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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

X-ray variability of Cygnus X-1 in its soft state

Observations from the Rossi X-ray Timing Explorer (RXTE) of Cyg X-1 in the soft state and during the soft to hard transition are examined. The results of this analysis confirm previous conclusions that for this source there is a settling period (following the transition from the hard to soft state during which the low energy spectrum varies significantly, while the high energy portion changes little) during which the source reaches nominal soft state brightness. This behavior can be characterized by a soft low energy spectrum and significant low frequency 1/f noise and white noise on the power density spectrum, which becomes softer upon reaching the true soft state. The low frequency 1/f noise is not observed when Cyg X-1 is in the hard state, and therefore appears to be positively correlated with the disk mass accretion rate. The difference in the observed spectral and timing properties between the hard and soft states is qualitatively consistent with a fluctuating corona model.

Cui, W.↗
DOE OSTI2024

Association Kinetics for Perfluorinated n -Alkyl Radicals

Radical-radical reaction channels are important in the pyrolysis and oxidation chemistry of perfluoroalkyl substances (PFAS). In particular, unimolecular dissociation reactions within unbranched n-perfluoroalkyl chains, and their corresponding reverse barrierless association reactions, are expected to be significant contributors to the gas-phase thermal decomposition of families of species such as perfluorinated carboxylic acids and perfluorinated sulfonic acids. Unfortunately, experimental data for these reactions are scarce and uncertain. Furthermore, obtaining reliable theoretical predictions for such reactions is a laborious and computationally intensive task. Here, in this work, the chemical kinetics of the various association/decomposition reactions producing/decomposing the C 2 -C 4 series of unbranched n-perfluoroalkanes (C 2 F 6 , C 3 F 8 , and C 4 F 10 ) are examined using state-of-the-art ab initio transition-state-theory-based master-equation calculations. The variable-reaction-coordinate transition-state theory (VRC-TST) formalism is employed in computing the microcanonical and canonical rates for the association reactions. Reaction thermochemistry is obtained via composite quantum chemistry calculations and the laddering of error-canceling reaction schemes via a connectivity-based hierarchy approach employing ANL1/ANL0-style reference energies. Lennard-Jones collision model parameters for the considered systems were estimated by a direct dynamics approach, and collisional energy transfer parameters were obtained from analogies to systems of similar size and heavy-atom connectivity. A one-dimensional master equation approach was used to convert the microcanonical rate coefficients from the VRC-TST analysis into temperature- and pressure-dependent rate constants for the association reactions and the reverse dissociation reactions. The data are reported in standardized formats for usage in comprehensive chemical kinetic models for PFAS thermal destruction.

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

First Measurements of Differential Cross Sections In Kinematic Imbalance Variables With The MicroBooNE Detector

Making high-precision measurements of neutrino oscillation parameters requires an unprecedented understanding of neutrino-nucleus scattering. In this presentation, we present the first muon neutrino charged current double-differential cross sections in kinematic imbalance variables. These variables characterize the imbalance in the plane transverse to an incoming neutrino. We use events with a single muon above 100 MeV/c, a single final state proton above 300 MeV/c, and no recorded final state pions. Thus, these variables act as a direct probe of nuclear effects such as final state interactions, Fermi motion, and multi-nucleon processes. We also present a complementary ongoing analysis using electron neutrinos. This channel is of the utmost importance for the extraction of neutrino oscillation parameters by making high-precision measurements. Our measurements allow us to constrain systematic uncertainties associated with neutrino oscillation results performed by near-future experiments of the Short Baseline Neutrino (SBN) program, as well as by future large-scale experiments like DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First Measurements of Differential Cross Sections In Kinematic Imbalance Variables With The MicroBooNE Detector

Making high-precision measurements of neutrino oscillation parameters requires an unprecedented understanding of neutrino-nucleus scattering. In this presentation, we present the first muon neutrino charged current double-differential cross sections in kinematic imbalance variables. These variables characterize the imbalance in the plane transverse to an incoming neutrino. We use events with a single muon above 100 MeV/c, a single final state proton above 300 MeV/c, and no recorded final state pions. Thus, these variables act as a direct probe of nuclear effects such as final state interactions, Fermi motion, and multi-nucleon processes. We also present a complementary ongoing analysis using electron neutrinos. This channel is of the utmost importance for the extraction of neutrino oscillation parameters by making high-precision measurements. Our measurements allow us to constrain systematic uncertainties associated with neutrino oscillation results performed by near-future experiments of the Short Baseline Neutrino (SBN) program, as well as by future large-scale experiments like DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

