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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Assimilating Scanning Radar Data into Cloud-Scale Models

The aim of this project is to improve the initial conditions of large eddy simulations (LES) of deep convective storms by assimilating scanning radar reflectivity and radial velocity data as well as local environmental observations. Accomplishing this goal often results in more accurate numerical forecasts of clouds and precipitation than if the background initial meteorological conditions are solely relied upon for convection initiation and intensification, as is typical of most operational and research models. Conducted in a storm-scale LES framework, these more accurate numerical analyses can serve as tool to better understand and parameterize land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development of convection. Our work examined the sensitivity of the numerical representation of cloud-scale wind and microphysical structures to: i) the assimilation of radiosonde observations characterizing the near-storm inflow, ii) the assimilation of radar data of varying resolution for model simulations with grid spacings of 1-km and 0.25-km, and iii) to the assimilation of three-dimensional plan-projection-indicator (PPI) and range-height indicator (RHI) radar volumes. Few studies have explored deep convective storm analyses and forecasts produced by assimilation of radar observations to cloud-scale LES. Furthermore, to our knowledge, no storm-scale DA study has explored the value of assimilating high-resolution sector RHI volumes to determine if they can improve the retrieval of the vertical kinematic and microphysical storm structure aloft over the use of traditionally utilized PPI scans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The introspective may achieve more: Enhancing existing Geoscientific models with native-language emulated structural reflection

Geoscientific models manage myriad and increasingly complex data structures as trans -disciplinary models are integrated. They often incur significant redundancy with cross-cutting tasks. Reflection, the ability of a program to inspect and modify its structure and behavior at runtime, is known as a powerful tool to improve code reusability, abstraction, and separation of concerns. Reflection is rarely adopted in high-performance Geoscientific models, especially with Fortran, where it was previously deemed implausible. Practical constraints of language and legacy often limit us to feather-weight, native-language solutions. We demonstrate the usefulness of a structural-reflection-emulating, dynamically-linked metaObjects, gd . We show real-world examples including data structure self-assembly, effortless save/restart and upgrade to parallel I/O, recursive actions and batch operations. We share gd and a derived module that reproduces MATLAB-like structure in Fortran and C++. We suggest that both a gd representation and a Fortran-native representation are maintained to access the data, each for separate purposes. In conclusion, embracing emulated reflection allows generically-written codes that are highly re-usable across projects.

58 GEOSCIENCES↗
DOE OSTI2025

Development of a data-driven neural network model for electron thermal transport in NSTX

A data-driven electron thermal transport neural network (ETT-NN) model, trained on TRANSP interpretative analysis results of National Spherical Torus Experiment (NSTX), was developed to enable faster and more accurate ETT computation for spherical tokamaks (STs). The model incorporates both convolutional NNs and recurrent NNs, allowing it to simultaneously account for the spatial and temporal non-localities and multi-scale features of turbulent transport, which have been considered only in a limited manner in conventional models. The model was validated through interpretative analysis and predictive simulations using Tokamak Reactor Integrated Automated Suite for Simulation and Computation, demonstrating relatively high accuracy. Additionally, parameter scans were performed on test discharges known to exhibit specific turbulent modes, such as microtearing mode, trapped electron mode, kinetic ballooning mode, and electron temperature gradient mode. The scanning results revealed that the ETT-NN model exhibits the same trends as those observed in conventional gyrokinetic simulations or theories, while also capturing the global nature of turbulent transport, indicating that the data-driven model accurately reflects the underlying physical characteristics. Furthermore, due to the dimensionless nature of the model, we can feasibly expand its applicability by incorporating data from other devices and uncovering the characteristics of ETT in STs in the future.

