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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance

Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment is achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

THE SPECIFIC ACCELERATION RATE IN LOOP-STRUCTURED SOLAR FLARES-IMPLICATIONS FOR ELECTRON ACCELERATION MODELS

We analyze electron flux maps based on RHESSI hard X-ray imaging spectroscopy data for a number of extended coronal-loop flare events. For each event, we determine the variation of the characteristic loop length L with electron energy E, and we fit this observed behavior with models that incorporate an extended acceleration region and an exterior 'propagation' region, and which may include collisional modification of the accelerated electron spectrum inside the acceleration region. The models are characterized by two parameters: the plasma density n in, and the longitudinal extent L{sub 0} of, the acceleration region. Determination of the best-fit values of these parameters permits inference of the volume that encompasses the acceleration region and of the total number of particles within it. It is then straightforward to compute values for the emission filling factor and for the specific acceleration rate (electrons s{sup -1} per ambient electron above a chosen reference energy). For the 24 events studied, the range of inferred filling factors is consistent with a value of unity. The inferred mean value of the specific acceleration rate above E{sub 0} = 20 keV is {approx}10{sup -2} s{sup -1}, with a 1{sigma} spread of about a half-order-of-magnitude above and below this value. We compare these values with the predictions of several models, including acceleration by large-scale, weak (sub-Dreicer) fields, by strong (super-Dreicer) electric fields in a reconnecting current sheet, and by stochastic acceleration processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗
DOE OSTI2014

WE-D-9A-01: A Novel Mesh-Based Deformable Surface-Contour Registration

Purpose: Initial guess is vital for 3D-2D deformable image registration (DIR) while dealing with large deformations for adaptive radiation therapy. A fast procedure has been developed to deform body surface to match 2D body contour on projections. This surface-contour DIR will provide an initial deformation for further complete 3D DIR or image reconstruction. Methods: Both planning CT images and come-beam CT (CBCT) projections are preprocessed to create 0–1 binary mask. Then the body surface and CBCT projection body contours are extracted by Canny edge detector. A finite element modeling system was developed to automatically generate adaptive meshes based on the image surface. After that, the projections of the CT surface voxels are computed and compared with corresponding 2D projection contours from CBCT scans. As a result, the displacement vector field (DVF) on mesh vertices around the surface was optimized iteratively until the shortest Euclidean distance between the pixels on the projections of the deformed CT surface and the corresponding CBCT projection contour is minimized. With the help of the tetrahedral meshes, we can smoothly diffuse the deformation from the surface into the interior of the volume. Finally, the deformed CT images are obtained by the optimal DVF applied on the original planning CT images. Results: The accuracy of the surface-contour registration is evaluated by 3D normalized cross correlation increased from 0.9176 to 0.9957 (sphere-ellipsoid phantom) and from 0.7627 to 0.7919 (H and N cancer patient data). Under the GPU-based implementation, our surface-contour-guided method on H and N cancer patient data takes 8 seconds/iteration, about 7.5 times faster than direct 3D method (60 seconds/iteration), and it needs fewer optimization iterations (30 iterations vs 50 iterations). Conclusion: The proposed surface-contour DIR method can substantially improve both the accuracy and the speed of reconstructing volumetric images, which is helpful for applying in adaptive radiotherapy. This research is supported by CPRIT individual investigator award RP110329.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computer vision models and advanced TEM imaging for microstructures of irradiated AM316 stainless steels

Advancements were made in automating microscopy-based material characterization, particularly in studying irradiation effects on additively manufactured (AM) materials using machine learning (ML) and computer vision (CV). These automation efforts address the challenges of analyzing complex microstructures, accelerating the detection of irradiation-induced defects. Two CV models were developed at Argonne National Laboratory (ANL) to enhance transmission electron microscopy (TEM) analysis of irradiated AM 316 stainless steel. The first model focused on the detection of irradiation-induced dislocation loops, which contribute to material hardening and embrittlement. These loops, categorized as faulted or perfect, were automatically detected and classified using a Mask R-CNN model trained on TEM images from both in-situ and ex-situ ion irradiation experiments. The model achieved high accuracy, with precision, recall, and F1 scores of 0.839, 0.734, and 0.776, respectively, demonstrating its effectiveness in analyzing dislocation loops in irradiated AM materials. The second CV model was developed to analyze the size and wall thickness of dislocation cells in laser powder bed fusion (LPBF) 316 stainless steel. Using a U-Net++ architecture with EfficientNet as the encoder, the model was trained on TEM images to segment and measure cell size and wall thickness.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Application of Perona Malik anisotropic diffusion on digital radiographic image

