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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Measurement of the helicity asymmetry $${\mathbb {E}}$$ for the $$\vec {\gamma }\vec {p} \rightarrow p \pi ^0$$ reaction in the resonance region: The CLAS Collaboration

Abstract The double-spin-polarization observable $${\mathbb {E}}$$ E for $$\vec {\gamma }\vec {p}\rightarrow p\pi ^0$$ γ → p → → p π 0 has been measured with the CEBAF Large Acceptance Spectrometer (CLAS) at photon beam energies $$E_\gamma $$ E γ from 0.367 to $$2.173~\textrm{GeV}$$ 2.173 GeV (corresponding to center-of-mass energies from 1.240 to $$2.200~\textrm{GeV}$$ 2.200 GeV ) for pion center-of-mass angles, $$\cos \theta _{\pi ^0}^{c.m.}$$ cos θ π 0 c . m . , between $$-$$ - 0.86 and 0.82. These new CLAS measurements cover a broader energy range and have smaller uncertainties compared to previous CBELSA data and provide an important independent check on systematics. These measurements are compared to predictions as well as new global fits from The George Washington University, Mainz, and Bonn-Gatchina groups. Their inclusion in multipole analyses will allow us to refine our understanding of the single-pion production contribution to the Gerasimov-Drell-Hearn sum rule and improve the determination of resonance properties, which will be presented in a future publication.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

How initial conditions-, structural-, and parameter-based model uncertainty interact and influence predictions in permafrost ecosystems: Modeling Archive

This dataset contains model output and input data, as well as source code examples for the Terrestrial Ecosystem Model with the Dynamic Vegetation Model and Dynamic Organic Soil (DVM-DOS-TEM) for the field sites Imnavait creek and the Bonanza creek Long Term Ecological Research Network (LTER). The data covers simulations from the last glacial maximum (LGM) until 2100 for a selection of paleo scenarios, setting the mean temperature of the LGM up to 10°C lower than pre-industrial conditions. The model structure was modulated to represent various model versions, and this dataset contains the relevant changes in the source code. The raw output data, the processed statistical data, the setup and processing scripts as well as parameter value distribution files from a parameter sensitivity analysis are included as well. Model outputs include active layer depth, organic soil carbon, soil layer depths, gross primary productivity (GPP) with and without nitrogen limitation, net primary productivity (NPP), soil liquid water content, heterotrophic, maintenance, and growth respiration, soil temperature, and vegetation carbon (*.nc files). The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research.Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra: Modeling Archive

This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION↗
DOE OSTI2025

Direct Radiative Effects of Aerosols at the ARM SGP and TWP Sites (DOE ASR Final Report)

This effort has examined and quantified aerosol direct radiative effects (DREs) and associated uncertainties at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) and Tropical Western Pacific (TWP) sites under both clear and all sky conditions by taking advantage of the advanced ARM long-term comprehensive measurements of aerosol, cloud, radiation, and atmospheric state. This effort has filled the knowledge gap in aerosol DREs at the SGP and TWP under all sky conditions based on the ARM observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Tightest Mixed-Integer Programming Formulations for Quadratic SCUC Optimization

In this project, we developed new, tighter Mixed-Integer Programming (MIP) formulations for the combined Alternating Current (AC) Security-Constrained Unit Commitment (SCUC) and Security-Constrained Optimal Power Flow (SCOPF). The work addresses a critical challenge in power system operations: efficiently determining which generation units to commit and how to optimally dispatch them while maintaining network reliability constraints for both normal and contingency scenarios. Our efforts: 1. Advance the Understanding of SCUC/SCOPF Modeling: By introducing tighter MIP formulations and leveraging cutting-edge optimization tools (Julia/JuMP, PowerModels.jl), this project has pushed forward the state of the art in efficient power systems scheduling. 2. Enhance Technical and Economic Feasibility: The methods developed provide more accurate and potentially faster solutions to large-scale, realistic scheduling and dispatch problems in electric power systems, which can translate into improved reliability and potentially lower costs for grid operations. 3. Benefit to the Public: Greater efficiency in power system operations leads to cost savings for utilities and end-users. Improved reliability and integration of advanced modeling approaches can facilitate the adoption of clean energy resources and better accommodate uncertainties in renewable generation. Because this technology could impact bulk power markets and reliability, these innovations have far-reaching public benefits in terms of cost savings, reliability, and sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Illuminating Dark Matter Admixed in Neutron Stars with Simultaneous Mass–Radius Constraints

We investigate how simultaneous mass and radius measurements of massive neutron stars can help constrain the properties of dark matter possibly admixed in them. Within a fermionic dark matter model that interacts only through gravitation, along with a well-constrained nuclear matter equation of state, we show that the simultaneous mass and radius measurement of PSRJ0740+6620 reduces the uncertainty of dark matter central energy density by more than 50% compared to the results obtained from using the two observables independently, while other dark matter parameters remain unconstrained. Additionally, we find that the dark matter fraction fD should be smaller than 2% when constrained by the observed neutron star maximum mass alone, and it could be even smaller than 0.3% with the simultaneous measurement of mass and radius, supporting the conclusion that only a small amount of dark matter exists in dark matter admixed neutron stars (DANSs).

