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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Synthetic-aperture radar (SAR) imaging with range-resolved reflection data

SAR imaging may be performed with range-resolved reflection data, where a spread-spectrum signal, such as a code division multiple access (CDMA) signal, is transmitted instead of a simple frequency chirp. The reflected spread-spectrum signal may be analyzed to gather range-resolved reflection data. Range-resolved reflection data may be gathered at each angular view. This data may be used to construct a more accurate approximation of the Fourier transform of the desired image than can be done by a conventional SAR approach. The image may be reconstructed from this Fourier transform using Fourier inversion techniques similar to those used in conventional SAR approaches. The range-resolved reflection scheme generally requires somewhat more processing to recover the image as compared with conventional SAR systems, but provides a significantly more stable image with less degradation from effects that plague conventional SAR systems. This can eliminate the need for phase coherency altogether and also eliminate “phase drift,” which leads to image distortion. This may be especially well suited for high resolution imaging of relatively large targets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Utah FORGE: Seismic Reflection Data

This is 2D and 3D seismic reflection data from Utah FORGE reprocessed during Phase 2c. The readme file containing an explanation of the data including data formats, software that can be used, processing, and projection and datum used. The Reprocessing document gives the rationale for reprocessing and shows examples of the improvements that were obtained. For all 3D and 2D data the following datasets were created and output in SEG-Y format: - Unmigrated Time - Prestack Time Migration (PSTM), Unenhanced (UnEnh) and Enhanced (Enh) - Prestack Depth Migration (PSDM), Unenhanced (UnEnh) and Enhanced (Enh) - Velocity Model used for Migration

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Code to map Xray reflectivity data from real space to reciprocal space

Code to map X-ray reflectivity data from real space to reciprocal space. The code is written as a Jupyter notebook. Example data are included as a separate file (example_data.csv). These data were collected on a Panalytical XRD system. As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for choosing the boundaries of the region of interest to estimate background. A simple algorithm is used to estimate background from the outer regions of the data collection region, interpolating the result inside the region of interest. The background is removed and then the data mapped to Qx-Qz (reciprocal space) coordinates. The results are written as NumPy binary and Matlab formatted files.

Fitzsimmons, Michael [Oak Ridge National Lab. (ORN↗
DOE OSTI2019

JGR_Data_Reflection_Project

This research data is based upon the work supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Award Number DE‐SC0019117. Additional support provided by Colorado School of Mines is highly appreciated.

58 GEOSCIENCES↗
DOE OSTI2025

Using Neural Networks to Identify Mixture Components in Hyperspectral Reflectance Data

Neural networks have been employed to identify materials of interest from hyperspectral data (generally imagery) based on their unique spectral signatures. This approach assumes that there is a single material that is standing out from the rest of the spectrum to be identified. However, pixels often contain more than one material, or a material of interest may itself be a mixture of multiple materials. Neural networks are only as good as the data used to train them, and it takes a great deal of work in the laboratory to identify, make, and measure all potential mixtures of interest. Thus, researchers often calculate synthetic spectra using algorithms with varying degrees of fidelity to the physics that govern the interactions between light and multiple materials. In this work, we have (1) adapted a neural network designed to identify mixture components from Raman spectroscopy to work with visible to near‐infrared reflectance data and (2) tested three common mixture algorithms to determine the most accurate and least computationally expensive method to build synthetic training datasets. With our initial test dataset, we have achieved accuracies of > 90% and found that the synthetic training dataset produced using the Hapke mixture model provides the best results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Place polarized neutron reflectivity data in bins of constant wavevector transfer

Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel. The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data. The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections. A future intention is to create a version of this code that will be one module of many in the data analysis workflow.

Fitzsimmons, Michael [Oak Ridge National Lab. (ORN↗
DOE OSTI2023

Estimating Individual Tree Mortality in the Sierra Nevada Using Lidar and Multispectral Reflectance Data