Perona Malik Anisotropic Diffusion (PMAD) is a very useful and efficient denoising technique if the parameters are properly selected. Overestimating the parameters may cause oversmoothed and underestimating it may leave unfiltered noise. This makes the selection of parameters a crucial process. In this paper the PMAD model is solved using a finite difference scheme The discretized model is evaluated using different diffusion coefficient of exponential and quadratic on defective radiographic images in terms of quality and efficiency. In the application of the PMAD model on image data, a set of defective radiographic images of welding is used as input data. Peak Signal to Noise Ratio (PSNR), Structural Similarity Measure (SSIM) and temporal time are used to evaluate the performance of the model. The implementation of the experiment has been carried out using MATLAB R2009a. In terms of quality, results show that the Quadratic Diffusion Coefficient Function (QDCF) provides better results compared with the Exponential Diffusion Coefficient Function (EDCF). In conclusion, the denoising effect using PMAD model based on finite difference scheme shows able to improve image quality by removing noise in the defective radiographic image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Geometry induced sequence of nanoscale Frank–Kasper and quasicrystal mesophases in giant surfactants

Frank–Kasper (F-K) and quasicrystal phases were originally identified in metal alloys and only sporadically reported in soft materials. These unconventional sphere-packing schemes open up possibilities to design materials with different properties. The challenge in soft materials is how to correlate complex phases built from spheres with the tunable parameters of chemical composition and molecular architecture. Here, we report a complete sequence of various highly ordered mesophases by the self-assembly of specifically designed and synthesized giant surfactants, which are conjugates of hydrophilic polyhedral oligomeric silsesquioxane cages tethered with hydrophobic polystyrene tails. We show that the occurrence of these mesophases results from nanophase separation between the heads and tails and thus is critically dependent on molecular geometry. Variations in molecular geometry achieved by changing the number of tails from one to four not only shift compositional phase boundaries but also stabilize F-K and quasicrystal phases in regions where simple phases of spheroidal micelles are typically observed. These complex self-assembled nanostructures have been identified by combining X-ray scattering techniques and real-space electron microscopy images. Brownian dynamics simulations based on a simplified molecular model confirm the architecture-induced sequence of phases. Furthermore, our results demonstrate the critical role of molecular architecture in dictating the formation of supramolecular crystals with “soft” spheroidal motifs and provide guidelines to the design of unconventional self-assembled nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2012

SOURCE-PLANE RECONSTRUCTION OF THE BRIGHT LENSED GALAXY RCSGA 032727-132609

We present new Hubble Space Telescope/Wide Field Camera 3 imaging data of RCSGA 032727-132609, a bright lensed galaxy at z = 1.7 that is magnified and stretched by the lensing cluster RCS2 032727-132623. Using this new high-resolution imaging, we modify our previous lens model (which was based on ground-based data) to fully understand the lensing geometry, and use it to reconstruct the lensed galaxy in the source plane. This giant arc represents a unique opportunity to peer into 100 pc scale structures in a high-redshift galaxy. This new source reconstruction will be crucial for a future analysis of the spatially resolved rest-UV and rest-optical spectra of the brightest parts of the arc.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Feature-based Anomaly Detection System

SAND2022-7963 O The Feature-Based Anomaly Detection System detects anomalies in video data based on features derived from pre-trained image models to avoid the need for training. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hannasch, David↗
DOE OSTI2025

Geochemical Impact of Acid Spearhead and Slickwater Stimulation on Wolfcamp Shale from the Hydraulic Fracturing Test Site

