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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

PyDDA: A Pythonic Direct Data Assimilation Framework for Wind Retrievals

This software assimilates data from an arbitrary number of weather radars together with other spatial wind fields (eg numerical weather forecasting model data) in order to retrieve high resolution three dimensional wind fields. PyDDA uses NumPy and SciPy’s optimization techniques combined with the Python Atmospheric Radiation Measurement (ARM) Radar Toolkit (Py-ART) in order to create wind fields using the 3D variational technique (3DVAR). PyDDA is hosted and distributed on GitHub at https://github.com/openradar/PyDDA. PyDDA has the potential to be used by the atmospheric science community to develop high resolution wind retrievals from radar networks. These retrievals can be used for the evaluation of numerical weather forecasting models and plume modelling. This paper shows how wind fields from 2 NEXt generation RADar (NEXRAD) WSR-88D radars and the High Resolution Rapid Refresh can be assimilated together using PyDDA to create a high resolution wind field inside Hurricane Florence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A modeling study of ocean thermal energy conversion resource and potential environmental effects around Kailua-Kona, Hawaii

Ocean Thermal Energy Conversion (OTEC) offers a promising renewable energy solution through a heat exchange process using the temperature difference between warm surface seawater and cold deep seawater. Because accurate resource characterization is critical for the optimal design and implementation of OTEC systems, a high-resolution numerical model is employed to better characterize the OTEC resource at Kona, Hawaii. Our model provides detailed spatial and temporal variability of the thermal gradient, which is essential for assessing the viability and efficiency of OTEC systems. The model results reveal distinct patterns and dynamics not captured by existing observations or models (e.g., lower-resolution information). These findings highlight the importance of using high-resolution models for accurate predictions of thermal gradient variability, ultimately supporting more efficient and sustainable OTEC deployment. Additionally, the study investigates the impacts of mixed water discharge from OTEC plants that can cause shock to organisms living in the surface water and potentially destabilize the water column. Understanding these effects is vital for minimizing any potential negative environmental consequences and ensuring the long-term viability of OTEC operations. Further, our model improves OTEC resource characterization, which can lead to optimal design and deployment of OTEC systems. The analysis of OTEC water discharge impacts can accelerate the development of OTEC technologies, overcoming permitting/consenting challenges. These findings contribute to the broader adoption of high-resolution modeling in ocean energy resource characterization, particularly for OTEC applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Study of SXR/EUV radiation of exploded foils and wires with spectral, spatial and temporal resolution simultaneously on KING electric discharge facility.

The results of studies of the soft X-ray and extreme ultraviolet (SXR/EUV) radiation of thin flat aluminum foils and wires under the explosion in an electric discharge on the compact high-current KING generator are presented. These studies were based on the SXR/EUV spectroscopy with a spectral resolution of 6 Å, a temporal resolution of 5 ns and a spatial resolution of 200 μm. To study the plasma radiation of exploded foils and wires in the SXR/EUV range, we used a transmission diffraction grating spectrograph which in combination with two additional slits provided spectral and spatial resolution. The spectrograph was coupled with a 4-frame recorder based on a microchannel plate for providing temporal resolution. The analysis and comparison of the spectral, spatial, temporal, and energy characteristics of the SXR/EUV radiation of plasma formed under the explosion of foils and wires of a similar mass made of aluminum was carried out. Here, the spectra were calculated as well and the plasma parameters and their changes in time and space were estimated on the basis of these calculations and comparison with relevant experimental results. Experiments have shown that when foils explode, a single intense source of SXR/EUV radiation is formed with radiated energy in the range of 10-20 J and a power of up to 100 MW in the quantum energy range from 30 to 250 eV. At the same time, the radiation power under the explosion of foils turned out to be about twice above the power under the explosion of wires of comparable mass.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2.5D Super-Resolution Approaches for X-Ray Computed Tomography-Based Inspection of Additively Manufactured Parts

X-ray computed tomography (XCT) is a key tool in non-destructive evaluation of additively manufactured (AM) parts, allowing for internal inspection and defect detection. Despite its widespread use, obtaining high-resolution CT scans can be extremely time consuming. This issue can be mitigated by performing scans at lower resolutions; however, reducing the resolution compromises spatial detail, limiting the accuracy of defect detection. Super-resolution algorithms offer a promising solution for overcoming resolution limitations in XCT reconstructions of AM parts, enabling more accurate detection of defects. While 2D super-resolution methods have demonstrated state-of-the-art performance on natural images, they tend to under-perform when directly applied to XCT slices. On the other hand, 3D super-resolution methods are computationally expensive, making them infeasible for large-scale applications. To address these challenges, we propose a 2.5D super-resolution approach tailored for XCT of AM parts. Our method enhances the resolution of individual slices by leveraging multi-slice information from neighboring 2D slices without the significant computational overhead of full 3D methods. Specifically, we use neighboring low-resolution slices to super-resolve the center slice, exploiting inter-slice spatial context while maintaining computational efficiency. This approach bridges the gap between 2D and 3D methods, offering a practical solution for high-throughput defect detection in AM parts.