Widespread tree mortality events occur during periods of severe drought in temperate conifer forests and are expected to become more frequent in many areas due to climate change. Improved mapping of individual tree mortality is needed to identify risk factors and design effective conservation strategies. In this study, we used National Ecological Observatory Network (NEON) lidar and multispectral reflectance airborne observations to map individual tree mortality over a 160 km 2 area during and after the 2012–2016 drought for two sites in California's Sierra National Forest. We used NEON lidar to derive tree locations and crown perimeters and multispectral data to map tree mortality for more than 1 million trees. We found that 25.4% of the trees in our study area died between 2013 and 2017, with considerably higher mortality at the lower-elevation Soaproot Saddle site. Between 2017 and 2019, an additional 2.0%–2.8% of the trees died each year. Two wildfires in 2020 and 2021 increased tree mortality within burned area perimeters by 49%–89% between 2019 and 2021. Consistent with previous work, we found that tree mortality risk increased as a function of tree height. Tree mortality was positively associated with distance from rivers, trees per hectare, and decreasing slope at the lower elevation site. In contrast, increasing slope was positively associated with tree mortality at the higher elevation site. Our approach and dataset provide a means to study the combined effects of drought and wildfire on tree mortality and may improve projections of forest resilience under a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Validating first-principles molecular dynamics calculations of oxide/water interfaces with x-ray reflectivity data

Metal oxide/water interfaces play a crucial role in many electrochemical and photocatalytic processes, such as photoelectrochemical water splitting, the creation of fuel from sunlight, and electrochemical CO 2 reduction. First-principles electronic structure calculations can reveal unique insights into these processes, such as the role of the alignment of the oxide electronic energy levels with those of liquid water. An essential prerequisite for the success of such calculations is the ability to predict accurate structural models of these interfaces, which in turn requires careful experimental validation. Here we report a general, quantitative validation protocol for first-principles molecular dynamics simulations of oxide/aqueous interfaces. The approach makes direct comparisons of interfacial x-ray reflectivity (XR) signals from experimental measurements and those obtained from ab initio simulations with semilocal and van der Waals functionals. The protocol is demonstrated here for the case of the Al 2 O 3 (001)/water interface, one of the simplest oxide/water interfaces. We discuss the technical requirements needed for validation, including the choice of the density functional, the simulation cell size, and the optimal choice of the thermodynamic ensemble. Our results establish a general paradigm for the validation of structural models and interactions at solid/water interfaces derived from first-principles simulations. Furthermore, while there is qualitative agreement between the simulated structures and the experimental best-fit structure, direct comparisons of simulated and measured XR intensities show quantitative discrepancies that derive from both bulk regions (i.e., alumina and water) as well as the interfacial region, highlighting the need for accurate density functionals to properly describe interfacial interactions. Our results show that XR data are sensitive not only to the atomic structure (i.e., the atom locations) but also to the electron-density distributions in both the substrate and at the interface.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗
DOE OSTI2020

Comparative analysis of the methods for quantitative determination of water content in skin from diffuse reflectance spectroscopy data

The predictive properties of methods aimed for estimating the water content in skin from the spectral diffuse reflection characteristics near the water absorption line in the near-IR spectral range are analysed. Numerical simulation data, experimental data on diffuse reflection from human skin phantoms, and data from the reference data set of human skin reflectance spectra are used to consider the possibility of gaining additional information about the water distribution in skin. The influence of variations in the scattering coefficient and oxyhaemoglobin concentration on the water content estimates is investigated. (paper)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗
DOE OSTI2023

An Alternative to Solution Experiments for Nuclear Data Validation: Reflection and Interaction of Juxtaposed Uranium (RAIJU) Experiment Design

The need for solution experiments was thoroughly discussed at the recent NCERC (National Criticality Experiments Research Center) Futures Meeting in September 2022 for multiple applications including criticality safety, training, and nuclear data. However, this capability does not exist anywhere in the United States. NCERC, located at the Nevada National Security Site and operated by LANL (Los Alamos National Laboratory) is the only general-purpose critical experiments laboratory in the United States. However, solution experiments are not authorized at NCERC, and obtaining that authorization would be too time consuming and costly to happen in the foreseeable future. An alternative is needed – an experimental configuration with the homogeneity of liquid experiments, but without being a liquid. This project, Reflection and Interaction of Juxtaposed Uranium (RAIJU) will fill the gap in capability within LANL, the U.S. Department of Energy, and the international community and will support current and future nuclear material processing needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Since solids are only sometimes seen en masse in a pure bulk form, and for liquids other than water almost never, a capability to model reflectance spectra from analytes deposited on various substrates would be highly advantageous. If available, the real, n ( ν ) , and imaginary, k ( ν ) , components of the complex refractive index, n n + i k , can be used to simulate infrared spectra, accounting for reflection, refraction, and absorption phenomena as a function of wavelength. We focus on using the Pacific Northwest National Laboratory (PNNL) derived n / k vectors for solid and liquid analytes deposited as thin layers on different types of substrates including conductors, such as aluminum, and inorganic dielectrics, such as glass. The model is an adaptation of the Monte Carlo ray trace modeling program, TracePro, extended through the use of its macrolanguage. The model is tested using thin films of organic liquids including silicone oil and no. 2 diesel fuel, as well as organic solids such as caffeine and acetaminophen on aluminum and glass. The predicted spectra for the solid films were compared to experimental hemispherical reflectance data measured using a Fourier transform spectrometer with an integrating sphere. The thickness of the calculated layer is a parameter for predicting the (transflectance) spectra and is obtained using the areal density measured from gravimetric methods to generate the thin-layer samples. Comparison of the calculated spectra with experimental hemispherical reflectance data shows excellent agreement, indicating promise for the use of measured n / k data to synthesize reference spectral data. In particular, accounting for the inhomogeneity of the deposits greatly improved the match with experimental data. Finally, the theoretical modeling shows that for thicker layers (ca. 20 to 100 μm) of typical organics possessing moderately strong k values, the longwave infrared features are often saturated and better spectral contrast is obtained from the overtone/combination bands in the shortwave infrared.