First Measurements of Differential Cross Sections In Kinematic Imbalance Variables With The MicroBooNE Detector

Making high-precision measurements of neutrino oscillation parameters requires an unprecedented understanding of neutrino-nucleus scattering. In this presentation, we present the first muon neutrino charged current double-differential cross sections in kinematic imbalance variables. These variables characterize the imbalance in the plane transverse to an incoming neutrino. We use events with a single muon above 100 MeV/c, a single final state proton above 300 MeV/c, and no recorded final state pions. Thus, these variables act as a direct probe of nuclear effects such as final state interactions, Fermi motion, and multi-nucleon processes. We also present a complementary ongoing analysis using electron neutrinos. This channel is of the utmost importance for the extraction of neutrino oscillation parameters by making high-precision measurements. Our measurements allow us to constrain systematic uncertainties associated with neutrino oscillation results performed by near-future experiments of the Short Baseline Neutrino (SBN) program, as well as by future large-scale experiments like DUNE.

43 PARTICLE ACCELERATORS↗
NASA NTRS2003

Computational Study of Axisymmetric Off-Design Nozzle Flows

Computational Fluid Dynamics (CFD) analyses of axisymmetric circular-arc boattail nozzles operating off-design at transonic Mach numbers have been completed. These computations span the very difficult transonic flight regime with shock-induced separations and strong adverse pressure gradients. External afterbody and internal nozzle pressure distributions computed with the Wind code are compared with experimental data. A range of turbulence models were examined, including the Explicit Algebraic Stress model. Computations have been completed at freestream Mach numbers of 0.9 and 1.2, and nozzle pressure ratios (NPR) of 4 and 6. Calculations completed with variable time-stepping (steady-state) did not converge to a true steady-state solution. Calculations obtained using constant timestepping (timeaccurate) indicate less variations in flow properties compared with steady-state solutions. This failure to converge to a steady-state solution was the result of using variable time-stepping with large-scale separations present in the flow. Nevertheless, time-averaged boattail surface pressure coefficient and internal nozzle pressures show reasonable agreement with experimental data. The SST turbulence model demonstrates the best overall agreement with experimental data.

DalBello, Teryn↗
NASA NTRSDate not supplied

Application of the Concepts of Load State, Load Space, and Output Space to Strain-Gage Balances

The concepts of load state, load space, and output space are used to describe elements of the development of a load prediction process for a six–component strain–gage balance. The use of these terms adds clarity during the selection of the independent and dependent variables for the development of the load prediction process. First, the control volume model of a strain–gage balance is reviewed as it helps better understand the role of loads, outputs, and state variables during the load prediction. Then, the description of the absolute load datum in both the load space and the output space is discussed. It is concluded that the use of the difference between a raw output and the natural zero of a balance gage has a key advantage for the definition of the output space. In that case, the origin of the output space will also describe the absolute load datum of the balance. Finally, details of the application of the concepts of load state, load space, and output space to two commonly used balance load prediction methods are discussed.

strain-gage balance↗
NASA NTRS2019

Dynamics and Variability of the Spring Dry Season in the United States Southwest as Observed in AmeriFlux and NLDAS-2 Data

The spring dry season occurring in an arid region of the Southwest United States, which receives both winter storm track and summer monsoon precipitation, is investigated. Bimodal precipitation and vegetation growth provide an opportunity to assess multiple climate mechanisms and their impact on hydroclimate and ecosystems.We detect multiple shifts from wet to drier conditions in the observational record and land surface model output. Focusing on the recent dry period, a shift in the late 1990s resulted in earlier and greater spring soil moisture draw down, and later and reduced spring vegetation green-up, compared to a prior wet period (1979 - 1997). A simple soil moisture balance model shows this shift is driven by changes in winter precipitation.The recent post-1999 dry period, as well as an earlier one from 1948 - 1966, are both related to the cool tropics phase of Pacific decadal variability which influences winter precipitation. In agreement with other studies for the Southwest United States, we find the recent drought cannot be explained in terms of precipitation alone, but also is due to the rising influence of temperature, thus highlighting the sensitivity of this region to warming temperatures. Future changes in the spring dry season will therefore be affected by how tropical decadal variability evolves, and also by emerging trends due to human-driven warming.