The Hydraulic Fracturing Test Site 1 (HFTS-1) was a field study performed in the Wolfcamp Formation in the West Texas Permian (Midland) Basin, USA, with a focus on improving the efficiency of hydraulic fracturing. Investigating site-specific rock-fluid geochemical interactions during hydraulic fracturing is an important step to understanding the impact on formation shale porosity, permeability, and long-term shale gas production. During field operations in this region, hydraulic fracturing fluid (HFF) injection usually starts with a concentrated acid spearhead for rapid rock dissolution, followed by the injection of near-neutral pH slickwater containing chemicals and proppants. A multistep sequential injection approach was used to investigate different stages of rock-fluid interactions. The carbonate content in the host rock is important when acid spearhead is considered, as carbonate mineral dissolution is rapid and can result in porosity and permeability changes in the shale matrix. Here, in this study, we designed flow-through experiments using fractured carbonate-rich and clay-rich Wolfcamp shale cores with (1) a short-time acid soaking step and (2) a long-term slickwater flow-through step to simulate the injection method used at HFTS-1. The fluid chemistry was analyzed. A thorough mineralogical progression [e.g., Calcium (Ca) dissolution and iron (Fe) redox progression] in the cores during HFF injection was also characterized and imaged by synchrotron microprobe. Reactive transport modeling was performed based on the experimental setup. The results showed that the acid spearhead is a crucial step in creating a reaction front by mineral dissolution, especially in carbonate-rich shales. A slight layer of ferrihydrite precipitated during the slickwater flow-through period. This study provides insights into potential geochemical impact due to hydraulic fracturing operations in the Permian Basin.

clastic rock↗
DOE OSTI2020

Limited-view Cone Beam CT reconstruction using 3D Patch-based Supervised and Adversarial Learning [Slides]

We present a novel machine learning CNN architecture that can learn from limited data combined appropriately with physics and statistical priors (e.g., forward models and noise models). To address the limited availability of training data we adopt a 3D patch-based approach for our models. Patch-based learning is central to several image reconstruction methods and demands fewer training data than DL approaches, as a single data volume can be broken into several millions of overlapping 3D sub-volumes or patches. This creates a very large number of training sub-volumes from a limited number of overall image volumes. A 3D Generative Adversarial Networks (GAN) is then trained to remove artifacts at the sub-volume level. The combination of a sub-volume-based approach with DL allows us to exploit the richness of the latter in extracting and representing image features, while avoiding risks associated with overfitting due to limited training data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Phylogenomic discovery and engineering of nitrogen fixation into the bioenergy woody crop poplar

Biological nitrogen fixation (BNF) is a key process enabling plants in specific lineages to convert atmospheric dinitrogen (N₂) into bioavailable ammonia through symbioses with diazotrophic microbes. Expanding this capability beyond native nitrogen-fixing clades into non-nodulating crops would reduce synthetic fertilizer use, lowering energy inputs and environmental impacts in agriculture. Supported by DOE Funding Award DE-SC0018247, the NitFix project advanced foundational knowledge required to engineer root-nodule symbioses in new host species. The team generated the most comprehensive phylogenomic analysis to date of all known nodulating lineages, resolving the evolutionary history of nitrogen-fixing symbiosis and identifying core gene suites retained across nodulating taxa. Through multimodal genomics, transcriptomics, and functional analyses in Medicago truncatula and related species, the project mapped regulatory networks underlying nodule organogenesis, bacterial infection, and nitrogen-fixation efficiency. Key discoveries include the identification of conserved signaling modules for rhizobial recognition, transcription factors controlling nodule differentiation, and metabolic pathways integrating fixed nitrogen into plant growth. The project also developed enabling tools—including optimized transformation pipelines, gene-editing workflows, and imaging-based phenotyping—to accelerate engineering efforts in emerging models. Together, these results refine the mechanistic framework of symbiotic nitrogen fixation and highlight transferable components essential for rewiring these traits into non-nodulating crops.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Geodesy and cartography

An overview of geodesy and cartography of Mars over the past century is presented. The modern exploration began with the Mariner 4, 6, and 7 flyby missions, followed by the Mariner 9 and Viking missions that mapped the entire surface of Mars. The primary modern changes to the coordinate system have led to improved measurements of the rotational period, the direction of the spin axis, and the size and shape of Mars. Planimetric mapping based on Mariner 9 pictures began with a 1:25-M-scale sheet and 30 1:5-M-scale sheets that covered the entire Martian surface. The quality of the Viking Orbiter pictures was greatly improved over Mariner 9 and led to the publication of 140 controlled photomosaic sheets at a scale of 1:2 M. Two digital data bases have been compiled for Mars - the digital image model and the digital terrain model.

