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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Visualization and Tracking of Parallel CFD Simulations

We describe a system for interactive visualization and tracking of a 3-D unsteady computational fluid dynamics (CFD) simulation on a parallel computer. CM/AVS, a distributed, parallel implementation of a visualization environment (AVS) runs on the CM-5 parallel supercomputer. A CFD solver is run as a CM/AVS module on the CM-5. Data communication between the solver, other parallel visualization modules, and a graphics workstation, which is running AVS, are handled by CM/AVS. Partitioning of the visualization task, between CM-5 and the workstation, can be done interactively in the visual programming environment provided by AVS. Flow solver parameters can also be altered by programmable interactive widgets. This system partially removes the requirement of storing large solution files at frequent time steps, a characteristic of the traditional 'simulate (yields) store (yields) visualize' post-processing approach.

Vaziri, Arsi↗
DOE OSTI2022

Voronoi Meshing to Accurately Capture Geological Structure in Subsurface Simulations

Mesh generation lies at the interface of geological modeling and reservoir simulation. Highly skewed or very small grid cells may be necessary to accurately capture the geometry of geological features, but the resulting poorly scaled or small grid cells can have a substantial negative impact on simulator accuracy and speed. One way to minimize numerical errors caused by gridding complex structures is to simulate on high-quality Voronoi meshes, which reduce grid orientation effects in fluid flow. This work presents a complete methodology to create Voronoi simulation grids, model fluid flow in complex geological systems, and visualize the results. A recently developed Voronoi meshing method that can automatically generate provably good unstructured meshes that conform to input surfaces creating closed volumes is used. Initially an analytical benchmark simulation is presented to validate the quality of the meshes and simulation results and demonstrate the superiority of simulation results using Voronoi meshes over flexed-hexahedral meshes on a domain with internal features. Next, meshes are created for test structures representing four of the most common geological features in the subsurface: layering, pinch-out, an interior lens that tapers to zero thickness on all sides and a fault with offset. Two benchmark flow simulations are run for each test structure. Finally, a realistic geological example for CO 2 injection into an anticline is simulated. Three realizations of the Voronoi mesh at the same resolution are generated for the simulations. Each mesh is highly refined near the injection wells and coarse in areas of less interest. These three meshes are used to model the CO 2 plume in the subsurface as it migrates to the top of the structure and then fills downward. Simulations on the meshes with randomly generated elements inside the input volumes each give slightly different fingering patterns for the viscous-unstable buoyant gas flow. The results presented in this work show a promising step towards utilizing fully automated Voronoi meshing for subsurface flow simulations in complex geology.

58 GEOSCIENCES↗
DOE OSTI2014

Monte Carlo capabilities of the SCALE code system

SCALE is a broadly used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. Finally, an overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Association Between Pulmonary Uptake of Fluorodeoxyglucose Detected by Positron Emission Tomography Scanning After Radiation Therapy for Non-Small-Cell Lung Cancer and Radiation Pneumonitis

Purpose: To study the relationship between fluorodeoxyglucose (FDG) uptake in pulmonary tissue after radical radiation therapy (RT) and the presence and severity of radiation pneumonitis. Methods and Materials: In 88 consecutive patients, {sup 18}F-FDG-positron emission tomography was performed at a median of 70 days after completion of RT. Patients received 60 Gy in 30 fractions, and all but 15 had concurrent platinum-based chemotherapy. RT-induced pulmonary inflammatory changes occurring within the radiation treatment volume were scored, using a visual (0 to 3) radiotoxicity grading scale, by an observer blinded to the presence or absence of clinical radiation pneumonitis. Radiation pneumonitis was retrospectively graded using the Radiation Therapy Oncology Group (RTOG) scale by an observer blinded to the PET radiotoxicity score. Results: There was a significant association between the worst RTOG pneumonitis grade occurring at any time after RT and the positron emission tomograph (PET) radiotoxicity grade (one-sided p = 0.033). The worst RTOG pneumonitis grade occurring after the PET scan was also associated with the PET radiotoxicity grade (one-sided p = 0.035). For every one-level increase in the PET toxicity scale, the risk of a higher RTOG radiation pneumonitis score increased by approximately 40%. The PET radiotoxicity score showed no significant correlation with the duration of radiation pneumonitis. Conclusions: The intensity of FDG uptake in pulmonary tissue after RT determined using a simple visual scoring system showed significant correlation with the presence and severity of radiation pneumonitis. {sup 18}F-FDG-PET may be useful in the prediction, diagnosis and therapeutic monitoring of radiation pneumonitis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

