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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Flow visualization and quantitative velocity and pressure measurements in simulated single and double brush seals

A method to visualize and characterize the complex flow fields in simulated single and double brush seals is presented. The brush seal configuration was tested in a gravity fed water tunnel and a pump driven pressurized oil tunnel. Visualization of the flow field revealed regions that are characteristically river jetting, vortical, crossflow and exist upstream, downstream or within the seal. Such flows are especially engendered by variations in fiber void that are spatial and temporal and affect changes in seal leakage and stability. While the effects of interface motion and cylindrical configuration have not been considered herein, it is believed that the observed flow fields and pressure drop patterns characterize flow phenomenology in brush seals. The axial pressure profiles upstream, across and downstream of the brush have been measured under a variety of inlet pressure conditions and the ensuing pressure maps are presented and discussed. Through the application of the Full Flow Field Tracking method developed by the authors, the flow patterns and the accompanying fluid velocities inside the brush were non-intrusively determined and graphically reconstructed.

Braun, M. J.↗
NASA NTRS1993

Calibration of a synthetic aperture radiometer

Calibration algorithms for a synthetic aperture microwave radiometer are presented. The calibration is geared to Earth remote sensing applications, and is demonstrated on an airborne prototype of thinned array imager. Two approaches to the system calibration are presented; the first utilizes commonly available reference brightness temperature scenes, such as open water, and the second utilizes data collected on the antenna range. Both algorithms yield spatial response information which is cast in matrix form and inverted to obtain the image reconstruction formula. Experimental results are examined, and errors in some reconstructed images are linked to the present prototype antenna design. Algorithms for improving the synthesized antenna pattern side lobe performance are also presented. In one solution, the pattern efficiency is optimized by minimizing the pattern outside a defined beam. In another solution, the patterns are matched to a desired model pattern by the method of least squared errors. Both techniques offer an attractive alternative to aperture weighting.

Tanner, Alan B.↗
NASA NTRS1999

Review of historical monitoring data on Techa River contamination

The Mayak Production Association was the first Russian site for the production and separation of plutonium. The extensive increase in plutonium production during 1948-1955, as well as the absence of reliable waste-management technology, resulted in significant releases of liquid radioactive effluent into the rather small Techa River. This resulted in chronic external and internal exposure of about 30,000 residents of riverside communities; these residents form the cohort of an epidemiologic investigation. Analysis of the available historical monitoring data indicates that the following reliable data sets can be used for reconstruction of doses received during the early periods of operation of the Mayak Production Association: Temporal pattern of specific beta activity of river water for several sites in the upper Techa region since July 1951; average annual values of specific beta activity of river water and bottom sediments as a function of downstream distance for the whole river since 1951; external gamma-exposure rates near the shoreline as a function of downstream distance for the whole Techa River since 1952; and external gamma-exposure rate as a function of distance from the shoreline for several sites in the upper and middle Techa since 1951.

NASA Discipline Radiation Health↗
DOE OSTI2026

Make the Fastest Faster: Importance Mask Synthesis for Interactive Volume Visualization using Reconstruction Neural Networks

Visualizing a large-scale volumetric dataset with high resolution is challenging due to the substantial computational time and space complexity. Recent deep learning-based image inpainting methods significantly improve rendering latency by reconstructing a high-resolution image for visualization in constant time on GPU from a partially rendered image where only a portion of pixels go through the expensive rendering pipeline. However, existing solutions need to render every pixel of either a predefined regular sampling pattern or an irregular sample pattern predicted from a low-resolution image rendering. Both methods require a significant amount of expensive pixel-level rendering. In this work, we provide Importance Mask Learning (IML) and Synthesis (IMS) networks, which are the first attempts to directly synthesize important regions of the regular sampling pattern from the user’s view parameters, to further minimize the number of pixels to render by jointly considering the dataset, user behavior, and the downstream reconstruction neural network. Our solution is a unified framework to handle various types of inpainting methods through the proposed differentiable compaction/decompaction layers. Experiments show our method can further improve the overall rendering latency of state-of-the-art volume visualization methods using reconstruction neural network for free when rendering scientific volumetric datasets. Our method can also directly optimize the off-the-shelf pre-trained reconstruction neural networks without elongated retraining.