Sullivan, Haley↗
DOE OSTI2024

The National Climate Database (NCDB): An Unbiased 100-Year Dataset for PV Modeling

In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.

bias correction↗
DOE OSTI2025

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗
DOE OSTI2022

What you get is not always what you see—pitfalls in solar array assessment using overhead imagery

Effective integration planning for small, distributed solar photovoltaic (PV) arrays into electric power grids requires access to high quality data: the location and power capacity of individual solar PV arrays. Unfortunately, national databases of small-scale solar PV do not exist; those that do are limited in their spatial resolution, typically aggregated up to state or national levels. While several promising approaches for solar PV detection have been published, strategies for evaluating the performance of these models are often highly heterogeneous from study to study. The resulting comparison of these methods for practical applications for energy assessments becomes challenging and may imply that the reported performance evaluations overly optimistic. The heterogeneity comes in many forms, each of which we explore in this work: the degree of diversity of the locations and sensors (e.g. different satellites, aerial photography) from which the training and validation data originate, the validation of ground truth (manual annotation of imagery vs known solar PV locations), the level of spatial aggregation (e.g. array-level vs regional estimates), and inconsistencies in the training and validation datasets (e.g. different datasets are used for each study and those data are not always made accessible). For each, we discuss emerging practices from the literature to address them or suggest directions of future research. As part of our investigation, we evaluate solar PV identification performance in two large regions: the entire state of Connecticut and the city of San Diego, CA. In Connecticut, we also use 33,114 known parcel-level solar PV installations from Berkeley Lab’s Tracking the Sun dataset to evaluate parcel-level performance and evaluate capacity estimates using 169 municipalities. We also make our code (which we call SolarMapper), pre-trained models, training data, and predictions publicly available and provide a web portal for interactively inspecting each prediction that was made. Here our findings suggest that traditional performance evaluation of the automated identification of solar PV from satellite imagery may be optimistic due to common limitations in the validation process. The takeaways from this work are intended to inform and catalyze the large-scale practical application of automated solar PV assessment techniques by energy researchers and professionals.

14 SOLAR ENERGY↗
DOE OSTI2026

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗
DOE OSTI2023

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images

Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectrometric imaging data of the corresponding tissue to determine the cancerous regions and their unique chemical signatures and variations of the predicted regions with original pathological annotations. We obtain features from high-resolution optical micrographs of whole slide H&E stained data through deep learning and spatially register them with mass spectrometry imaging (MSI) data to correlate the chemical signature with the tissue anatomy of the data. We then use the learned correlation to predict prostate cancer from observed H&E images using trained coregistered MSI data. This multimodal approach can predict cancerous regions with ~80% accuracy, which indicates a correlation between optical H&E features and chemical information found in MSI. Further, we show that such paired multimodal data can be used for training feature extraction networks on H&E data which bypasses the need to acquire expensive MSI data and eliminates the need for manual annotation saving valuable time. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This study shows promise in generating improved patient treatment trajectories by predicting prostate cancer directly from readily available H&E-stained biopsy images aided by coregistered MSI data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Comparing Thermal Neutron Scintillators for Use With SiPM-Readout Detectors

Scintillator-based thermal neutron detectors for scientific scattering facilities offer an effective combination of large-area coverage and good spatial resolution. At Oak Ridge National Laboratory, silicon photomultiplier (SiPM)-readout Anger cameras using 6 Li glass scintillators have been developed, but the spatial resolution of these detectors is limited by the relatively low light yield of the glass. Recently, several brighter scintillator compositions with sufficient 6 Li concentration have emerged as promising candidates for higher-resolution imaging. Here, in this work, we evaluate five scintillator materials: GS20, LiF/ZnS:Ag, LiF/ZnO:Zn, LiI:Eu, and Cs 2 LiYCl 6 :Ce, each mounted on a SiPM Anger camera. For each scintillator, the neutron detection efficiency, spatial resolution, and count rate capabilities were measured and compared. Each of the new compositions achieved a spatial resolution better than 0.5 mm, compared to 0.66 mm for GS20, with LiI:Eu reaching the best value of 0.32 mm. Although these compositions improve the spatial resolution of the Anger camera, their longer pulse decay times limit their use in high count rate applications, and the camera’s hardware must be optimized for the different properties of the new scintillators.

