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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Can Restoring Tidal Wetlands Reduce Estuarine Nuisance Flooding of Coasts Under Future Sea‐Level Rise?

Wetland restoration is an increasingly popular nature‐based method for flood risk mitigation in coastal communities. In this study, we present a novel method using hydrodynamic modeling and harmonic analysis to quantify wetlands' ability to reduce future nuisance flooding. The method leverages a hydrodynamic model calibrated to present day data and was run for a range of future sea‐level rise (SLR) and wetland restoration scenarios to quantify changes to tidal harmonic amplitudes and phases. The harmonic constituents are used to generate water surface elevations over a time period of interest (e.g., one year) and compared to critical exceedance thresholds such as levee elevations. Then, changes to nuisance flooding are calculated by counting the number of hours critical thresholds are exceeded under different SLR and wetland restoration scenarios. We applied the method to Coos Bay, Oregon, USA as a test case. We found restoration reduces the number of hours nuisance flooding occurs in downtown Coos Bay from 15 hr (present day conditions) to 0 hr (fully restored condition) under median SLR (82 cm by 2100). Restoration had spatially variable impacts on reducing peak flood elevations with minimal impacts near the estuary mouth and greatest impact 32 km inland. The effectiveness of restoration was heavily dependent on future SLR. Restoration was maximally effective in 2050 under all SLR scenarios, less effective in 2100 under median SLR, and not effective under high SLR. Modeling results suggest increased tidal prism and accommodation space are driving restoration‐associated reductions in tidal amplitudes.

Brand, Matthew W. [Louisiana State Univ., Baton Ro↗
DOE OSTI2024

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗
DOE OSTI2023

Dynamics of episodic supershear in the 2023 M7.8 Kahramanmaraş/Pazarcik earthquake, revealed by near-field records and computational modeling

Abstract The 2023 M7.8 Kahramanmaraş/Pazarcik earthquake was larger and more destructive than what had been expected. Here we analyzed nearfield seismic records and developed a dynamic rupture model that reconciles different currently conflicting inversion results and reveals spatially non-uniform propagation speeds in this earthquake, with predominantly supershear speeds observed along the Narli fault and at the southwest (SW) end of the East Anatolian Fault (EAF). The model highlights the critical role of geometric complexity and heterogeneous frictional conditions in facilitating continued propagation and influencing rupture speed. We also constrained the conditions that allowed for the rupture to jump from the Narli fault to EAF and to generate the delayed backpropagating rupture towards the SW. Our findings have important implications for understanding earthquake hazards and guiding future response efforts and demonstrate the value of physics based dynamic modeling fused with near-field data in enhancing our understanding of earthquake mechanisms and improving risk assessment.

Environmental Sciences & Ecology↗
DOE OSTI2023

Feasibility of Correlated Extensive Air Shower Detection with a Distributed Cosmic-Ray Network

We explore the sensitivity offered by a global network of cosmic-ray detectors to a novel, unobserved phenomenon: widely separated simultaneous extended air showers. Existing localized observatories work independently to observe individual showers, offering insight into the source and nature of ultrahigh-energy cosmic rays. However no current observatory is large enough to provide sensitivity to anticipated processes such as the Gerasimova–Zatsepin effect or potential new physics that generate simultaneous air showers separated by hundreds to thousands of kilometers. A global network of consumer electronics (the Cosmic Rays Found In Smartphones (CRAYFIS) experiment), may provide a novel opportunity for observation of such phenomena. Two user scenarios are explored. In the first, with maximal user adoption, we find that statistically significant discoveries of spatially separated but coincident showers are possible within a couple years. In the second, more practical adoption model with 10 6 active devices, we find a worldwide CRAYFIS to be sensitive to novel "burst" phenomena where many simultaneous extensive air showers (EAS) occur at once.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Anti-Ultralocality and Plateau Models of Inflation