Large-scale data↗
DOE OSTI2023

Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network

The relationships between porous microstructures and transport properties are of fundamental importance in various scientific and engineering applications. Due to the intricacy, stochasticity and heterogeneity of porous media, reliable characterization and modeling of transport properties often require a complete dataset of internal microstructure samples. However, it is often an unbearable cost to acquire sufficient 3D digital microstructures by purely using microscopic imaging systems. Herein this paper presents a machine learning-based technique to hierarchically reconstruct 3D well-connected porous microstructures from one isotropic or several anisotropic low-cost 2D exemplar(s). To compactly characterize the large-scale microstructural features, a Gaussian image pyramid is built for each 2D exemplar. Local morphology patterns are collected from the Gaussian image pyramids, and then they serve as the training data to embed the 2D morphological statistics into feed-forward neural networks at multiple length levels. By using a specially-developed morphology integration scheme, the 3D morphological statistics at different levels can be inferred from the statistics-informed neural networks. Gibbs sampling is adopted to hierarchically reconstruct 3D microstructures by using multi-level 3D morphological statistics, where the large-scale, regional and local morphological patterns are statistically generated and successively added to the same 3D random field. The proposed method is tested on a series of porous media with distinct morphologies, and the statistical equivalence between the reconstructed and the real microstructures is systematically evaluated by comparing morphological descriptors and transport properties. The results demonstrate that the proposed 2D-to-3D microstructure reconstruction method is a universal and efficient approach to generating morphologically and physically realistic samples of porous media.

42 ENGINEERING↗
DOE OSTI2025

Travelling wave‐based fault detection and location in a real low‐voltage DC microgrid

Abstract This paper discusses a device‐level implementation of a travelling wave (TW) protection device (PD) designed for a real low‐voltage DC microgrid. The TWPD fault detection and location algorithm is executed on a commercial digital signal processor (DSP) board, involving signal sampling at 1 MHz via the DSP board's analog‐to‐digital converter (ADC). The analogue input card measures positive pole, negative pole and pole‐to‐pole voltages at the TWPD location. Upon a successful fault detection using a second‐order high‐pass filter, the voltage data is normalised and multi‐resolution analysis (MRA) is performed on a 128‐sample buffer around the TW arrival time. MRA employs the discrete wavelet transform (DWT) to capture high‐frequency voltage patterns, and then the Parseval's energy theorem quantifies these TW characteristics by computing the energy of reconstructed wavelet coefficients. These energy values per decomposed frequency band are the basis for training a random forest classifier that predicts fault location and type. The TWPD is fully implemented and connected to a real DC microgrid in Albuquerque, NM, USA, for validation, and results are shown for field tests verifying the performance under faults.

Paruthiyil, Sajay Krishnan [Department of Electric↗
NASA NTRS2015

Improving AIRS Radiance Spectra in High Contrast Scenes Using MODIS

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 microns with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS is designed to measure temperature and water vapor profiles for improvement in weather forecast accuracy and improved understanding of climate processes. As with most instruments, the AIRS Point Spread Functions (PSFs) are not the same for all detectors. When viewing a non-uniform scene, this causes a significant radiometric error in some channels that is scene dependent and cannot be removed without knowledge of the underlying scene. The magnitude of the error depends on the combination of non-uniformity of the AIRS spatial response for a given channel and the non-uniformity of the scene, but is typically only noticeable in about 1% of the scenes and about 10% of the channels. The current solution is to avoid those channels when performing geophysical retrievals. In this effort we use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument to provide information on the scene uniformity that is used to correct the AIRS data. For the vast majority of channels and footprints the technique works extremely well when compared to a Principal Component (PC) reconstruction of the AIRS channels. In some cases where the scene has high inhomogeneity in an irregular pattern, and in some channels, the method can actually degrade the spectrum. Most of the degraded channels appear to be slightly affected by random noise introduced in the process, but those with larger degradation may be affected by alignment errors in the AIRS relative to MODIS or uncertainties in the PSF. Despite these errors, the methodology shows the ability to correct AIRS radiances in non-uniform scenes under some of the worst case conditions and improves the ability to match AIRS and MODIS radiances in non-uniform scenes.