In vivo volumetric imaging of calcium and glutamate activity at synapses with high spatiotemporal resolution

Studying neuronal activity at synapses requires high spatiotemporal resolution. For high spatial resolution in vivo imaging at depth, adaptive optics (AO) is required to correct sample-induced aberrations. To improve temporal resolution, Bessel focus has been combined with two-photon fluorescence microscopy (2PFM) for fast volumetric imaging at subcellular lateral resolution. To achieve both high-spatial and high-temporal resolution at depth, we develop an efficient AO method that corrects the distorted wavefront of Bessel focus at the objective focal plane and recovers diffraction-limited imaging performance. Applying AO Bessel focus scanning 2PFM to volumetric imaging of zebrafish larval and mouse brains down to 500 µm depth, we demonstrate substantial improvements in the sensitivity and resolution of structural and functional measurements of synapses in vivo. This enables volumetric measurements of synaptic calcium and glutamate activity at high accuracy, including the simultaneous recording of glutamate activity of apical and basal dendritic spines in the mouse cortex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Smart soft contact lenses for continuous 24-hour monitoring of intraocular pressure in glaucoma care

Continuous monitoring of intraocular pressure, particularly during sleep, remains a grand challenge in glaucoma care. Here we introduce a class of smart soft contact lenses, enabling the continuous 24-hour monitoring of intraocular pressure, even during sleep. Uniquely, the smart soft contact lenses are built upon various commercial brands of soft contact lenses without altering their intrinsic properties such as lens power, biocompatibility, softness, transparency, wettability, oxygen transmissibility, and overnight wearability. We show that the smart soft contact lenses can seamlessly fit across different corneal curvatures and thicknesses in human eyes and therefore accurately measure absolute intraocular pressure under ambulatory conditions. We perform a comprehensive set of in vivo evaluations in rabbit, dog, and human eyes from normal to hypertension to confirm the superior measurement accuracy, within-subject repeatability, and user comfort of the smart soft contact lenses beyond current wearable ocular tonometers. We envision that the smart soft contact lenses will be effective in glaucoma care.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Stimulus edges induce orientation tuning in superior colliculus

Orientation columns exist in the primary visual cortex (V1) of cat and primates but not mouse. Intriguingly, some recent studies reported the presence of orientation and direction columns in the mouse superficial superior colliculus (sSC), while others reported a lack of columnar organization therein. Using in vivo calcium imaging of sSC in the awake mouse brain, we found that the presence of columns is highly stimulus dependent. Specifically, we observed orientation and direction columns formed by sSC neurons retinotopically mapped to the edge of grating stimuli. For both excitatory and inhibitory neurons in sSC, orientation selectivity can be induced by the edge with their preferred orientation perpendicular to the edge orientation. Furthermore, we found that this edge-induced orientation selectivity is associated with saliency encoding. These findings indicate that the tuning properties of sSC neurons are not fixed by circuit architecture but rather dependent on the spatiotemporal properties of the stimulus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Imaging of a van der Waals spin-orbit torque system using spin ensembles in hBN

Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.

Imaging techniques↗
DOE OSTI2023

Ultrafast structural changes direct the first molecular events of vision

Vision is initiated by the rhodopsin family of light-sensitive G protein-coupled receptors (GPCRs). A photon is absorbed by the 11-cis retinal chromophore of rhodopsin, which isomerizes within 200 femtoseconds to the all-transconformation, thereby initiating the cellular signal transduction processes that ultimately lead to vision. However, the intramolecular mechanism by which the photoactivated retinal induces the activation events inside rhodopsin remains experimentally unclear. Here we use ultrafast time-resolved crystallography at room temperature to determine how an isomerized twisted all-trans retinal stores the photon energy that is required to initiate the protein conformational changes associated with the formation of the G protein-binding signalling state. The distorted retinal at a 1-ps time delay after photoactivation has pulled away from half of its numerous interactions with its binding pocket, and the excess of the photon energy is released through an anisotropic protein breathing motion in the direction of the extracellular space. Notably, the very early structural motions in the protein side chains of rhodopsin appear in regions that are involved in later stages of the conserved class A GPCR activation mechanism. Our study sheds light on the earliest stages of vision in vertebrates and points to fundamental aspects of the molecular mechanisms of agonist-mediated GPCR activation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Onset of normal and inverse homoclinic bifurcation in a double plasma system near a plasma fireball

