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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Estimation of Corn Latent Heat Flux from High Resolution Thermal Imagery

Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A high-resolution record of Late Holocene drought in the eastern Sierra Nevada (California, USA) from June Lake carbonate geochemistry

As historic drought conditions become more common in western North America, Late Quaternary hydroclimate records become vital for putting present anthropogenic conditions into a longer-term context. Here, we establish a high-resolution record of drought for the eastern Sierra Nevada (California) using lacustrine carbonates from well-dated sediment cores. We used oxygen and carbon stable-isotope ratios, combined with high-resolution scanning X-ray fluorescence counts of calcium (Ca) and titanium (Ti), to reconstruct the drought record over the last 4600 years in June Lake. We found elevated δ 18 O and δ 13 C carbonate isotope values coinciding with peaks in both total inorganic carbon and Ca/Ti, suggesting enhanced carbonate precipitation in response to evaporative concentration of lake water. At least six intervals of prolonged (centennial-scale) carbonate deposition were identified, including three pulses during the Late Holocene Dry Period (LHDP; ~3500–2000 cal yr BP), the Medieval Climate Anomaly (~1200–800 cal yr BP), and the Current Warm Period, which began around 100 cal yr BP. This record highlights the complexities of the LHDP, an interval that was more variable at June Lake than has been previously described in regional records.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗
DOE OSTI2023

Capturing high‐resolution digital images for use in forensic document examination

Abstract In the past, pattern disciplines within forensic science have periodically faced criticism due to their subjective and qualitative nature and the perceived absence of research evaluating and supporting the foundations of their practices. Recently, however, forensic scientists and researchers in the field of pattern evidence analysis have developed and published approaches that are more quantitative, objective, and data driven. This effort includes automation, algorithms, and measurement sciences, with the end goal of enabling conclusions to be informed by quantitative models. Before employing these tools, forensic evidence must be digitized in a way that adequately balances high‐quality detail and content capture with minimal background noise imparted by the selected technique. While the current work describes the process of optimizing a method to digitize physical documentary evidence for use in semi‐automated trash mark examinations, it could be applied to assist other disciplines where the digitization of physical items of evidence is prevalent. For trash mark examinations specifically, it was found that high‐resolution photography provided optimal digital versions of evidentiary items when compared to high‐resolution scanning.

Riley, Paige↗
DOE OSTI2024

High‐Resolution Direct Push NMR Tools for Groundwater Investigations

Abstract A small‐diameter nuclear magnetic resonance (NMR) technology optimized for use with direct push (DP) and cone penetrometer test (CPT) drilling has been developed. The DP NMR tool can be deployed through 2.25‐in. diameter DP and CPT drilling rods allowing high‐resolution NMR logging measurements to be acquired during retraction of drill rods. DP NMR technology runs from a person‐portable battery‐powered control unit and provides significantly higher resolution in both the spatial (vertical) dimension and in the time domain of the NMR measurement than previously available NMR technology. In this study, we summarize the development of two different DP NMR tools and demonstrate their application at different sites within the United States. We believe that this technology can provide a leap forward in adoption of NMR technology for high‐resolution hydrological and geophysical investigations in groundwater resources and environmental remediation applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A high-resolution clock phase shifter circuitry for ALTIROC

Abstract A high-resolution clock phase shifter is implemented to adjust the phase of multiple clocks at 40 MHz, 80 MHz, or 640 MHz in the ALTIROC chip. The phase shifter has a coarse-phase shifter and a fine-phase shifter to achieve a step size of 97.7 ps and an adjustable range of 25 ns. The fine delay unit is based on a Delay Locked Loop (DLL) operating at 640 MHz. The phase shifter is fabricated in a 130 nm CMOS process. The area of the phase shifter is 725 µm × 248 µm. The Differential Non-Linearity (DNL) and the Integral Non-Linearity (INL) are ±0.6 LSB and ±0.75 LSB, respectively. The jitter from −25 °C to 20 °C is less than 15.5 ps (RMS), including the contributions from the FPGA clock source and the PLL. The power consumption is 11.2 mW.

Instruments & Instrumentation↗
DOE OSTI2025

Topography of Fermi arcs in 𝑡−PtBi 2 using high-resolution angle-resolved photoemission spectroscopy

Here, we use high-resolution angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT) to investigate the electronic structure of trigonal phase PtBi 2 (𝑡 −PtBi 2 ), a proposed Weyl semimetal that is expected to exhibit topological Fermi arcs. Our ARPES data elucidates the topography of these objects and confirms their Fermi arc character. The arcs are formed by surface bands that have fairly flat bottoms located very close to the chemical potential ∼ 6–8 meV, before they merge with bulk bands at higher binding energy. Comparison of the ARPES data with DFT calculations shows good agreement about their location and topography. Data acquired at low temperatures does not show any signatures of superconductivity down to 3 K in terms of expected changes in dispersion due to formation of Bogoliubov quasiparticles or superconducting gap in the form of reliable shifts of peaks in energy distribution curves.