Pascolini-Campbell, Madeleine↗
DOE OSTI2022

Data-centric machine learning in quantum information science

Abstract We propose a series of data-centric heuristics for improving the performance of machine learning systems when applied to problems in quantum information science. In particular, we consider how systematic engineering of training sets can significantly enhance the accuracy of pre-trained neural networks used for quantum state reconstruction without altering the underlying architecture. We find that it is not always optimal to engineer training sets to exactly match the expected distribution of a target scenario, and instead, performance can be further improved by biasing the training set to be slightly more mixed than the target. This is due to the heterogeneity in the number of free variables required to describe states of different purity, and as a result, overall accuracy of the network improves when training sets of a fixed size focus on states with the least constrained free variables. For further clarity, we also include a ‘toy model’ demonstration of how spurious correlations can inadvertently enter synthetic data sets used for training, how the performance of systems trained with these correlations can degrade dramatically, and how the inclusion of even relatively few counterexamples can effectively remedy such problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Steady state estimation of soil organic carbon using satellite‐derived canopy leaf area index

Abstract Estimation of soil organic carbon (SOC) stock using models typically requires long term spin‐up of the carbon‐nitrogen (CN) models, which has become a bottleneck for global modeling. We report a new numerical approach to estimate global SOC stock that can alleviate long spin‐up. The approach uses satellite‐based canopy leaf area index (LAI) and takes advantage of a reaction‐based biogeochemical module—Next Generation BioGeoChemical Module (NGBGC) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as in CLM4CN, it can be easily configured to run prognostic or steady state simulations. The new approach was applied at point and global scales and compared with SOC derived from spin‐up by running NGBGC in the prognostic mode, and SOC from the Harmonized World Soil Database (HWSD). The steady state solution is comparable to the spin‐up value when the satellite LAI is close to that from the spin‐up solution, and largely captured the global variability of the HWSD SOC across the different dominant plant functional types (PFTs). The correlation between the simulated and HWSD SOC was, however, weak at both point and global scales, suggesting the needs for improving the biogeochemical processes described in CLM4 and updating HWSD. Besides SOC, the steady state solution also includes all other state variables simulated by a spin‐up run, which makes the tested approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare multiple aspects simulated by different CN mechanisms in the model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

How do perceptions of safety and car ownership importance affect autonomous vehicle adoption?

In this study, we explicitly modeled how individuals' perceptions of automated vehicle (AV) safety and the importance they place on car ownership affect mode choices involving conventional and automated vehicles in the context of privately owned cars and ridehailing services. We adopted psychometric questions to capture these two latent variables and designed a stated preference survey based on the participants' actual travel patterns. Then, we quantified the impact of these latent variables on mode choices using an integrated choice and latent variable (ICLV) model. We found that both latent variables have a statistically significant effect on mode choices. The results show that car ownership importance has the most potent effect on privately owned cars (conventional car and self-driving car), followed by driverless ridehailing and conventional ridehailing. We also found that changes in safety perception are equivalent to sizable changes in price. In addition, we further investigated the impact of improvements in safety perception through four scenarios. The scenario testing results show that as the distribution of perceived safety is compressed toward positive safety perception, the market share of AVs spikes and dominates regular cars. Our results demonstrate that based on our respondents' current understanding of AVs, even if AV prices were comparable to regular cars, we cannot expect widespread use of AVs. However, improvements in AVs' safety and, consequently, consumer safety perception can considerably expand AVs' market share, and may offset the high cost of using the technology.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2000

State Relationships of Laminar Permanently-Blue Opposed-Jet Hydrocarbon-Fueled Diffusion Flames

The structure and state relationships of laminar soot-free (permanently-blue) diffusion flames at various strain rates were studied experimentally using an opposed-jet configuration, motivated by the importance of soot-free hydrocarbon-fueled diffusion flames for many practical applications. Measurements of gas velocities, temperatures and compositions were carried out along the stagnation stream line. Flame conditions studied included propylene- and 1,3-butadiene-fueled opposed-jet diffusion flames having a stoichiometric mixture fractions of 0.7 and strain rates of 60-240/s at normal temperature and pressure. It was found that oxygen leakage to fuel-rich conditions and carbon monoxide leakage to fuel-lean conditions both increased as strain rates increased. Furthermore, increased strain rates caused increased fuel concentrations near the flame sheet decreased peak gas temperatures, and decreased concentrations of carbon dioxide and water vapor throughout the flames. State relationships for major gas species and gas temperatures for these flames were found to exist over broad ranges of strain rates. In addition, current measurements, as well as previous measurements and predictions of ethylene-fueled permanently-blue diffusion flames, all having a stoichiometric mixture fraction of 0.7, were combined to establish generalized state relationships for permanently-blue diffusion flames for this stoichiometric mixture fraction. The combined measurements and predictions support relatively universal generalized state relationships for N2, CO2, H2O and fuel over a broad range of strain rates and fuel types. State relationships for O2 in the fuel-rich region, and for CO in the fuel-lean region, however, are functions of strain rate and fuel type. State relationships for H2 and temperature exhibit less universality, mainly due to the increased experimental uncertainties for these variables. The existence of state relationships for soot-free hydrocarbon-fueled diffusion flames provides potential for significant computational simplifications for modeling purposes in many instances, allowing for effects of finite-rate chemistry while avoiding time-consuming computations of Arrhenius expressions.