Plasma fireballs are generated due to a localized discharge and appear as a luminous glow with a sharp boundary, which suggests the presence of a localized electric field such as electrical sheath or double layer structure. The present work reports the observation of normal and inverse homoclinic bifurcation phenomena in plasma oscillations that are excited in the presence of fireball in a double plasma device. The controlling parameters for these observations are the ratio of target to source chamber (n{sub T}/n{sub S}) densities and applied electrode voltage. Homoclinic bifurcation is noticed in the plasma potential fluctuations as the system evolves from narrow to long time period oscillations and vice versa with the change of control parameter. The dynamical transition in plasma fireball is demonstrated by spectral analysis, recurrence quantification analysis (RQA), and statistical measures, viz., skewness and kurtosis. The increasing trend of normalized variance reflects that enhancing n{sub T}/n{sub S} induces irregularity in plasma dynamics. The exponential growth of the time period is strongly indicative of homoclinic bifurcation in the system. The gradual decrease of skewness and increase of kurtosis with the increase of n{sub T}/n{sub S} also reflect growing complexity in the system. The visual change of recurrence plot and gradual enhancement of RQA variables DET, L{sub max}, and ENT reflects the bifurcation behavior in the dynamics. The combination of RQA and spectral analysis is a clear evidence that homoclinic bifurcation occurs due to the presence of plasma fireball with different density ratios. However, inverse bifurcation takes place due to the change of fireball voltage. Some of the features observed in the experiment are consistent with a model that describes the dynamics of ionization instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2013

Discovery of a visual T-dwarf triple system and binarity at the L/T transition

We present new high contrast imaging of eight L/T transition brown dwarfs (BDs) using the NIRC2 camera on the Keck II telescope. One of our targets, the T3.5 dwarf 2MASS J08381155+1511155, was resolved into a hierarchal triple with projected separations of 2.5 ± 0.5 AU and 27 ± 5 AU for the BC and A(BC) components, respectively. Resolved OSIRIS spectroscopy of the A(BC) components confirms that all system members are T dwarfs. The system therefore constitutes the first triple T-dwarf system ever reported. Using resolved photometry to model the integrated-light spectrum, we infer spectral types of T3 ± 1, T3 ± 1, and T4.5 ± 1 for the A, B, and C components, respectively. The uniformly brighter primary has a bluer J – K{sub s} color than the next faintest component, which may reflect a sensitive dependence of the L/T transition temperature on gravity, or alternatively divergent cloud properties among components. Relying on empirical trends and evolutionary models we infer a total system mass of 0.034-0.104 M {sub ☉} for the BC components at ages of 0.3-3 Gyr, which would imply a period of 12-21 yr assuming the system semimajor axis to be similar to its projection. We also infer differences in effective temperatures and surface gravities between components of no more than ∼150 K and ∼0.1 dex. Given the similar physical properties of the components, the 2M0838+15 system provides a controlled sample for constraining the relative roles of effective temperature, surface gravity, and dust clouds in the poorly understood L/T transition regime. For an age of 3 Gyr we estimate a binding energy of ∼20 × 10{sup 41} erg for the wide A(BC) pair, which falls above the empirical minimum found for typical BD binaries, and suggests that the system may have been able to survive a dynamical ejection during formation. Combining our imaging survey results with previous work we find an observed binary fraction of 4/18 or 22{sub −8}{sup +10}% for unresolved spectral types of L9-T4 at separations ≳ 0.''1. This translates into a volume-corrected frequency of 13{sub −6}{sup +7}%, which is similar to values of ∼9%-12% reported outside the transition. Our reported L/T transition binary fraction is roughly twice as large as the binary fraction of an equivalent L9-T4 sample selected from primary rather than unresolved spectral types (6{sub −4}{sup +6}%); however, this increase is not yet statistically significant and a larger sample is required to settle the issue.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

No more active galactic nuclei in clumpy disks than in smooth galaxies at z ∼ 2 in CANDELS/3D-HST