spatial↗
DOE OSTI2020

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Flat Bands and Chiral Optical Response of Moiré Insulators

Here, we present a low-energy model describing the reconstruction of the electronic spectrum in twisted bilayers of honeycomb crystals with broken sublattice symmetry. The resulting moiré patterns are classified into two families with different symmetry. In both cases, flat bands appear at relatively large angles without any magic-angle condition. Transitions between them give rise to sharp resonances in the optical absorption spectrum at frequencies well below the gap of the monolayer. Owing to their chiral symmetry, twisted bilayers display circular dichroism, that is, different absorption of left and right circularly polarized light. This optical activity is a nonlocal property determined by the stacking. In hexagonal boron nitride, sensitivity to the stacking leads to strikingly different circular dichroism in the two types of moirés. Our calculations exemplify how subtle properties of the electronic wave functions, encoded in current correlations between the layers, control physical observables of moiré materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Potential of Attosecond Coherent Diffractive Imaging

Attosecond science has been transforming our understanding of electron dynamics in atoms, molecules, and solids. However, to date almost all of the attoscience experiments have been based on spectroscopic measurements because attosecond pulses have intrinsically very broad spectra due to the uncertainty principle and are incompatible with conventional imaging systems. In this paper we report an important advance towards achieving attosecond coherent diffractive imaging. Using simulated attosecond pulses, we simultaneously reconstruct the spectrum, 17 probes, and 17 spectral images of extended objects from a set of ptychographic diffraction patterns. We further confirm the principle and feasibility of this method by successfully performing a ptychographic coherent diffractive imaging experiment using a light-emitting diode with a broad spectrum. We believe this work clears the way to an unexplored domain of attosecond imaging science, which could have a far-reaching impact across different disciplines.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Search for the chiral magnetic effect through beam energy dependence of charge separation using event shape selection

High-energy, heavy-ion collisions can create local domains of chirality-imbalanced quarks, reflecting the topological features of quantum chromodynamics. The chiral magnetic effect (CME) predicts an electric charge separation of quarks in such topological domains along the magnetic field ($\vec{B}$) generated by the passing of two high-Z nuclei. Here, we use a correlation observable Δ⁢𝛾$^{112}$ between charged meson pairs to detect the CME-induced charge separation and a novel event shape selection (ESS) method to mitigate the background effects related to elliptic flow (𝑣 2 ). The ESS method classifies events based on the emission pattern of final-state particles and determines Δ⁢𝛾$^{112}_{ESS}$ from the zero-flow limit. We reconstruct the $\vec{B}$ field direction from the spectator nucleons, which minimizes backgrounds unrelated to the collective motion of the system. In this work, we report the measurements of Δ⁢𝛾$^{112}$ and a background indicator Δ⁢𝛾$^{132}$ in Au+Au collisions from the Brookhaven National Laboratory Relativistic Heavy Ion Collider (RHIC) Beam Energy Scan phase II and at the top RHIC energy. After background suppression, Δ⁢𝛾$^{132}_{ESS}$ aligns with zero, and Δ⁢𝛾$^{112}_{ESS}$ is reduced to no more than 20% of Δ⁢𝛾$^{112}$. We observe a finite residual charge separation with 2.5⁢𝜎, 3⁢𝜎, and 3.2⁢𝜎 significance in the 20–50% centrality range of Au + Au collisions at 11.5, 14.6, and 19.6 GeV. The results at 17.3 and 27 GeV also show positive values but with a lower significance of 1.3⁢𝜎 and 1.1⁢𝜎, respectively. The corresponding Δ⁢𝛾$^{112}_{ESS}$ values at 7.7, 9.2, and 200 GeV are consistent with zero within uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Coded-mask-based X-ray phase-contrast and dark-field imaging

Phase contrast and dark-field X-ray imaging enable imaging of objects that absorb or reflect very little X-ray light. Disclosed is a method and systems for performing coded-mask-based multi-contrast imaging (CMMI). The method includes providing radiation to a coded mask that has a known phase and absorption profile according to a pre-determined pattern. The radiation is then impingent upon a sample, and the radiation is detected to perform phase-reconstruction and image processing. The method and associated systems allow for the use of maximum-likelihood and machine learning methods for reconstruction images of the sample from the detected radiation.