Lin, K.-C.↗
NASA NTRS2000

State Relationships of Laminar Permanently-Blue Opposed-Jet Hydrocarbon-Fueled Diffusion Flames

The structure and state relationships of laminar soot-free (permanently-blue) diffusion flames at various strain rates were studied experimentally using an opposed-jet configuration, motivated by the importance of soot-free hydrocarbon-fueled diffusion flames for many practical applications. Measurements of gas velocities, temperatures and compositions were carried out along the stagnation stream line. Flame conditions studied included propylene- and 1,3-butadiene-fueled opposed-jet diffusion flames having a stoichiometric mixture fractions of 0.7 and strain rates of 60-240 s (exp -1) at normal temperature and pressure. It was found that oxygen leakage to fuel-rich conditions and carbon monoxide leakage to fuel-lean conditions both increased as strain rates increased. Furthermore, increased strain rates caused increased fuel concentrations near the flame sheet, decreased peak gas temperatures, and decreased concentrations of carbon dioxide and water vapor throughout the flames. State relationships for major gas species and gas temperatures for these flames were found to exist over broad ranges of strain rates. In addition, current measurements, as well as previous measurements and predictions of ethylene-fueled permanently-blue diffusion flames, all having a stoichiometric mixture fraction of 0.7, were combined to establish generalized state relationships for permanently-blue diffusion flames for this stoichiometric mixture fraction. The combined measurements and predictions support relatively universal generalized state relationships for N2, CO2, H2O and fuel over a broad range of strain rates and fuel types. State relationships for O2 in the fuel-rich region, and for CO in the fuel-lean region, however, are functions of strain rate and fuel type. State relationships for H2 and temperature exhibit less universality, mainly due to the increased experimental uncertainties for these variables. The existence of state relationships for soot-free hydrocarbon-fueled diffusion flames provides potential for significant computational simplifications for modeling purposes in many instances, allowing for effects of finite-rate chemistry while avoiding time-consuming computations of Arrhenius expressions.

Lin, K.-C.↗
DOE OSTI2025

Interactions Between Climate Mean and Variability Drive Future Agroecosystem Vulnerability

ABSTRACT Agriculture is crucial for global food supply and dominates the Earth's land surface. It is unknown, however, how slow but relentless changes in climate mean state, versus random extreme conditions arising from changing variability , will affect agroecosystems' carbon fluxes, energy fluxes, and crop production. We used an advanced weather generator to partition changes in mean climate state versus variability for both temperature and precipitation, producing forcing data to drive factorial‐design simulations of US Midwest agricultural regions in the Energy Exascale Earth System Model. We found that an increase in temperature mean lowers stored carbon, plant productivity, and crop yield, and tends to convert agroecosystems from a carbon sink to a source, as expected; it also can cause local to regional cooling in the earth system model through its effects on the Bowen Ratio. The combined effect of mean and variability changes on carbon fluxes and pools was nonlinear, that is, greater than each individual case. For instance, gross primary production reduces by 9%, 1%, and 13% due to change in mean temperature, change in temperature variability, and change in both temperature mean and variability, respectively. Overall, the scenario with change in both temperature and precipitation means leads to the largest reduction in carbon fluxes (−16% gross primary production), carbon pools (−35% vegetation carbon), and crop yields (−33% and −22% median reduction in yield for corn and soybean, respectively). By unambiguously parsing the effects of changing climate mean versus variability and quantifying their nonadditive impacts, this study lays a foundation for more robust understanding and prediction of agroecosystems' vulnerability to 21st‐century climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Grid Integration and the Carrying Capacity of the U.S. Grid to Incorporate Variable Renewable Energy

