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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Method and System for Physiologically Modulating Videogames and Simulations which Use Gesture and Body Image Sensing Control Input Devices

Method for physiologically modulating videogames and simulations includes utilizing input from a motion-sensing video game system and input from a physiological signal acquisition device. The inputs from the physiological signal sensors are utilized to change the response of a user's avatar to inputs from the motion-sensing sensors. The motion-sensing system comprises a 3D sensor system having full-body 3D motion capture of a user's body. This arrangement encourages health-enhancing physiological self-regulation skills or therapeutic amplification of healthful physiological characteristics. The system provides increased motivation for users to utilize biofeedback as may be desired for treatment of various conditions.

Pope, Alan T.↗
DOE OSTI2023

HOLISMOKES IX. Neural network inference of strong-lens parameters and uncertainties from ground-based images

Modeling of strong gravitational lenses is a necessity for further applications in astrophysics and cosmology. With the large number of detections in current and upcoming surveys, such as the Rubin Legacy Survey of Space and Time (LSST), it is pertinent to investigate automated and fast analysis techniques beyond the traditional and time-consuming Markov chain Monte Carlo sampling methods. Building upon our (simple) convolutional neural network (CNN), we present here another CNN, specifically a residual neural network (ResNet), that predicts the five mass parameters of a singular isothermal ellipsoid (SIE) profile (lens center x and y, ellipticity e x and e y , Einstein radius θ E ) and the external shear (γ ext, 1 , γ ext, 2 ) from ground-based imaging data. In contrast to our previous CNN, this ResNet further predicts the 1σ uncertainty for each parameter. To train our network, we use our improved pipeline to simulate lens images using real images of galaxies from the Hyper Suprime-Cam Survey (HSC) and from the Hubble Ultra Deep Field as lens galaxies and background sources, respectively. We find very good recoveries overall for the SIE parameters, especially for the lens center in comparison to our previous CNN, while significant differences remain in predicting the external shear. From our multiple tests, it appears that most likely the low ground-based image resolution is the limiting factor in predicting the external shear. Given the run time of milli-seconds per system, our network is perfectly suited to quickly predict the next appearing image and time delays of lensed transients. Therefore, we use the network-predicted mass model to estimate these quantities and compare to those values obtained from our simulations. Unfortunately, the achieved precision allows only a first-order estimate of time delays on real lens systems and requires further refinement through follow-up modeling. Nonetheless, our ResNet is able to predict the SIE and shear parameter values in fractions of a second on a single CPU, meaning that we are able to efficiently process the huge amount of galaxy-scale lenses expected in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

EUV Imaging of SWCX-Produced He(+) 30.4-nm Emission/Scattering at the Magnetosheath

Theoretically, charge exchange between solar wind alpha-particles and geocoronal hydrogen at the magnetosheath results in the production of helium ions in an excited state, i.e, He(2+) + H (right arrow) He(+*) + H(+) resulting in the emission of 30.4-nm radiation upon relaxation of the helium ions. It has been estimated that the magnetosphere was compressed to inside the orbit of IMAGE during the Halloween storm of 2003. This configuration should have placed the subsolar point of the magnetosheath well beyond the limb of the solar disk and allow EUV the potential of imaging this solar wind charge exchange interaction Analysis of EUV full-frame data acquired during 31 October 2003 (Day 304) indicates the detection of 30.4-nm photons in the likely vicinity of the magnetosheath either as a direct consequence of the emission proposed above or, provided the magnetosheath He(+) density was sufficient to exceed the EUV sensitivity threshold, via resonant scattering of solar UV. We present initial analysis of EUV imaging during the Halloween 2003 storm from the context of solar wind parameters, including composition, and from the perspective of the generation of simulated EUV imaging of the event both as an emitting and as a scattering process.

Adrian, M. L.↗
DOE OSTI2016

TH-EF-207A-05: Feasibility of Applying SMEIR Method On Small Animal 4D Cone Beam CT Imaging

