2016

Improving the representation of soluble iron in climate models

Funding from this grant supported Rachel Sanza, Yan Zhang and partially Samuel Albani. Substantial progress has been made on inclusion of mineralogy, showing the quality of the simulations, and the impact on radiation in the CAM4 and CAM5 (Scanza et al., 2015). In addition, the elemental distribution has been evaluated (and partially supported by this grant) (Zhang et al., 2015), showing that using spatial distributions of mineralogy, improved resperentation of Fe, Ca and Al are possible, compared to the limited available data. A new intermediate complexity soluble iron scheme was implemented in the Bulk Aerosol Model (BAM), which was completed as part of Rachel Scanza’s PhD thesis. Currently Rachel is writing up at least two first author papers describing the general methods and comparison to observations (Scanza et al., in prep.), as well as papers describing the sensitivity to preindustrial conditions and interannual variability. This work lead to the lead PI being asked to write a commentary in Nature (Mahowald, 2013) and two review papers (Mahowald et al., 2014, Mahowald et al., submitted) and contributed to related papers (Albani et al., 2016, Albani et al., 2014, Albani et al., 2015).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Peridynamic Theory as a New Paradigm for Multiscale Modeling of Sintering

Sintering is a component fabrication process in which powder is compacted by pressing or some other means and then held at elevated temperature for a period of hours. The powder grains bond with each other, leading to the formation of a solid component with much lower porosity, and therefore higher density and higher strength, than the original powder compact. In this project, we investigated a new way of computationally modeling sintering at the length scale of grains. The model uses a high-fidelity, three-dimensional representation with a few hundred nodes per grain. The numerical model solves the peridynamic equations, in which nonlocal forces allow representation of the attraction, adhesion, and mass diffusion between grains. The deformation of the grains is represented through a viscoelastic material model. The project successfully demonstrated the use of this method to reproduce experimentally observed features of material behavior in sintering, including densification, the evolution of microstructure, and the occurrence of random defects in the sintered solid.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Feasibility of Using Radar for Characterizing and Tracking Plumes

With the enhanced capabilities of NEXRAD radars has come an increased body of research focused on non-weather artifacts in the radar signal. Radar data has been collected and evaluated for a range of plume-generating events. Events such as wildfires, measuring and tracking ash from volcanic eruptions, and tracking plumes from events such as the SpaceX rocket explosion in 2016 have been investigated to determine the useful measurements available in radar data. For decision makers interested in radar use in nuclear forensics or during an emergency response, the usefulness of radar for attempting to provide some answers early in an event is clear. Currently emplaced operational radars provide high spatial and temporal resolution data within minutes of an event. This is not to say radar observations would replace current methods used by decision makers; however, supplementing decision making with radar data can only enhance and better inform the decision process. This report builds on two previous reports submitted in November 2016 and May 2017. This feasibility study demonstrates that radar can be used to improve decision making in the early phases of a plume-generating event by decreasing uncertainty as well as improving source-term inputs in F&T models. Radar coverage exists today in capabilities such as NOAA’s NEXRAD weather surveillance radars and Terminal Doppler Weather Radars. Improvement could be realized quickly by (1) improving awareness of existing radar products and incorporating them into decision making and modeling efforts, (2) evaluating and improving radar coverage around key urban areas and critical infrastructure, and (3) improving radar algorithms to optimize for non-meteorological events such as plumes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Structural Studies of Amorphous Materials by Fluctuation Electron Microscopy

Fluctuation Electron Microscopy (FEM) is a technique that examines the fluctuations in electron scattering across a uniformly thin amorphous sample. The statistics of the intensity fluctuations, mean and variance, reveal any underlying medium-range order present in the structure. The goals of this project were: (1) To determine the fundamentals of the scattering physics that gives rise to the variance signal in fluctuation electron microscopy (FEM); (2) To use these discoveries to find ways to quantify FEM; (3) To apply the FEM method to interesting and technologically important families of amorphous materials, particularly those with important applications in energy-related processes. Excellent progress was made in items (1) and (2). In stage (3) we did not examine the metamict zircons, as proposed. Instead, we examined films of polycrystalline and amorphous semi-conducting diamond. Significant accomplishments are: (1) A Reverse Monte Carlo procedure was successfully implemented to invert FEM data into a structural model. This is computer-intensive, but it demonstrated that diffraction and FEM data from amorphous silicon are most consistent with a paracrystallite model. This means that there is more diamond-like topology present in amorphous silicon than is predicted by the continuous random network model. (2) There is significant displacement decoherence arising in diffraction from amorphous silicon and carbon. The samples are being bombarded by the electron beam and atoms do not stay still while being irradiated – much more than was formerly understood. The atom motions cause the destructive and constructive interferences in the diffraction pattern to fluctuate with time, and it is the time-averaged speckle that is being measured. The variance is reduced by a factor m, 4 ≤ m ≤ 1000, relative to that predicted by kinematical scattering theory. (3) Speckle intensity obeys a gamma distribution, where the mean intensity $ \overline{I}\ $ and m are the two parameters governing the shape of the gamma distribution profile. m is determined by the illumination spatial coherence, which is normally very high, and mostly by the displacement decoherence within the sample. (4) Amorphous materials are more affected by the electron beam than are crystalline materials. Different samples exhibit different disruptibility, as measured by the effective values of m that fit the data. (5) Understanding the origin of the displacement decoherence better should lead to efficient methods for computing the observed variance from amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