We use CANDELS imaging, 3D-HST spectroscopy, and Chandra X-ray data to investigate if active galactic nuclei (AGNs) are preferentially fueled by violent disk instabilities funneling gas into galaxy centers at 1.3 < z < 2.4. We select galaxies undergoing gravitational instabilities using the number of clumps and degree of patchiness as proxies. The CANDELS visual classification system is used to identify 44 clumpy disk galaxies, along with mass-matched comparison samples of smooth and intermediate morphology galaxies. We note that despite being mass-matched and having similar star formation rates, the smoother galaxies tend to be smaller disks with more prominent bulges compared to the clumpy galaxies. The lack of smooth extended disks is probably a general feature of the z ∼ 2 galaxy population, and means we cannot directly compare with the clumpy and smooth extended disks observed at lower redshift. We find that z ∼ 2 clumpy galaxies have slightly enhanced AGN fractions selected by integrated line ratios (in the mass-excitation method), but the spatially resolved line ratios indicate this is likely due to extended phenomena rather than nuclear AGNs. Meanwhile, the X-ray data show that clumpy, smooth, and intermediate galaxies have nearly indistinguishable AGN fractions derived from both individual detections and stacked non-detections. The data demonstrate that AGN fueling modes at z ∼ 1.85—whether violent disk instabilities or secular processes—are as efficient in smooth galaxies as they are in clumpy galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations

Molecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).

Chae, Junghoon↗
DOE OSTI2014

Adaptation of the modified Bouc–Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: Testing using MRI

Purpose: Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc–Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors’ previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart. Methods: In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior–inferior direction during free breathing using MRI navigators. A visual tracking system (VTS) synchronized with MRI acquisition tracked the anterior–posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc–Wen model by inputting the VTS derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson’s linear correlation coefficient between the abdomen, chest, average of chest and abdomen markers, and Bouc–Wen derived signals versus the true internal motion of the heart from MRI was used to judge the signals match to the heart motion. Results: The results show that the Bouc–Wen model generated signals demonstrated strong correlation with the heart motion. This correlation was slightly larger on average than that of the external surrogate signals derived from the abdomen marker, and average of the abdomen and chest markers, but was not statistically significantly different from them. Conclusions: The results suggest that the proposed model has the potential to be a unified framework for modeling hysteresis in respiratory motion in cardiac perfusion studies and beyond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-J-42: Evaluation of Fiducial Markers for Ultrasound and X-Ray Images Used for Motion Tracking in Pancreas SBRT

Purpose Ultrasound tracking of target motion relies on visibility of vascular and/or anatomical landmark. However this is challenging when the target is located far from vascular structures or in organs that lack ultrasound landmark structure, such as in the case of pancreas cancer. The purpose of this study is to evaluate visibility, artifacts and distortions of fusion coils and solid gold markers in ultrasound, CT, CBCT and kV images to identify markers suitable for real-time ultrasound tracking of tumor motion in SBRT pancreas treatment. Methods Two fusion coils (1mm × 5mm and 1mm × 10 mm) and a solid gold marker (0.8mm × 10mm) were embedded in a tissue–like ultrasound phantom. The phantom (5cm × 12cm × 20cm) was prepared using water, gelatin and psyllium-hydrophilic-mucilloid fiber. Psylliumhydrophilic mucilloid acts as scattering medium to produce echo texture that simulates sonographic appearance of human tissue in ultrasound images while maintaining electron density close to that of water in CT images. Ultrasound images were acquired using 3D-ultrasound system with markers embedded at 5, 10 and 15mm depth from phantom surface. CT images were acquired using Philips Big Bore CT while CBCT and kV images were acquired with XVI-system (Elexta). Visual analysis was performed to compare visibility of the markers and visibility score (1 to 3) were assigned. Results All markers embedded at various depths are clearly visible (score of 3) in ultrasound images. Good visibility of all markers is observed in CT, CBCT and kV images. The degree of artifact produced by the markers in CT and CBCT images are indistinguishable. No distortion is observed in images from any modalities. Conclusion All markers are visible in images across all modalities in this homogenous tissue-like phantom. Human subject data is necessary to confirm the marker type suitable for real-time ultrasound tracking of tumor motion in SBRT pancreas treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

Hohman, Frederick M.↗