Purpose: Small animal cone beam CT imaging has been widely used in preclinical research. Due to the higher respiratory rate and heat beats of small animals, motion blurring is inevitable and needs to be corrected in the reconstruction. Simultaneous motion estimation and image reconstruction (SMEIR) method, which uses projection images of all phases, proved to be effective in motion model estimation and able to reconstruct motion-compensated images. We demonstrate the application of SMEIR for small animal 4D cone beam CT imaging by computer simulations on a digital rat model. Methods: The small animal CBCT imaging system was simulated with the source-to-detector distance of 300 mm and the source-to-object distance of 200 mm. A sequence of rat phantom were generated with 0.4 mm{sup 3} voxel size. The respiratory cycle was taken as 1.0 second and the motions were simulated with a diaphragm motion of 2.4mm and an anterior-posterior expansion of 1.6 mm. The projection images were calculated using a ray-tracing method, and 4D-CBCT were reconstructed using SMEIR and FDK methods. The SMEIR method iterates over two alternating steps: 1) motion-compensated iterative image reconstruction by using projections from all respiration phases and 2) motion model estimation from projections directly through a 2D-3D deformable registration of the image obtained in the first step to projection images of other phases. Results: The images reconstructed using SMEIR method reproduced the features in the original phantom. Projections from the same phase were also reconstructed using FDK method. Compared with the FDK results, the images from SMEIR method substantially improve the image quality with minimum artifacts. Conclusion: We demonstrate that it is viable to apply SMEIR method to reconstruct small animal 4D-CBCT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Cosmic Ray Muon Tomography

This presentation discusses muons and their application in detectors, imaging and simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Investigation of Stress Field and Fracture Development During Shale Maturation Using Analog Rock Systems

The emergence of hydrocarbons within shale as a major recoverable resource has sparked interest in fluid transport through these tight mudstones. Recent studies suggest the importance to recovery of microfracture networks that connect localized zones with large organic content to the inorganic matrix. This paper presents a joint modeling and experimental study to examine the onset, formation, and evolution of microfracture networks as shale matures. Both the stress field and fractures are simulated and imaged. A novel laboratory-scale, phase-field fracture propagation model was developed to characterize the material failure mechanisms that play a significant role during the shale maturation process. The numerical model developed consists of coupled solid deformation, pore pressure, and fracture propagation mechanisms. Benchmark tests were conducted to validate model accuracy. Laboratory-grade gelatins with varying Young’s modulus were used as scaled-rock analogs in two dimensional Hele-Shaw cell apparatus. Yeast within the gelatin generates gas in a fashion analogous to hydrocarbon formation as shale matures. These setups allow study and visualization of host rock elastic-brittle fracture and fracture network propagation mechanisms. The experimental setup was fitted to utilize photoelasticity principles coupled with birefringence properties of gelatin to explore visually the stress field of the gelatin as the fracture network developed. Stress optics image analysis and Linear Elastic Fracture Mechanics (LEFM) principles for crack propagation were used to monitor fracture growth for each gelatin type. Observed and simulated responses suggest gas diffusion within and deformation of the gelatin matrix as predominant mechanisms for energy dissipation depending on gelatin strength. LEFM, an experimental estimation of principal stress development with fracture growth, at different stages was determined for each gelatin rheology. Here, the interplay of gas diffusion and material deformation determines the resulting frequency and pattern of fractures. Results correlate with Young’s modulus. Experimental and computed stress fields reveal that fractures resulting from internal gas generation are similar to, but not identical to, type 1 opening mode.

58 GEOSCIENCES↗
DOE OSTI2024

Structural Complexities in Sodium Ion Conductive Antiperovskite Revealed by Cryogenic Transmission Electron Microscopy

Here we use low-dose cryogenic transmission electron microscopy (cryo-TEM) to investigate the atomic-scale structure of antiperovskite Na 2 NH 2 BH 4 crystals by preserving the room-temperature cubic phase and carefully monitoring the electron dose. Via quantitative analysis of electron beam damage using selected area electron diffraction, we find cryogenic imaging provides 6-fold improvement in beam stability for this solid electrolyte. Cryo-TEM images obtained from flat crystals revealed the presence of a new, long-range-ordered supercell with a cubic phase. The supercell exhibits doubled unit cell dimensions of 9.4 Å × 9.4 Å as compared to the cubic lattice structure revealed by X-ray crystallography of 4.7 Å × 4.7 Å. The comparison between the experimental image and simulated potential map indicates the origin of the supercell is a vacancy ordering of sodium atoms. This work demonstrates the potential of using cryo-TEM imaging to study the atomic-scale structure of air- and electron-beam-sensitive antiperovskite-type solid electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TH-CD-202-07: A Methodology for Generating Numerical Phantoms for Radiation Therapy Using Geometric Attribute Distribution Models