In the United States and elsewhere, renewable energy (RE) generation supplies an increasingly large percentage of annual demand, including nine U.S. states where wind comprised over 10% of in-state generation in 2013. This white paper summarizes the challenges to integrating increasing amounts of variable RE, identifies emerging practices in power system planning and operation that can facilitate grid integration, and proposes a unifying concept—economic carrying capacity—that can provide a framework for evaluating actions to accommodate higher penetrations of RE. There is growing recognition that while technical challenges to variable RE integration are real, they can generally be addressed via a variety of solutions that vary in implementation cost. As a result, limits to RE penetration are primarily economic, driven by factors that include transmission and the flexibility of the power grid to balance supply and demand. This limit can be expressed as economic carrying capacity, or the point at which variable RE is no longer economically competitive or desirable to the system or society.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Unified 0.25-degree gridded infrastructure-critical extreme weather for the United States from 1979 to 2100

Extreme weather events can severely disrupt critical infrastructure, triggering cascading effects on power, transportation, and essential services. However, standard weather and climate datasets often lack specialized variables necessary for hazard assessments. We present a unified dataset of infrastructure-critical weather and climate variables across the United States at 0.25° resolution, covering daily or sub-daily intervals from 1979 to 2100. The dataset includes temperature, dew point, wind gusts, precipitation partitioned by rain, snow, and freezing rain or ice pellets, lightning, and wildfire metrics. Historical conditions (1979-2023) are synthesized from observations and reanalysis products, while future projections are derived from 14 CMIP6 global climate models (historical, SSP245, and SSP585 experiments). Physically based and data-driven methods are used to estimate variables not directly provided by existing models. By integrating these variables into a single unified dataset, we enable consistent, high-resolution assessments of weather-related infrastructure risks across past and future periods, supporting wide-ranging applications in energy, transportation, water resources, emergency management, and beyond.

Climate and Earth system modelling↗
DOE OSTI2016

Tungsten Incorporation into Gallium Oxide: Crystal Structure, Surface and Interface Chemistry, Thermal Stability and Interdiffusion

Tungsten (W) incorporated gallium oxide (Ga2O3) (GWO) thin films were deposited by radio-frequency magnetron co-sputtering of W-metal and Ga2O3-ceramic targets. Films were produced by varying sputtering power applied to the W-target in order to achieve variable W-content (0-12 at%) into Ga2O3 while substrate temperature was kept constant at 500 °C. Chemical composition, chemical valence states, microstructure and crystal structure of as-deposited and annealed GWO films were evaluated as a function of W-content. The structural and chemical analyses indicate that the samples deposited without any W-incorporation are stoichiometric, nanocrystalline Ga2O3 films, which crystallize in β-phase monoclinic structure. While GWO films also crystallize in monoclinic β-Ga2O3 phase, W-incorporation induces surface amorphization as revealed by structural studies. The chemical valence state of Ga ions probed by X-ray photoelectron spectroscopic (XPS) analyses is characterized by the highest oxidation state i.e., Ga3+. No changes in Ga chemical state are noted for variable W-incorporation in the range of 0-12 at%. Rutherford backscattering spectrometry (RBS) analyses indicate the uniform distribution of W-content in the GWO films. However, XPS analyses indicate the formation of mixed valence states for W ions, which may be responsible for surface amorphization in GWO films. GWO films were stable up to 900 oC, at which point thermally induced secondary phase (W-oxide) formation was observed. A transition to mesoporous structure coupled with W interdiffusion occurs due to thermal annealing as derived from the chemical analyses at the GWO films’ surface as well as depth-profiling towards the GWO-Si interface. A model has been formulated to account for the mechanism of W-incorporation, thermal stability and interdiffusion via pore formation in GWO films.

Chemical composition↗
DOE OSTI2024

AutoCheck: Automatically Identifying Variables for Checkpointing by Data Dependency Analysis

Checkpoint/Restart (C/R) has been widely deployed in numerous HPC systems, Clouds, and industrial data centers, which are typically operated by system engineers. Nevertheless, there is no existing approach that helps system engineers without domain expertise and domain scientists without system fault tolerance knowledge identify those critical variables accounted for correct application execution restoration in a failure for C/R. To address this problem, we propose an analytical model and a tool (AutoCheck) that can automatically identify critical variables to checkpoint for C/R. AutoCheck relies on first, analytically tracking and optimizing data dependency between variables and other application execution state, and second, a set of heuristics that identify critical variables for checkpointing from the refined data dependency graph (DDG). AutoCheck allows programmers to pinpoint critical variables to checkpoint quickly within a few minutes. We evaluate AutoCheck on 13 representative HPC benchmarks, demonstrating that AutoCheck can efficiently identify correct critical variables to checkpoint.

HPC↗