NSTX↗
DOE OSTI2023

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

We report results from a recent field experiment to test the validity of using physics-based synthetic infrared spectra to serve as endmembers in a spectral database targeted at chemical deposits. Specifically, the optical constants n and k, (the real and imaginary part of the refractive index) were used to first model infrared reflectance spectra for different thicknesses of chemical layers (e.g. acetaminophen, methylphosphonic acid – MPA, etc.) on various conducting and insulating substrates such as aluminum, wood, and glass. In the experimental portion of the research, thin films of the solid and liquid analytes were deposited onto such substrates to form micron-thick layers of the analytes at different thicknesses: Standoff data from an imaging instrument were then recorded and analyzed to not only identify the different analytes, but also quantify the layer/deposit thickness. To gauge success, the detection results using the synthetic data were compared to the results from hemispherical reflectance (HRF) spectra that were collected for the same sample planchets measured in the field via standoff methods. Preliminary results indicate good agreement between the synthetic reference data as compared to the lab-measured HRF data in terms of their ability to quantitatively reduce longwave infrared data. Specifically, modeled IR spectra for acetaminophen on an aluminum planchet at various thicknesses (1, 2, 5, 10, 15, and 20 µm) were synthesized and compared with standoff field reflectance data as well as HRF laboratory reflectance spectra for two samples: a 5.2 µm- and 12.8 µm-thick layer of acetaminophen on aluminum. Using a first-order approximation, analysis of the field data estimates the thicknesses of the samples to be 2 and 10 µm for the two samples, respectively, while the HRF laboratory data yields thickness estimates of between 5-10 µm and 10 µm, respectively. Both yield reasonable estimates, with the uncertainty most likely due to factors yet to be accounted for in the synthetic spectra such as light scattering.

complex index of refraction, optical constants, hy↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2019

Silicate weathering in anoxic marine sediment as a requirement for authigenic carbonate burial

We emphasize the importance of marine silicate weathering (MSiW) reactions in anoxic sediment as fundamental in generating alkalinity and cations needed for carbonate precipitation and preservation along continental margins. We use a model that couples thermodynamics with aqueous geochemistry to show that the CO 2 released during methanogenesis results in a drop in pH to 6.0; unless these protons are buffered by MSiW, carbonate minerals will dissolve. We present data from two regions: the India passive margin and the active subduction zone off Japan, where ash and/or rivers supply the reactive silicate phase, as reflected in strontium isotope data. Offshore India and Korea, alteration of continent-derived silicates results in pore water enriched in radiogenic 87 Sr, with 87 Sr/ 86 Sr ratios as high as 0.7095 and 0.7104, respectively. Off Japan, strontium in pore water influenced by ash alteration is depleted in 87 Sr, with 87 Sr/ 86 Sr as low as 0.7065. Carbonate minerals formed by alkalinity and cations generated through MSiW carry these strontium isotopic signals, and are typically dolomite, siderite, and Fe-rich calcite. These contrast with the aragonite and high-magnesium calcite that form during anaerobic oxidation of methane and incorporate the coeval seawater 87 Sr/ 86 Sr signal. We show that MSiW is necessary for authigenic carbonate formation and preservation along continental margins, which remove carbon from Earth’s surface at rates previously estimated to be at least 10 12 mol yr -1 . In addition, these authigenic carbonates are of relevance to studies of the deep biosphere, fluid flow, seismogenesis, slope stability, and reservoir characteristics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Trapped Proton Environment in Medium-Earth Orbit (2000-2010)

This report describes the method used to derive fluxes of the trapped proton belt along the GPS orbit (i.e., a Medium-Earth Orbit) during 2000 – 2010, a period almost covering a solar cycle. This method utilizes a newly developed empirical proton radiation-belt model, with the model output scaled by GPS in-situ measurements, to generate proton fluxes that cover a wide range of energies (50keV- 6MeV) and keep temporal features as well. The new proton radiation-belt model is developed based upon CEPPAD proton measurements from the Polar mission (1996 – 2007). Comparing to the de-facto standard empirical model of AP8, this model is not only based upon a new data set representative of the proton belt during the same period covered by GPS, but can also provide statistical information of flux values such as worst cases and occurrence percentiles instead of solely the mean values. The comparison shows quite different results from the two models and suggests that the commonly accepted error factor of 2 on the AP8 flux output over-simplifies and thus underestimates variations of the proton belt. Output fluxes from this new model along the GPS orbit are further scaled by the ns41 in-situ data so as to reflect the dynamic nature of protons in the outer radiation belt at geomagnetically active times. Derived daily proton fluxes along the GPS ns41 orbit, whose data files are delivered along with this report, are depicted to illustrate the trapped proton environment in the Medium-Earth Orbit. Uncertainties on those daily proton fluxes from two sources are evaluated: One is from the new proton-belt model that has error factors < ~3; the other is from the in-situ measurements and the error factors could be ~ 5.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Micro Rain Radar / Processed Data

This dataset includes the reflectivity, estimated rainfall rate, liquid water content, and vertical velocity recorded by the MRR2 averaged over 30-second intervals.