DeepMerge: Studying Distant Merging Galaxies with Deep Neural Networks

The hierarchical merging of galaxies is a probe of the cosmos to test the canonical ?CDM cosmology paradigm. A particularly interesting period is "cosmic high noon" at redshifts z? 2?3, during which star formation rates were the highest, and significant amounts of stellar mass assembled into galaxy-scale bodies. Detecting galaxy mergers in observations by conventional automated methods (which use extracted parameters of galaxy structure - asymmetry, clumpiness, concentration etc.) or by visual inspection has proven to be quite time-consuming and prone to errors. Convolutional Neural Network (CNNs) are a primary representative of deep learning algorithms which are used in computer vision tasks by training to detect features in images. CNNs were already used for classification of low-redshift merging galaxies [1, 2]. Here we will use CNN to to learn directly from images (without the need to extract morphology parameters) of distant merging galaxies in order to distinguish between merging and non-merging objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Irradiation of Mo-100 Targets and Testing Fe(ll)CI 2 Precipitation for Tc-99 Removal

The production of molybdenum-99 (Mo-99) is a critical step in the generation of technetium-99m (Tc-99m), a radioisotope widely used in medical imaging. NorthStar Medical Radioisotopes, LLC is planning to produce the important medical radioisotope Mo-99 through a photonuclear reaction on molybdenum-100 (Mo-100). Accelerator production of Mo-99 using enriched Mo-100 targets yields undesirable isotopes, such as niobium-95 (Nb-95) and zirconium-95 (Zr-95). Previous studies reported that Nb and Zr isotopes can be effectively removed from Mo-99 products through coprecipitation with Fe(III). To enable the potential utilization of the first milking of Tc-99m from a Mo-99/Tc-99m generator, it is desirable to remove long-lived Tc-99. This can be accomplished by substituting Fe(III) with Fe(II) during the precipitation step, without affecting the removal of Zr and Nb isotopes. Previous experiments demonstrated up to 99+% removal of Tc using this method. It was also observed that the presence of hydrogen peroxide significantly impacts Tc removal. This was evident in the processing of enriched Mo-100 targets, where only 25% of Tc was removed. To further investigate this, another irradiation of enriched Mo-100 disks was conducted, followed by Tc-99 removal using Fe(II). Prior to irradiation, experimental conditions for Tc removal were optimized through several test runs using Mo-100 disks spiked with Tc-99. The results of these tests are discussed in this report.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Analysis of Deformation Mechanisms, Strain Localization, and Fracture in Highly Irradiated Austenitic Steels – Light-Water Reactor Core Materials – via Advanced inSEM Techniques

The present report describes the establishing of an advanced experimental approach – high-resolution digital image correlation or µDIC – for testing miniature irradiated specimens in the ORNL’s Low Activation Materials Development and Analysis (LAMDA) facility. As expected, the µDIC approach will allow for studying strain localization inside grains, for instance, during dislocation channel-grain boundary interaction processes. This information is of high importance for understanding degradation processes in irradiated austenitic steels – in-core materials of Light Water Reactors. The Level 4 report provides a brief introduction, lists materials designated for µDIC testing and delivered in LAMDA this FY, discusses methodical concerns and preliminary observations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Interactions between molecular-scale biogeochemical processes and hyporheic exchange for understanding coupled Fe-S-C cycling in iron-rich riparian wetlands (Final Technical Report)