NICER↗
DOE OSTI2020

Gamma-Rays from Kilonovae and the Cosmic Gamma-Ray Background

The recent detection of the gravitational-wave event GW170817, produced by the coalescence of two neutron stars, and of its optical–infrared counterpart, powered by the radioactive decay of r-process elements, has opened a new window onto gamma-ray astronomy: the direct detection of photons coming from such decays. In this work, we calculate the contribution of kilonovae to the diffuse gamma-ray background in the MeV range, using recent results on the spectra of the gamma-rays emitted in individual events, and we compare it with that from other sources. We find that the contribution from kilonovae is not dominant in such an energy range, but within current uncertainties, and its addition to other sources might help to fit the observational data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures

Abstract. This paper provides a summary of the work done within Phase IV of the Offshore Code Comparison Collaboration, Continued with Correlation and unCertainty (OC6) project, under International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the loading on and motion of a novel floating offshore wind system. Numerical models of a 3.6 MW horizontal-axis wind turbine atop the TetraSpar floating support structure were compared using measurement data from a 1:43-Froude-scale test performed in the University of Maine's Alfond Wind–Wave (W2) Ocean Engineering Laboratory. Participants in the project ran a series of simulations, including system equilibrium, surge offsets, free-decay tests, wind-only conditions, wave-only conditions, and a combination of wind and wave conditions. Validation of the models was performed by comparing the aerodynamic loading, floating support structure motion, tower base loading, mooring line tensions, and keel line tensions. The results show a relatively good estimation of the aerodynamic loading and a reasonable estimation of the platform motion and tower base fore–aft bending moment. However, there is a significant dispersion in the dynamic loading for the upwind mooring line. Very good agreement was observed between most of the numerical models and the experiment for the keel line tensions.

17 WIND ENERGY↗
DOE OSTI2022

Deep modelling of plasma and neutral fluctuations from gas puff turbulence imaging

The role of turbulence in setting boundary plasma conditions is presently a key uncertainty in projecting to fusion energy reactors. To robustly diagnose edge turbulence, we develop and demonstrate a technique to translate brightness measurements of HeI line radiation into local plasma fluctuations via a novel integrated deep learning framework that combines neutral transport physics and collisional radiative theory for the $3^3 D - 2^3 P$ transition in atomic helium. The tenets for experimental validity are reviewed, illustrating that this turbulence analysis for ionized gases is transferable to both magnetized and unmagnetized environments with arbitrary geometries. Based upon fast camera data on the Alcator C-Mod tokamak, we present the first 2-dimensional time-dependent experimental measurements of the turbulent electron density, electron temperature, and neutral density revealing shadowing effects in a fusion plasma using a single spectral line.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1985

Theoretical study of EAS hadronic structure

The structure of extensive air showers (EAS) is determined mainly by the energetic hadrons. They are strongly collimated in the core of the shower and essential difficulties are encountered for resolution of individual hadrons. The properties for resolution are different from the variety of hadron detectors used in EAS experiments. This is the main difficulty in obtaining a general agreement between actually registered data with different detectors. The most plausible source for disagreement is the uncertainty in determination of the energy of individual hadrons. This research demonstrates that a better agreement can be obtained with the average tendency of hadronic measurements if one assumes a larger coefficient of inelasticity and stronger energy increase of the total inelastic cross section in high energy pion interactions. EAS data above 10 to the 5th power GeV are revealing a faster development of hadronic cascades in the air then can be expected by extrapolating the parameters of hadron interactions obtained in accelerator measurements.

Popova, L.↗
NASA NTRS1992

AXAF VETA-I mirror encircled energy measurements and data reduction

The AXAF VETA-I mirror encircled energy was measured with a series of apertures and two flow gas proportional counters at five X-ray energies ranging from 0.28 to 2.3 keV. The proportional counter has a thin plastic window with an opaque wire mesh supporting grid. Depending on the counter position, this mesh can cause the X-ray transmission to vary as much as +/-9 percent, which directly translates into an error in the encircled energy. In order to correct this wire mesh effect, window scan measurements were made, in which the counter was scanned in both horizontal (Y) and vertical (Z) directions with the aperture fixed. Post VETA measurement of the VXDS setup were made to determine the exact geometry and position of the mesh grid. Computer models of the window mesh were developed to simulate the X-ray transmission based on this measurement. The window scan data were fitted to such mesh models and corrections were made. After this study, the mesh effect was well understood and the final results of the encircled energy were obtained with an uncertainty of less than 0.8 percent.

Zhao, Ping↗
NASA NTRS1993

AXAF VETA-I mirror encircled energy measurements and data reduction

The AXAF VETA-I mirror encircled energy was measured with a series of apertures and two flow gas proportional counters at five X-ray energies ranging from 0.28 to 2.3 keV. The proportional counter has a thin plastic window with an opaque wire mesh supporting grid. Depending on the counter position, this mesh can cause the X-ray transmission to vary as much as +/- 9 percent, which directly translates into an error in the encircled energy. In order to correct this wire mesh effect, window scan measurements were made, in which the counter was scanned in both horizontal (Y) and vertical (Z) directions with the aperture fixed. Post VETA measurement of the VXDS setup were made to determine the exact geometry and position of the mesh grid. Computer models of the window mesh were developed to simulate the X-ray transmission based on this measurement. The window scan data were fitted to such mesh models and corrections were made. After this study, the mesh effect was well understood and the final results of the encircled energy were obtained with an uncertainty of less than 0.8 percent.