17 WIND ENERGY↗
DOE OSTI2024

Micro Rain Radar / Raw Data

This dataset includes the reflectivity, estimated rainfall rate, liquid water content, and vertical velocity recorded by the MRR2 averaged over 30 s intervals.

17 WIND ENERGY↗
DOE OSTI2017

The Very Low Albedo of WASP-12b from Spectral Eclipse Observations with Hubble

We present an optical eclipse observation of the hot Jupiter WASP-12b using the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope. These spectra allow us to place an upper limit of A{sub g}<0.064 (97.5% confidence level) on the planet’s white light geometric albedo across 290–570 nm. Using six wavelength bins across the same wavelength range also produces stringent limits on the geometric albedo for all bins. However, our uncertainties in eclipse depth are ∼40% greater than the Poisson limit and may be limited by the intrinsic variability of the Sun-like host star—the solar luminosity is known to vary at the 10{sup −4} level on a timescale of minutes. We use our eclipse depth limits to test two previously suggested atmospheric models for this planet: Mie scattering from an aluminum-oxide haze or cloud-free Rayleigh scattering. Our stringent nondetection rules out both models and is consistent with thermal emission plus weak Rayleigh scattering from atomic hydrogen and helium. Our results are in stark contrast with those for the much cooler HD 189733b, the only other hot Jupiter with spectrally resolved reflected light observations; those data showed an increase in albedo with decreasing wavelength. The fact that the first two exoplanets with optical albedo spectra exhibit significant differences demonstrates the importance of spectrally resolved reflected light observations and highlights the great diversity among hot Jupiters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

An infrared, Raman, and X-ray database of battery interphase components

Further improvements to lithium-ion and emerging battery technologies can be enabled by an improved understanding of the chemistry and working mechanisms of interphases that form at electrochemically active battery interfaces. However, it is difficult to collect and interpret spectra of interphases for several reasons, including the presence of a variety of compounds. To address this challenge, we herein present a vibrational spectroscopy and X-ray diffraction data library of ten compounds that have been identified as interphase constituents in lithium-ion or emerging battery chemistries. The data library includes attenuated total reflectance Fourier transform infrared spectroscopy, Raman spectroscopy, and X-ray diffraction data, collected in inert atmospheres provided by custom sample chambers. The data library presented in this work (and online repository) simplifies access to reference data that is otherwise either diffusely spread throughout the literature or non-existent, and provides energy storage researchers streamlined access to vital interphase-relevant data that can accelerate battery research efforts.

25 ENERGY STORAGE↗
DOE OSTI2024

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗
DOE OSTI2021

Leaf spectral reflectance and transmittance, San Lorenzo, Panama, 2020

This data package contains full-range (350 – 2500 nm) leaf reflectance and transmittance spectra of leaves collected at the San Lorenzo forest canopy crane site in Panama (PA-SLZ) from January to March 2020. Around 1000 leaves were measured from 50 species and various leaf phenological stages. Leaves were sampled from both the top of the canopy and multiple heights within the canopy from 10 vertical profiles and for six core species, from the top of the canopy. This data package includes processed leaf spectra (*.csv), and raw data from the spectroradiometer (compressed as .zip). Metadata files include data descriptions (_dd.csv) for tabular data and sample information and a description of the field campaign protocol (PA-SLZ_2020_Protocol.pdf). In addition to the leaf spectral measurements included here, these samples were also used for measurement of leaf gas exchange, carbon and nitrogen content and leaf mass per unit leaf area (LMA) contained in related data packages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

NGEE Arctic Leaf Spectral Reflectance and Transmittance, Barrow, Alaska, 2014-2016