Shi, Xianbo↗
DOE OSTI2026

Tree-ring evidence marks year 2022 as the driest spring season in nearly four centuries in the Western Himalayas

The Hindukush-Karakoram-Himalayan region is a crucial freshwater source for billions across South Asia, yet its climate remains poorly understood due to limited long-term records. Winter and spring precipitation govern snow accumulation and downstream water availability in dry months particularly across the Western Himalayas (WH), but recent decades show intensifying droughts with unclear long-term context. Here, we have reconstructed a nearly four-century-long spring i.e. February to May (FMAM) precipitation for the Lahaul region of the (WH), an area dominated by the Western Disturbances. This record was developed using moisture-sensitive Cedrus deodara (Deodar) tree-rings from three high-elevation sites. A regional composite tree-ring-width chronology, developed through a Nested Principal Component Analysis and modeled with a nonlinear Generalized Additive Model (GAM) that explains 71 % of the variance during the calibration period. We identified the last two decades as the most precipitation deficit phase and the year 2022 showing the driest FMAM on record. The observed rise in the FMAM dry episodes post 1999 CE in our reconstruction, corresponds to the meteorological records. This recent drying is linked to a northward shift of the subtropical westerly jet and reduced moisture transport, both associated with unusual sea surface temperature patterns in the tropical Indian Ocean and the Western Pacific Ocean. Our results provide compelling evidence of long-term hydroclimatic instability in the WH and emphasize the value of tree-ring records in extending precipitation histories beyond the instrumental observations. Such reconstructions can be benchmarks to validate high-resolution climate models and formulate adaptation policies to mitigate future risks.

Cedrus deodara↗
DOE OSTI2025

Paleoclimatic implications of glacial fluctuations in the Sierra Nevada del Cocuy, northern Andes, Colombia, during the Lateglacial and Holocene

The reconstruction of former mountain glaciers from geomorphic mapping and cosmogenic-nuclide surface-exposure dating provides a unique opportunity to infer patterns of past terrestrial climate variability. Tropical mountain glaciers are particularly valuable as there are comparatively few terrestrial climate proxies at equatorial latitudes relative to higher latitudes. As the single largest climate zone on Earth, the tropics play an outsized role in mediating global climate via the ocean-atmosphere transfer of latent heat and water vapor. Nonetheless, there remains a persistent gap in our understanding of how the tropics influenced – or were influenced by – the high-magnitude climate shifts of the Late Pleistocene, and whether this high-energy region simply responded to extratropical forcing or was itself a driver of global climatic change. To help address this knowledge gap, we analyzed geologic evidence for past glacial fluctuations in three adjacent valleys in the Sierra Nevada del Cocuy, the highest subrange of the Eastern Cordillera in the Colombian Andes, to provide a terrestrial record of atmospheric temperature during the latter part of Termination 1. Coupled with geomorphic mapping and paleo-snowline reconstructions, our beryllium-10 glacial chronology indicates that glaciers in the humid inner tropics underwent pronounced growth and gradual decay during the Antarctic Cold Reversal (14.5–12.8 ka) and Younger Dryas (12.8–11.7 ka) periods, respectively, following a trend that, according to directly dated moraine records from throughout both polar hemispheres, appears to have been global. While the specific mechanism(s) behind this large-scale behavior remains to be corroborated, we revisit the hypothesis that ocean-atmosphere heat transfer and water vapor flux are key drivers of abrupt Lateglacial temperature fluctuations. Subsequent to the Lateglacial, deglaciation of the Sierra Nevada del Cocuy accelerated during the Early Holocene, a pattern also observed in other tropical glacier records. More recently, the magnitude of snowline rise and glacier retreat over the last two centuries supports the view that modern tropospheric warming is anomalously strong at least relative to the last ∼16,000 years.