Anti-ultralocality refers to the growth of spatial gradient terms relative to velocity terms in the coupled Einstein--scalar field equations. It is a characteristic feature of decelerated expansion before the onset of inflation. Previous numerical relativity studies have shown that anti-ultralocality prevents the onset of inflation in models with power-law inflaton potentials. In this paper, we show that models with plateau-shaped inflaton potentials, which are considered to be the simplest way to generate a tensor-to-scalar ratio below current observational upper limits, are especially vulnerable to anti-ultralocality effects. The reasons are the flatness of the plateau and the energy density gap of $\sim 10$ orders of magnitude between the Planck density and the plateau potential energy. To study the problem, we develop a protocol for assessing the viability of inflationary models in general, and we apply it to a plateau potential using a previously validated numerical relativity code. We find that, starting from generic initial conditions, the growth of gradient terms in the Einstein equations relative to non-gradient terms either prevents inflation from lasting for enough $e$-folds or triggers a phase of quantum runaway. We show that the fine-tuning of initial conditions necessary to avoid these issues becomes more severe as the energy scale of inflation is made smaller, disfavoring common approaches for reducing the tensor-to-scalar ratio.

FOS: Physical sciences↗
DOE OSTI2024

End-of-Winter Snow Depth, Temperature, Density, and SWE Measurements at Teller Road Site, Seward Peninsula, Alaska, 2023

Measurements of end-of-winter snow properties were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) from March 31 to April 3, 2023. This dataset contains one *.pdf user guide and four *.csv data files of spatially distributed values of snow depth, snow water equivalent (SWE), snow temperature, and snow density. Snow temperature and snow density were collected throughout the snowpack at different depths. Data were collected toward the end of the winter season from late March to early April, when the snowpack is typically near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used to improve collection efficiency and enhance spatial coverage. This dataset is a continuation of the previous end-of-winter snow surveys conducted at the Teller Road Site in 2016-2018 (Wilson et al., 2020; https://doi.org/10.5440/1592103), 2019 (Bennett et al., 2021; https://doi.org/10.5440/1798170), and 2022 (Bennett et al., 2022; https://doi.org/10.5440/1887250).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Thematic Mapper Protoflight Model Line Spread Function

The Thematic Mapper (TM) Protoflight Model Spatial Line Spread Function (LSF) was not measured before launch. Therefore, methodology are developed to characterize LSF with protoflight model optics and electronics measurements that were made before launch. Direct prelaunch LSF measurements that were made from the flight model TM verified the protoflight TM LSF simulation. Results for two selected protoflight TM channels are presented here. It is shown that LSF data for the other ninety-four channels could be generated in the same fashion.

Schueler, C.↗
NASA NTRS1993

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗
NASA NTRS1993

Nonlinear unstable auroral-arc driven thermospheric winds in an ionosphere-magnetosphere coupled model

The nonlinear evolution of thermospheric winds in an ionosphere-magnetosphere coupled model has been studied for the first time for a dynamic unstable auroral-arc environment. We treat the problem using a multi-layer, quasi-three-dimensional model which averages in altitude the thermospheric dynamics over each layer. For the upper thermosphere, we find that (1) the thermosphere can respond to the ionospheric Kelvin-Helmholtz (KH) instability on temporal scales on the order of an hour, depending on ambient conditions, and on spatial scales of tens to hundreds of kilometers, (2) strong thermospheric meridional and zonal vortical flows with embedded nonlinear jet-like structures can be generated by the ionospheric/magnetospheric KH instability and (3) neutral thermospheric winds, vortices, and associated power spectra develop in a distinctly different manner in the presence of magnetospheric coupling effects. Comparison with recent observations is made.