Data were collected to characterize the leaf-level optical properties and albedo of dominant Arctic tundra species in the Barrow, AK area and to enable trait scaling. Measurements of full-spectrum (i.e. 350-2500nm) leaf spectral reflectance of Arctic plant species. Data were collected in Barrow, Alaska during the 2014-2016 period. This dataset contains 5 zipped folders, 4 csv, 4 xlsx, 1 txt, and 1 pdf files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort 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↗
DOE OSTI2015

Software for HUBER-5042 diffractometer with Displex DE-202 helium cryostat

A software for structural studies on a Huber-5042 diffractometer with a point detector and closed-cycle Displex DE-202 helium cryostat has been developed. The software package includes programs for the preliminary stage of experiment, planning, data collection, profile analysis of reflections, etc. The measurement of reflections in the 2θ angular range from 0° to 152° is provided, which is unique for Eulerian goniometers. Tools for enhancing data collection are demonstrated. Accurate experimental data are obtained for a test CaF{sub 2} crystal (sp. gr. Fm3̄m, Z = 4, resolution sinθ/λ{sub max} ≈ 1.354 Å{sup −1}, 121 reflections, 16 parameters in refinement, R/wR = 0.31/0.34%, Δρ{sub min}/Δρ{sub max} = −0.08/+0.07 e/Å{sup 3}).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

TESTING RELATIVISTIC REFLECTION AND RESOLVING OUTFLOWS IN PG 1211+143 WITH XMM-NEWTON AND NuSTAR

We analyze the broad-band X-ray spectrum (0.3–50 keV) of the luminous Seyfert 1/quasar PG 1211+143—the archetypal source for high-velocity X-ray outflows—using near-simultaneous XMM-Newton and NuSTAR observations. We compare pure relativistic reflection models with a model including the strong imprint of photoionized emission and absorption from a high-velocity wind, finding a spectral fit that extrapolates well over the higher photon energies covered by NuSTAR . Inclusion of the high signal-to-noise ratio XMM-Newton spectrum provides much tighter constraints on the model parameters, with a much harder photon index/lower reflection fraction compared to that from the NuSTAR data alone. We show that pure relativistic reflection models are not able to account for the spectral complexity of PG 1211+143 and that wind absorption models are strongly required to match the data in both the soft X-ray and Fe K spectral regions. In confirming the significance of previously reported ionized absorption features, the new analysis provides a further demonstration of the power of combining the high throughput and resolution of long-look XMM-Newton observations with the unprecedented spectral coverage of NuSTAR .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Development of a Short-Duration Drive Cycle to Represent Long-Term Measured Drive Cycle Data: Evaluation of Truck Efficiency Technologies in Class 8 Tractor Trailers

Quantifying the fuel savings and emissions reductions that can be achieved from truck fuel efficiency technologies for a fleet's specific usage allows the fleet to select a combination of technologies that will yield the greatest operational efficiency and profitability. An accurate characterization of usage for the fleet is critical for such an evaluation; however, short-term measured drive cycle data do not generally reflect overall usage very effectively. This study presents a detailed analysis of vehicle usage in a commercial vehicle fleet and demonstrates the development of a short-duration synthetic drive cycle with measured drive cycle data collected over an extended period of time. The approach matched statistical measures of the vehicle speed with acceleration history and integrated measured grade data to develop a compressed drive cycle that accurately represents total usage. Drive cycle measurements obtained during a full year from six tractor trailers in normal operations in a less-than-truckload carrier were analyzed to develop a synthetic drive cycle. The vehicle mass was also estimated to account for the variation of loads that the fleet experienced. These drive cycle and mass data were analyzed with a tractive energy analysis to quantify the benefits in terms of fuel efficiency and reduced carbon dioxide emissions that can be achieved on Class 8 tractor trailers by using advanced efficiency technologies, either individually or in combination. Although differences exist between Class 8 tractor trailer fleets, this study provides valuable insight into the energy and emissions reduction potential that various technologies can bring in this important trucking application. Finally, the methodology employed for generating the synthetic drive cycle serves as a rigorous approach to develop an accurate usage characterization that can be used to effectively compress large quantities of drive cycle data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