Davies, Merton E.↗
NASA NTRS2011

Source Plane Reconstruction of the Bright Lensed Galaxy RCSGA 032727-132609

We present new HST/WFC3 imaging data of RCS2 032727-132609, a bright lensed galaxy at z=1.7 that is magnified and stretched by the lensing cluster RCS2 032727-132623. Using this new high-resolution imaging, we modify our previous lens model (which was based on ground-based data) to fully understand the lensing geometry, and use it to reconstruct the lensed galaxy in the source plane. This giant arc represents a unique opportunity to peer into 100-pc scale structures in a high redshift galaxy. This new source reconstruction will be crucial for a future analysis of the spatially-resolved rest-UV and rest-optical spectra of the brightest parts of the arc.

Sharon, Keren↗
NASA NTRS2014

How Dusty Is Alpha Centauri? Excess or Non-excess over the Infrared Photospheres of Main-sequence Stars

Context. Debris discs around main-sequence stars indicate the presence of larger rocky bodies. The components of the nearby, solar-type binary Centauri have metallicities that are higher than solar, which is thought to promote giant planet formation. Aims. We aim to determine the level of emission from debris around the stars in the Cen system. This requires knowledge of their photospheres.Having already detected the temperature minimum, Tmin, of CenA at far-infrared wavelengths, we here attempt to do the same for the moreactive companion Cen B. Using the Cen stars as templates, we study the possible eects that Tmin may have on the detectability of unresolveddust discs around other stars. Methods.We used Herschel-PACS, Herschel-SPIRE, and APEX-LABOCA photometry to determine the stellar spectral energy distributions in thefar infrared and submillimetre. In addition, we used APEX-SHeFI observations for spectral line mapping to study the complex background around Cen seen in the photometric images. Models of stellar atmospheres and of particulate discs, based on particle simulations and in conjunctionwith radiative transfer calculations, were used to estimate the amount of debris around these stars. Results. For solar-type stars more distant than Cen, a fractional dust luminosity fd LdustLstar 2 107 could account for SEDs that do not exhibit the Tmin eect. This is comparable to estimates of fd for the Edgeworth-Kuiper belt of the solar system. In contrast to the far infrared,slight excesses at the 2:5 level are observed at 24 m for both CenA and B, which, if interpreted as due to zodiacal-type dust emission, wouldcorrespond to fd (13) 105, i.e. some 102 times that of the local zodiacal cloud. Assuming simple power-law size distributions of the dustgrains, dynamical disc modelling leads to rough mass estimates of the putative Zodi belts around the Cen stars, viz.4106 M$ of 4 to 1000 msize grains, distributed according to n(a) a3:5. Similarly, for filled-in Tmin emission, corresponding Edgeworth-Kuiper belts could account for103 M$ of dust. Conclusions. Our far-infrared observations lead to estimates of upper limits to the amount of circumstellar dust around the stars CenA and B.Light scattered andor thermally emitted by exo-Zodi discs will have profound implications for future spectroscopic missions designed to searchfor biomarkers in the atmospheres of Earth-like planets. The far-infrared spectral energy distribution of Cen B is marginally consistent with thepresence of a minimum temperature region in the upper atmosphere of the star. We also show that an Cen A-like temperature minimum mayresult in an erroneous apprehension about the presence of dust around other, more distant stars.

metallicities↗
NASA NTRSDate not supplied

Comparing Planetary Helicopter Brownout Observations with Numerical Predictions for Ingenuity

Ingenuity is considered the Martian equivalent of the Wright Flyer. Its sustained flights on Mars proved that non-terrestrial powered flight is possible, even on planets with thin atmospheres. However, Ingenuity was small and carried no payload. Future planetary rotorcraft will be bigger and heavier to accomplish new scientific and exploratory goals. On dusty planets, the associated increase in rotor thrust poses a potential challenge well known to helicopter pilots who have flown in desert environments: dust clouds forming during take-off and landing due to rotor wash, referred to as brownout. This work evaluates the effectiveness of existing numerical simulation models in predicting the severity of this phenomenon for planetary rotorcraft. We compare the output of a CFD-based dust mobilization model with data recently gathered using image processing techniques of Ingenuity’s flights. The simulation results suggest that the sensitivity of the wall friction velocity to the rotorcraft height may be lower than previously assessed. We further evaluate the sensitivity of the total mass of mobilized dust to other model parameters such as the sandblasting efficiency and the saltation threshold velocity. Finally, we discuss the limitations of this comparison due to uncertainty in both the observation and the numerical model.

HEC↗