Keskinen, M. J.↗
NASA NTRS2001

Combustion of Metals in Carbon Dioxide and Reduced-Gravity Environments

Ongoing exploration and future mission2001110444 s to Mars have given impetus to research on the use of natural resources of the planet. Since carbon dioxide (CO2) constitutes approximately 95% of the Mars atmosphere and since it reacts directly and vigorously with several metals, this investigation focuses on metal-CO2 reactions as a possible combination for rocket-propellant production and energy generation. Magnesium (Mg) has been initially selected as the metal fuel owing to its low ignition temperature and high specific impulse and burning rate in CO2. Our studies in this field started with low gravity (g) combustion tests of Mg in O2, CO2, and CO. Reduced gravity provided a clear picture of the burning phenomena by eliminating the intrusive buoyant flows in high-temperature metal reactions and by removing the destructive effect of gravity on the shape of molten metal samples. Suspended cylindrical metal samples of 2, 3, and 4-mm in diameter and length were radiatively ignited in low-g to generate free-floating samples exhibiting a spherically symmetric flame with increasing metal-oxide accumulation in an outer shell. For the Mg-CO2 combination, burning times twice as long as in normal-g and five times longer than in Mg-O2 flames were observed, revealing a diffusion-controlled reaction. The burning time is proportional to the square of the sample diameter. In tests conducted with pure CO, combustion was not possible without constant heating of the sample due to the formation of a thick carbon-containing coating around the Mg sample generated by surface reactions. The following work presents two new studies that attempt to explain some of the low-g experimental observations. First, a simplified one-dimensional, quasi-steady numerical model is developed to obtain temperature, species concentrations, and burning rates of the spherically symmetric diffusion flame around the Mg sample burning in O2 and CO2. Second, a Planar Laser Induced Fluorescence (PLIF) technique is implemented to provide spatially resolved measurements of magnesium oxide (MgO) in the reaction zone of Mg samples burning in O2 and CO2. These experiments reveal fundamental differences between the two combustion systems.

Branch, M. C.↗
NASA NTRS2006

General Flow-Solver Code for Turbomachinery Applications

Phantom is a computer code intended primarily for real-fluid turbomachinery problems. It is based on Corsair, an ideal-gas turbomachinery code, developed by the same authors, which evolved from the ROTOR codes from NASA Ames. Phantom is applicable to real and ideal fluids, both compressible and incompressible, flowing at subsonic, transonic, and supersonic speeds. It utilizes structured, overset, O- and H-type zonal grids to discretize flow fields and represent relative motions of components. Values on grid boundaries are updated at each time step by bilinear interpolation from adjacent grids. Inviscid fluxes are calculated to third-order spatial accuracy using Roe s scheme. Viscous fluxes are calculated using second-order-accurate central differences. The code is second-order accurate in time. Turbulence is represented by a modified Baldwin-Lomax algebraic model. The code offers two options for determining properties of fluids: One is based on equations of state, thermodynamic departure functions, and corresponding state principles. The other, which is more efficient, is based on splines generated from tables of properties of real fluids. Phantom currently contains fluid-property routines for water, hydrogen, oxygen, nitrogen, kerosene, methane, and carbon monoxide as well as ideal gases.

Dorney, Daniel↗
DOE OSTI2023

Modeling Wind-Hydrogen System and Analyzing Curtailment

Low-cost green hydrogen can be achieved by integrating utility-scale wind farms to an electrolyzer. The power produced by a wind farm depends on spatial and temporal changes in the wind, and this variability can affect the electrolyzer's performance. This study examines the trade-offs between two electrolyzer configurations: a large centralized electrolyzer connected to the wind farm versus several smaller distributed electrolyzers connected directly to each wind turbine. The results show that a centralized configuration generates more hydrogen because turbines that are waked and produce less power are compensated but other un-waked turbines.

electrolyzer↗
DOE OSTI2018

Studying biomineralization pathways in a 3D culture model of breast cancer microcalcifications

Microcalcifications serve as diagnostic markers for breast cancer, yet their formation pathway(s) and role in cancer progression are debated due in part to a lack of relevant 3D culture models that allow studying the extent of cellular regulation over mineralization. Previous studies have suggested processes ranging from dystrophic mineralization associated with cell death to bone-like mineral deposition. In this paper, we evaluated microcalcification formation in 3D multicellular spheroids, generated from non-malignant, pre-cancer, and invasive cell lines from the MCF10A human breast tumor progression series. The spheroids with greater malignancy potential developed necrotic cores, thus recapitulating spatially distinct viable and non-viable areas known to regulate cellular behavior in tumors in vivo. The spatial distribution of the microcalcifications, as well as their compositions, were characterized using nanoCT, electron-microscopy, and X-ray spectroscopy. Apatite microcalcifications were primarily detected within the viable cell regions and their number and size increased with malignancy potential of the spheroids. Levels of alkaline phosphatase decreased with malignancy potential, whereas levels of osteopontin increased. Finally, these findings support a mineralization pathway in which cancer cells induce mineralization in a manner that is linked to their malignancy potential, but that is distinct from physiological osteogenic mineralization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Spin-Dependent Thermoelectric Power of Nanoislands