Fermi surface↗
DOE OSTI2021

Developing High-Resolution Constrained Variational Analysis of Vertical Velocity and Advective Tendencies within the Range of ARM Scanning Radars at the SGP

Research progress has been made in two areas. One is about the incorporation of the ARM variationally constrained objective analysis method into the WRF GSI data assimilation system. The other is the development of high resolution ARM data and its applications. Specially, we developed a new data assimilation algorithm by adding dynamical constraints to the WRF GSI data assimilation system using hybrid ensemble variational system to derive 3-D fields of atmospheric dynamics and thermodynamics over the ARM SGP sites. We also developed 4x4 km high-resolution constrained variational analysis data over the SGP during the PECAN and made them available to the community. Details are in the attached report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Efficient boundary-guided scanning for high-resolution X-ray ptychography

In the realm of X-ray ptychography experiments, a considerable amount of ptychography scans are typically performed within a field of view encompassing the target sample. While it is crucial to obtain overlapping scans in small increments over the region of interest for achieving high-resolution sample reconstruction, a significant number of these scans often redundantly measure the empty background within the wide field of view. To address this inefficiency, an innovative algorithm is proposed that introduces automatic guidance for data acquisition. The algorithm first directs the scan point to actively search for the object of interest within the field of view. Subsequently, it intelligently scans along the perimeter of the sample, strategically acquiring measurements exclusively within the boundary of the region of interest. By employing this approach, a reduction in the number of measurements required to obtain high-resolution reconstruction images is demonstrated, as compared with conventional raster scanning methods. Furthermore, the automatic guidance provided by the algorithm offers the added advantage of saving valuable time during the reconstruction process. Through practical implementation on real experiments, these findings showcase the efficacy of the proposed algorithm in enhancing the efficiency and accuracy of X-ray ptychography experiments. This novel approach holds immense potential for advancing sample analysis and imaging techniques in various scientific disciplines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
DOE OSTI2022

Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data

Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.

58 GEOSCIENCES↗
DOE OSTI2023

A plano–convex thick-lens velocity map imaging apparatus for direct, high resolution 3D momentum measurements of photoelectrons with ion time-of-flight coincidence

Since their inception, velocity map imaging (VMI) techniques have received continued interest in their expansion from 2D to 3D momentum measurements through either reconstructive or direct methods. Recently, much work has been devoted to the latter of these by relating electron time-of-flight (TOF) to the third momentum component. The challenge is having a timing resolution sufficient to resolve the structure in the narrow (<10 ns) electron TOF spread. Here, we build upon the work in VMI lens design and 3D VMI measurement by using a plano–convex thick-lens (PCTL) VMI in conjunction with an event-driven camera (TPX3CAM) providing TOF information for high resolution 3D electron momentum measurements. We perform simulations to show that, with the addition of a mesh electrode to the thick-lens geometry, the resulting plano–convex electrostatic field extends the detectable electron cutoff energy range while retaining the high resolution. This design also extends the electron TOF range, allowing for a better momentum resolution along this axis. We experimentally demonstrate these capabilities by examining above-threshold ionization in xenon, where the apparatus is shown to collect electrons of energy up to ∼7 eV with a TOF spread of ∼30 ns, both of which are improved compared to a previous work by factors of ∼1.4 and ∼3.75, respectively. Finally, the PCTL-VMI is equipped with a coincident ion TOF spectrometer, which is shown to effectively extract unique 3D momentum distributions for different ionic species in a gas mixture. These techniques have the potential to lend themselves to more advanced measurements involving systems where the electron momentum distributions possess non-trivial symmetries.

Instruments & Instrumentation↗
DOE OSTI2022

Sea Ice Rheology Experiment (SIREx): 2. Evaluating Linear Kinematic Features in High-Resolution Sea Ice Simulations

Simulating sea ice drift and deformation in the Arctic Ocean is still a challenge because of the multiscale interaction of sea ice floes that compose the Arctic Sea ice cover. The Sea Ice Rheology Experiment (SIREx) is a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). In SIREx, skill metrics are designed to evaluate different recently suggested approaches for modeling linear kinematic features (LKFs) to provide guidance for modeling small-scale deformation. These LKFs are narrow bands of localized deformation that can be observed in satellite images and also form in high resolution sea ice simulations. In this contribution, spatial and temporal properties of LKFs are assessed in 36 simulations of state-of-the-art sea ice models and compared to deformation features derived from the RADARSAT Geophysical Processor System. All simulations produce LKFs, but only very few models realistically simulate at least some statistics of LKF properties such as densities, lengths, or growth rates. All SIREx models overestimate the angle of fracture between conjugate pairs of LKFs and LKF lifetimes pointing to inaccurate model physics. The temporal and spatial resolution of a simulation and the spatial resolution of atmospheric boundary condition affect simulated LKFs as much as the model's sea ice rheology and numerics. Only in very high resolution simulations (≤2 km) the concentration and thickness anomalies along LKFs are large enough to affect air-ice-ocean interaction processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Assessment of the associated particle technique with high-resolution gamma-ray spectroscopy for in-field identification of chemical warfare agents and explosives

In this work, high-resolution prompt γ-ray neutron activation analysis (PGNAA) is performed using the associated particle (AP) technique with a deuterium-tritium neutron generator and high-purity germanium detector. Although the time resolution is inferior compared to similar systems employing fast scintillation γ-ray detectors, the strong background suppression combined with the high γ-ray energy resolution provides an important boost in sensitivity to certain key elements, especially relevant to field measurements of complex chemicals encased within thick layers of metal, such as in the case of recovered chemical warfare (CW) munitions. Results for various CW and explosive simulants contained within mock munitions are presented and compared with results obtained from traditional PGNAA measurements without the aid of the AP technique. Significant improvements in identification and discrimination between certain chemicals are achieved with the high energy resolution AP technique.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Evaluation of extreme sub-daily precipitation in high-resolution global climate model simulations

We examine the resolution dependence of errors in extreme sub-daily precipitation in available high-resolution climate models. We find that simulated extreme precipitation increases as horizontal resolution increases but that appropriately constructed model skill metrics do not significantly change. We find little evidence that simulated extreme winter or summer storm processes significantly improve with the resolution because the model performance changes identified are consistent with expectations from scale dependence arguments alone. We also discuss the implications of these scale-dependent limitations on the interpretation of simulated extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Many current gridded surface meteorological datasets are inadequate for quantifying near surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.

54 ENVIRONMENTAL SCIENCES↗