Andes↗
DOE OSTI2020

Oxygen Adsorption, Subsurface Oxygen Layer Formation and Reaction with Hydrogen on Surfaces of a Pt–Rh Alloy Nanocrystal

The oxygen adsorption and its catalytic reaction with hydrogen on Pt–Rh single crystals were studied at the nanoscale by Field Emission Microscopy (FEM) and Field Ion Microscopy (FIM) techniques at 700 K. Both FEM and FIM use samples prepared as sharp tips, apexes of which mimic a single nanoparticle of catalyst considering their similar size and morphology. Oxygen adsorption on Pt-17.4 at.%Rh samples leads to the formation of subsurface oxygen, which is manifested in the field emission (FE) patterns: for O2 exposure of ~3 Langmuir (L), {113} planes appear bright in the emission pattern, while for higher oxygen doses, i.e. 84 L, the bright regions correspond to the high index planes between the {012} and {011} planes. Formation of subsurface oxygen is probably accompanied by a surface reconstruction of the nanocrystal. The subsurface oxygen can be effectively reacted off by subsequent exposure of the sample to hydrogen gas at 700 K. The hydrogenation reaction was observed as a sudden, eruptive change of the brightness seen on the FE pattern. This reaction resulted in the recovery of the initial field emission pattern characteristic of a clean tip, with {012} facets being the most visible. It was shown that the oxygen accumulation-reduction process is completely reversible. The obtained results indicate that the presence of subsurface species must be considered in the description of reactive processes on Pt–Rh catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Structural Phase Transitions of NbO 2 : Bulk versus Surface

The metal to insulator transition of NbO 2 has been predicted to be a result of a structural phase transition (SPT) governed by Peierls physics. However, direct observation of the SPT using experimental techniques is still restricted by the extremely high transition temperature (810 °C) and the proclivity for NbO 2 to oxidize into Nb 2 O 5 above 400 °C when exposed to air. In this work, we address these issues and employ temperature-dependent X-ray spectroscopy to describe the SPT of NbO 2 from the bulk to surface. Temperature-dependent extended X-ray absorption fine structure spectroscopy (T-EXAFS) reveals a gradual weakening of the bulk Nb dimers over a large temperature range, which is indicative of a second-order Peierls mechanism. From these measurements, we determine the critical dimer distance to be 2.77 Å. Our T-EXAFS observations are supported by density functional theory of the phonon dispersion and the electronic density of states of NbO 2 , which conclude that the dimerization is responsible for the insulating phase. The dimerization does not extend to the topmost layers, where an oxygen rich surface reconstruction is preferred irrespective of temperature even in extremely reducing environments; changes in the low-energy electron diffraction patterns are attributed to oxygen concentration and are independent of the underlying bulk phase transitions of NbO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Three-Dimensional Settling Dynamics of Environmental Microplastics

Resolving the three-dimensional settling dynamics of microplastic (MP) particles is essential for developing comprehensive models of MP transport in rivers-both vertically within the water column and laterally across the channel. While previous research has largely examined one-dimensional vertical settling velocities, little is known about the lateral drifting, settling paths, and horizontal velocities of MPs. To address this, we investigated the full three-dimensional settling behavior of environmental MPs collected from rivers and ocean water, as well as from estuarine and ocean sediment. Geometric properties of 127 environmental MPs were quantified by a dynamic particle image analyzer, and their settling trajectories were recorded and reconstructed via a multicamera tracking algorithm. This enabled quantification of a particle's horizontal drift, tortuosity, amplitude and settling pattern, as well as vertical and horizontal velocities. Results showed that spherical MPs settled with minimal lateral displacement, whereas elongated particles, such as rod- and blade-shaped MPs, displayed pronounced lateral movements, reaching up to 65 times their equivalent diameter and averaging more than twice that of spheres. These dynamics suggest that elongated MPs may have a greater probability for wider lateral dispersion in rivers, increasing their likelihood for interactions with riverbanks and channel boundaries compared to more spherical shaped MPs.

54 ENVIRONMENTAL SCIENCES↗