Riparian wetlands are dynamic interfaces that exert strong control over water quality, contaminant mobility, and greenhouse gas emissions. These systems are characterized by hyporheic exchange between oxic surface water and anoxic groundwater, which generates steep redox gradients and promotes spatially and temporally variable microbial activity. Despite growing recognition of tightly coupled iron (Fe), sulfur (S), and carbon (C) cycling in these environments, the mechanisms governing these interactions—particularly under low-sulfate freshwater conditions—remain poorly constrained. This project developed a mechanistic understanding of how hydrologic variability and microbial processes interact to control Fe–S–C cycling in iron-rich riparian wetlands. Using a multi-scale and multi-method approach integrating field observations, geochemical and spectroscopic analyses, metagenomics, and reactive transport modeling, we demonstrate that “cryptic” sulfur cycling—rapid sulfur transformations involving intermediate-valence species—plays a dominant and previously underrecognized role in freshwater wetlands. These processes persist despite low sulfate concentrations and significantly influence iron reduction, carbon mineralization, and methane dynamics. The results show that cryptic sulfur cycling enhances dissolved Fe 2+ production, regulates methane concentrations, and is strongly controlled by climate-driven hydrologic fluxes. By linking hydroclimate, subsurface flow, and biogeochemical reactions, this work provides a predictive framework for understanding how wetland systems respond to environmental change, with direct implications for water quality and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertainty that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Global energetics of solar flares. III. Nonthermal energies

This study entails the third part of a global flare energetics project, in which Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) data of 191 M and X-class flare events from the first 3.5 years of the Solar Dynamics Observatory mission are analyzed. We fit a thermal and a nonthermal component to RHESSI spectra, yielding the temperature of the differential emission measure (DEM) tail, the nonthermal power-law slope and flux, and the thermal/nonthermal cross-over energy e {sub co}. From these parameters, we calculate the total nonthermal energy E {sub nt} in electrons with two different methods: (1) using the observed cross-over energy e {sub co} as low-energy cutoff, and (2) using the low-energy cutoff e {sub wt} predicted by the warm thick-target bremsstrahlung model of Kontar et al. Based on a mean temperature of T {sub e} = 8.6 MK in active regions, we find low-energy cutoff energies of e{sub wt}=6.2±1.6 keV for the warm-target model, which is significantly lower than the cross-over energies e{sub co}=21±6 keV. Comparing with the statistics of magnetically dissipated energies E {sub mag} and thermal energies E {sub th} from the two previous studies, we find the following mean (logarithmic) energy ratios with the warm-target model: E{sub nt}=0.41 E{sub mag}, E{sub th}=0.08 E{sub mag}, and E{sub th}=0.15 E{sub nt}. The total dissipated magnetic energy exceeds the thermal energy in 95% and the nonthermal energy in 71% of the flare events, which confirms that magnetic reconnection processes are sufficient to explain flare energies. The nonthermal energy exceeds the thermal energy in 85% of the events, which largely confirms the warm thick-target model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes

Atmospheric retrievals are essential tools for interpreting exoplanet transmission and eclipse spectra, enabling quantitative constraints on the chemical composition, aerosol properties, and thermal structure of planetary atmospheres. The James Webb Space Telescope (JWST) offers unprecedented spectral precision, resolution, and wavelength coverage, unlocking transformative insights into the formation, evolution, climate, and potential habitability of planetary systems. However, this opportunity is accompanied by challenges: modeling assumptions and unaccounted-for noise or signal sources can bias retrieval outcomes and their interpretation. To address these limitations, we introduce a Gaussian process (GP)-aided atmospheric retrieval framework that flexibly accounts for unmodeled features and correlated noise in exoplanet spectra. We validate this method on synthetic JWST observations, and show that GP-aided retrievals reduce bias in inferred abundances and better capture model–data mismatches than traditional approaches. We also introduce the concept of mean squared error to quantify the trade-off between bias and variance, arguing that this metric more accurately reflects retrieval performance than bias alone. We then reanalyze the NIRISS/SOSS JWST transmission spectrum of WASP-96 b, finding that GP-aided retrievals yield broader constraints on CO 2 and H 2 O, possibly alleviating tension between previous retrieval results and equilibrium predictions. Our GP framework provides precise and accurate constraints while highlighting regions where models fail to explain the data. As JWST matures and future facilities come online, a deeper understanding of the limitations of both data and models will be essential, and GP-enabled retrievals like the one presented here offer a principled path forward.

Rotman, Yoav [Arizona State Univ., Tempe, AZ (Unit↗