Zhao, Ping↗
NASA NTRS1993

Physical model-set identification for robust control of flexible structures

An approach to dynamic system identification is presented taking into account the goal of enhancing robust control performance of flexible structures. Identification techniques are derived which take advantage of the physics of structural dynamics and can provide realistic bounds for all potential parameter uncertainties. The developed approach includes input optimization which distributes excitation energy in such a way that the influence of residual uncertainties on robust control performance is reduced.

Karlov, Valeri I.↗
NASA NTRS2011

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction.

Kahn, Ralph A.↗
NASA NTRS2014

Interactions Between Biomass-Burning Aerosols and Clouds over Southeast Asia: Current Status, Challenges, and Perspectives

The interactions between aerosols, clouds, and precipitation remain among the largest sources of uncertainty in the Earth's energy budget. Biomass-burning aerosols are a key feature of the global aerosol system, with significant annually-repeating fires in several parts of the world, including Southeast Asia (SEA). SEA in particular provides a "natural laboratory" for these studies, as smoke travels from source regions downwind in which it is coupled to persistent stratocumulus decks. However, SEA has been under-exploited for these studies. This review summarizes previous related field campaigns in SEA, with a focus on the ongoing Seven South East Asian Studies (7-SEAS) and results from the most recent BASELInE deployment. Progress from remote sensing and modeling studies, along with the challenges faced for these studies, are also discussed. We suggest that improvements to our knowledge of these aerosol/cloud effects require the synergistic use of field measurements with remote sensing and modeling tools.

biomass-burning aerosol↗
NASA NTRS2015

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗
NASA NTRS2018

Microphysical Properties of Tropical Tropopause Layer Cirrus

Pervasive cirrus clouds in the tropical tropopause layer (TTL) play an important role in determining the composition of stratospheric air through dehydration of tropospheric air entering the stratosphere. This dehydration affects Earth's energy budget and climate, yet uncertainties remain regarding the microphysical processes that govern TTL cirrus. TTL cirrus were sampled with the NASA Global Hawk UAV for over 30 hr in the Western Pacific in 2014 during the Airborne Tropical TRopopause EXperiment. In situ measurements by a Fast Cloud Droplet Probe and Hawkeye probe (combination Fast Cloud Droplet Probe, Two‐Dimensional Stereo optical array probe, and Cloud Particle Imager) provided particle concentrations and sizing between 1‐ and 1,280‐μm diameter and high resolution images for habit identification. We present the variability in ice concentrations, size distributions, and habits as functions of temperature, altitude, and time since convective influence. Observed ice particles were predominantly small and quasi‐spheroidal in shape, with the percentage of quasi‐spheroids increasing with decreasing temperature. In comparison to the large fraction of the population consisting of quasi‐spheroids, faceted habits (columns, plates, rosettes, and budding rosettes) constituted a smaller percentage of the overall population and exhibited the opposite correlation with temperature. The trend of higher percentages of faceted crystals occurring at warmer temperatures may be due to diffusional growth or aggregation as particles descend through cloud, and/or the more rapid diffusional growth rate at warmer temperatures. Sampling was typically well away from deep convection, however, and very few aggregates were observed, so the trend of higher percentages of faceted habits is likely attributable to diffusional growth.

Woods, Sarah↗
NASA NTRS2019

Optimization of a Remote Sensing Energy Balance Method over Different Canopy Applied at Global Scale

Parameterization methods which calculate turbulent heat and water fluxes with thermal remote sensing data were evaluated in the revised remote sensing surface energy balance system (SEBS) model (Chen et al., 2013). The model calculates sensible heat (H) based on the Monin-Obukhov similarity theory (MOST) and determines latent heat (LE) as the residual of energy balance. We examined the uncertainties of H and LE in the SEBS model due to five key parameters at the local station point scale. Observations at 27 flux towers located in seven land cover types (needle-leaf forest, broad leaf forest, shrub, savanna, grassland, cropland, and sparsely vegetated land) and an artificial intelligence particle swarm optimization (PSO) algorithm was combined to calibrate the five parameters (leaf drag coefficient, leaf heat transfer coefficients, roughness length for soil, and two parameters for ground heat calculation) in the SEBS model. The root-mean-square error at the site scale was reduced by 9 W/sq.m for H, and 92 W/sq.m for LE, and their correlation coefficients were increased by 0.07 (H) and 0.11 (LE) after using the calibrated parameters. The updated model validation was further conducted globally for the remotely sensed evapotranspiration (ET) calculations. Overestimation of SEBS global ET was significantly improved by using the optimized values of the parameters. The results suggested PSO was able to consistently locate the global optimum of the SEBS model, and appears to be capable of solving the ET model optimization problem.

Chen, Xuelong↗