Neutron detectors↗
DOE OSTI2020

Validation of the High-Resolution Salish Sea Tidal Hydrodynamic Model

In this study, a tidal hydrodynamic model was developed and validated to simulate tidal currents in Puget Sound, Washington, to support tidal energy resource characterization using the unstructured-grid, Finite Volume Community Ocean Model (FVCOM). The Salish Sea tidal hydrodynamic model was driven by tides along two open boundaries at the entrance of the Strait of Juan de Fuca and north end of Georgia Strait, and river flows from 19 major rivers in the Salish Sea. To simulate the tidal current in Puget Sound, a high-resolution model grid is required to accurately represent the complex coastlines and bathymetry. The spatial resolution of the model grid varies from ~10 m near river boundaries and ~30 m in small tidal channels and estuaries to near 1000 m inside Georgia Strait and at the open boundaries. Model validation was carried out by comparing simulated and observed water levels at 12 tidal stations and currents at 135 Acoustic Doppler Current Profiler stations in the model domain. A set of model performance metrics, including root mean square error, scatter index, bias, and linear correlation coefficient, were used to quantify the model skills in simulating the tidal hydrodynamics in Puget Sound. Error statistics showed an overall good agreement between simulated and observed tidal elevations and currents, which demonstrated that the Puget Sound tidal model can be used to accurately characterize the tidal stream energy resource in Puget Sound.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

ANNIE: the Accelerator Neutrino Neutron Interaction Experiment

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a Gadolinium-loaded water Cherenkov detector placed in the Booster Neutrino Beam (BNB) at the Fermi National Accelerator Laboratory, USA. The primary physics goal of ANNIE is to perform neutrino cross-section measurements that will constrain systematic uncertainties in the next generation of long-baseline neutrino experiments. The first measurement will be the multiplicity of final-state neutrons from neutrino-nucleus interactions in water. Alongside these measurements, ANNIE has achieved the first ever deployments of two novel detector technologies in a neutrino beam: Large Area Picosecond Photodetectors (LAPPDs) and Water-based Liquid Scintillator (WbLS). LAPPDs are micro-channel-plate-based devices that provide timing resolution of ~100 picoseconds and sub-centimeter spatial resolution. WbLS combines the low attenuation and Cherenkov production of pure water with the high light-yield and low detection threshold of liquid scintillator. This talk will discuss the status of ANNIE's physics and R&D measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

High temperature thick film sensor development based on doped lanthanum chromites refractory semiconductors materials

High temperature advanced sensing materials have generated high demand due the high accuracy temperature measurements requirements for process optimization, controlling and sensing. Some technological applications of harsh conditions sensing include monitoring tiles of space shuttles, rotating bearings in aircraft engines, turbines, jet engines dynamics and chemical reactors. High temperature conditions limit the sensing strategies, where typically traditional metal thermocouples are unstable, and the sensing options are limited to optical spectroscopy methods. Recently, refractory semiconductors thick- and thin-film thermocouples have been developed and, in many cases, preferred over conventional metallic thermocouples due their spatial resolution, and capability of direct deposition on any surface. Rare earth chromites ceramics materials, exhibit some properties of interest for high temperature sensing technologies development, such as: high microstructure and sintering stability, excellent conductive behavior at high temperatures, and matching thermal expansion coefficients relative to other conductors and refractory ceramics. In this work, high performance ultra-high temperature thermocouples using p-type and n-type doped lanthanum chromites materials were fabricated and tested at temperatures up to 1500 o C. Thermoelectric voltage, Seebeck Coefficients were established for all devices, evidencing high stability and performance in prolongated operational time and harsh conditions.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Reduced ecosystem resilience quantifies fine-scale heterogeneity in tropical forest mortality responses to drought

Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, in this study, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one- out cross-validation R 2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine-scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high-resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Neutron Grating Interferometry at the High Flux Isotope Reactor

Neutron imaging is a non-destructive probe that can spatially resolve bulk materials’ internal features/structures. Neutron imaging spatial resolution is driven by detector technology, i.e., pixel size, and is currently on the order of 10–20 µm. This limitation can be alleviated by the use of neutron grating interferometry – an advanced neutron imaging technique – that enables simultaneous access to three contrast mechanisms: attenuation, differential phase, and small-angle neutron scattering. Recently, a Talbot-Lau neutron grating interferometry has been implemented at the Multimodal Advanced Radiography Station at the High Flux Isotope Reactor. In this work, the design, setup and performance of the grating apparatus are presented.

Zhang, Yuxuan [ORNL] (ORCID:0000000200831408)↗
DOE OSTI2022

Electric field determination in transient plasmas: in situ & non-invasive methods

Abstract One of the primary basic plasma parameters within transient nonequilibrium plasmas is the reduced electric field strength, roughly understood as the ratio of the electrical energy given to the charged species between two collisions. While physical probes have historically been used for electric field measurements, recent advances in high intensity lasers and sensitive detection methods have allowed for non-invasive optical electric field determination in nearly any discharge configuration with time-resolution up to the sub-nanosecond range and sub-millimeter spatial resolution. This topical review serves to highlight several non-invasive methods for in situ electric field strength determination in transient plasmas ranging from high vacuum environments to atmospheric pressure and above. We will discuss the advantages and proper implementation of (i) laser induced fluorescence dip spectroscopy for measurements in low pressure RF discharges, (ii) optical emission spectroscopy based methods for nitrogen, helium or hydrogen containing discharges, (iii) electric field induced coherent Raman scattering, and (iv) electric field induced second harmonic generation. The physical mechanism for each method will be described as well as basic implementation and highlighting recent results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