42 ENGINEERING↗
DOE OSTI2024

Temporal and spatial characterization of a thermogenic, fault-controlled gas hydrate system, Woolsey Mound, Gulf of Mexico

Woolsey Mound, located at Mississippi Canyon Lease Block 118 (MC118), is the site of the Gulf of Mexico hydrate research consortium’s seafloor observatory, where gas hydrates outcrop at the seafloor. The presence of gas hydrates in the mound is confirmed directly by coring and indirectly by 3D seismic reflection data. Craters, pockmarks, chemosynthetic communities, and authigenic carbonates populate the seafloor at Woolsey Mound. Each crater is characterized by a network of shallow crestal faults that connect the hydrate mound to the underlying allochthonous salt body. We characterize the temporal and spatial evolution of gas hydrates at Woolsey Mound under natural perturbations using four collocated 3D seismic reflection data sets that span over 14 years. Data acquisition differences embedded in the data sets arising from variation in geometry, sample rate, and phase are minimized using the “cross-equalization” method. Our results indicate that hydrate formation and dissociation vary temporally and spatially in close connection to the shallow crestal faults. Evidence of gas hydrate dissociation is observed over a period of three years (2000–2003), where major dissociation occurred along the southern portion of the crestal fault in the southeast crater. The dissociation is less prominent in the southwest crater. Evidence of methane venting is observed between 2000 and 2010, which is mostly concentrated in the southeast crater. The residual amplitude anomalies observed between 2000 and 2014 in the mound are mostly positive, implying that the methane venting had increased significantly. The positive anomalies are correlated with the methane seepage recorded in 2011. Our results indicate the evolution of a fault-controlled gas hydrate system in the northern Gulf of Mexico, which would aid in assessing its impact on the seafloor.

Geochemistry & Geophysics↗
DOE OSTI2021

Identifying geological structures through microseismic cluster and burst analyses complementing active seismic interpretation

At the Decatur carbon capture and storage site (IL, USA) CO 2 has been injected from 2011–2014 and from 2017 to present near the base of the Lower Mt. Simon Sandstone saline reservoir, resulting in microseismicity. Microseismicity is mainly located in the basement and distributed in distinct spatial clusters. The lack of significant impedance contrasts within the basement makes the interpretation of active-source seismic reflection data challenging, however, recent reprocessing allowed to resolve faults above and at the top of the basement. These faults generally do not coincide with the location of microseismic events and their continuation to the general depth of the seismic events cannot be assumed. This paper shows how the interpretation of the microseismicity can complement structural interpretations of active-source seismic reflection data. In particular, we analyze clusters and bursts (abrupt increases) of microseismicity, identify unresolved, smaller-scale weaknesses and extract statistical parameters. These parameters allow comparisons with the interpreted faults, and with fracture sets intercepted by boreholes. During injection at the Decatur site, the injection pressure was kept far below fracture pressure, nevertheless, seismic events were induced and spread far beyond the expected extent of the CO 2 plume. We argue that local stress transfers related to the CO 2 injection reactivated pre-existing fractures within the critically stressed basement. Finally, we conducted a slip tendency analysis for faults interpreted from active seismic, selected cluster, bursts and nodal planes from focal mechanisms to determine if the interpreted structures are optimally oriented with respect to the stress regime. Our results suggest that the orientation of fractures close to the injection well, generally shows slight deviations from the optimal orientation for slip. This might indicate either slight local deviations of the maximum horizontal stress azimuth from the average direction used in the analysis, or the lack of optimally oriented fractures at this location.

58 GEOSCIENCES↗