The Seebeck effect explains the generation of electric voltage as a result of a temperature gradient. Its efficiency, defined as the ratio of the generated electric voltage to the temperature difference, is sensitive to local inhomogeneities that alter the scattering rate and the density of the conduction electrons. Spin-polarized Seebeck tunneling generates a distinct thermovoltage in spin-up and spin-down charge transport channels, which, as a key to spin caloritronics, focuses on transport phenomena related to spin and heat. Here, we report spatially resolved measurement of the spin-dependent thermovoltage in a tunneling junction formed by ferromagnetic Co nanoislands and a Ni tip using spin-dependent scanning tunneling thermovoltage microscopy (SP-STVthM). We resolve the nanoscale thermoelectric powers with respect to spin polarization, nanoisland size, stacking order of Co layers on a Cu substrate, and local sample heterogeneities. The observed thermally generated spin voltages are supported by first-principles and model calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Persistence of Spin Coherence in a Crystalline Environment

Here, we analyze quantum interference in the triplet-exciton pair generated by singlet exciton fission in a molecular crystal and introduce transport-induced dephasing (TID) as a key effect that can suppress the expected fluorescence quantum beats when the triplet-exciton wave function can localize on inequivalent sites. TID depends on the triplet-exciton hopping rate between inequivalent sites and on the energy shifts among the stationary states of the entangled triplet pair in different spatial configurations. The theoretical model is confirmed by experiments in rubrene single crystals, where triplet pairs remain entangled for more than 50 ns but quantum beats are suppressed by TID within a few nanoseconds when the magnetic field is misaligned by just a few degrees from specific symmetric directions. Our experiments deliver the zero-field parameters for the rubrene molecule in its orthorhombic lattice and information on triplet-exciton transport, in particular, the triplet-exciton hopping rate between inequivalent sites, which we evaluate to be of the order of 150 ps in rubrene.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Correlation-Aided Robust Decentralized Dynamic State Estimation of Power Systems with Unknown Control Inputs

This paper proposes a correlation-aided robust adaptive unscented Kalman filter for power system decentralized dynamic state estimation with unknown inputs, termed as robust AUKF-UI. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive (VAR) model in an adaptive manner. This VAR model is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. This allows taking into account the implicit cross-correlations between the states and the unknown inputs. As a result, the rank requirement for unknown input vector estimation is relaxed and the local generator frequency measurement is not required. The temporal correlations of time series innovation vectors, predicted state and input vectors are also leveraged by the robust AUKFUI to detect, identify and process bad data. Without these correlations, it is very challenging to address bad data with unknown inputs. Simulation results carried out on the IEEE 39-bus system demonstrate that the proposed robust AUKF-UI achieves much better results than other methods in the presence of low measurement redundancy, strong nonlinearity, and bad data.

Zhao, Junbo↗
DOE OSTI2020

Simulated JWST Data Sets for Multispectral and Hyperspectral Image Fusion

The James Webb Space Telescope (JWST) will provide multispectral and hyperspectral infrared images of a large number of astrophysical scenes. Multispectral images will have the highest angular resolution, while hyperspectral images (e.g., with integral field unit spectrometers) will provide the best spectral resolution. This paper aims at providing a comprehensive framework to generate an astrophysical scene and to simulate realistic hyperspectral and multispectral data acquired by two JWST instruments, namely, NIRCam Imager and NIRSpec IFU. We want to show that this simulation framework can be resorted to assess the benefits of fusing these images to recover an image of high spatial and spectral resolutions. To do so, we make a synthetic scene associated with a canonical infrared source, the Orion Bar. We develop forward models including corresponding noises for the two JWST instruments based on their physical features. JWST observations are then simulated by applying the forward models to the aforementioned synthetic scene. We test a dedicated fusion algorithm we developed on these simulated observations. We show that the fusion process reconstructs the high spatio-spectral resolution scene with a good accuracy on most areas, and we identify some limitations of the method to be tackled in future works. The synthetic scene and observations presented in the paper can be used, for instance, to evaluate instrument models, pipelines, or more sophisticated algorithms dedicated to JWST data analysis. Besides, fusion methods such as the one presented in this paper are shown to be promising tools to fully exploit the unprecedented capabilities of the JWST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. For this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

54 ENVIRONMENTAL SCIENCES↗