Purpose: A persistent challenge for the quality assessment of radiation therapy treatments (e.g. contouring accuracy) is the absence of the known, ground truth for patient data. Moreover, assessment results are often patient-dependent. Computer simulation studies utilizing numerical phantoms can be performed for quality assessment with a known ground truth. However, previously reported numerical phantoms do not include the statistical properties of inter-patient variations, as their models are based on only one patient. In addition, these models do not incorporate tumor data. In this study, a methodology was developed for generating numerical phantoms which encapsulate the statistical variations of patients within radiation therapy, including tumors. Methods: Based on previous work in contouring assessment, geometric attribute distribution (GAD) models were employed to model both the deterministic and stochastic properties of individual organs via principle component analysis. Using pre-existing radiation therapy contour data, the GAD models are trained to model the shape and centroid distributions of each organ. Then, organs with different shapes and positions can be generated by assigning statistically sound weights to the GAD model parameters. Organ contour data from 20 retrospective prostate patient cases were manually extracted and utilized to train the GAD models. As a demonstration, computer-simulated CT images of generated numerical phantoms were calculated and assessed subjectively and objectively for realism. Results: A cohort of numerical phantoms of the male human pelvis was generated. CT images were deemed realistic both subjectively and objectively in terms of image noise power spectrum. Conclusion: A methodology has been developed to generate realistic numerical anthropomorphic phantoms using pre-existing radiation therapy data. The GAD models guarantee that generated organs span the statistical distribution of observed radiation therapy patients, according to the training dataset. The methodology enables radiation therapy treatment assessment with multi-modality imaging and a known ground truth, and without patient-dependent bias.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Enhancing Nanoparticle Detection in Interferometric Scattering (iSCAT) Microscopy Using a Mask R-CNN

Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, in this paper, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Concept of an upright wearable positron emission tomography imager in humans

Abstract Background Positron Emission Tomography ( PET ) is traditionally used to image patients in restrictive positions, with few devices allowing for upright, brain‐dedicated imaging. Our team has explored the concept of wearable PET imagers which could provide functional brain imaging of freely moving subjects. To test feasibility and determine future considerations for development, we built a rudimentary proof‐of‐concept prototype (Helmet_ PET ) and conducted tests in phantoms and four human volunteers. Methods Twelve Silicon Photomultiplier‐based detectors were assembled in a ring with exterior weight support and an interior mechanism that could be adjustably fitted to the head. We conducted brain phantom tests as well as scanned four patients scheduled for diagnostic F 18‐ FDG PET / CT imaging. For human subjects the imager was angled such that field of view included basal ganglia and visual cortex to test for typical resting‐state pattern. Imaging in two subjects was performed ~4 hr after PET / CT imaging to simulate lower injected F 18‐ FDG dose by taking advantage of the natural radioactive decay of the tracer (F 18 half‐life of 110 min), with an estimated imaging dosage of 25% of the standard. Results We found that imaging with a simple lightweight ring of detectors was feasible using a fraction of the standard radioligand dose. Activity levels in the human participants were quantitatively similar to standard PET in a set of anatomical ROI s. Typical resting‐state brain pattern activation was demonstrated even in a 1 min scan of active head rotation. Conclusion To our knowledge, this is the first demonstration of imaging a human subject with a novel wearable PET imager that moves with robust head movements. We discuss potential research and clinical applications that will drive the design of a fully functional device. Designs will need to consider trade‐offs between a low weight device with high mobility and a heavier device with greater sensitivity and larger field of view.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multi-frame, ultrafast, x-ray microscope for imaging shockwave dynamics

Inertial confinement fusion (ICF) holds increasing promise as a potential source of abundant, clean energy, but has been impeded by defects such as micro-voids in the ablator layer of the fuel capsules. It is critical to understand how these micro-voids interact with the laser-driven shock waves that compress the fuel pellet. At the Matter in Extreme Conditions (MEC) instrument at the Linac Coherent Light Source (LCLS), we utilized an x-ray pulse train with ns separation, an x-ray microscope, and an ultrafast x-ray imaging (UXI) detector to image shock wave interactions with micro-voids. To minimize the high- and low-frequency variations of the captured images, we incorporated principal component analysis (PCA) and image alignment for flat-field correction. After applying these techniques we generated phase and attenuation maps from a 2D hydrodynamic radiation code (xRAGE), which were used to simulate XPCI images that we qualitatively compare with experimental images, providing a one-to-one comparison for benchmarking material performance. Moreover, we implement a transport-of-intensity (TIE) based method to obtain the average projected mass density (areal density) of our experimental images, yielding insight into how defect-bearing ablator materials alter microstructural feature evolution, material compression, and shock wave propagation on ICF-relevant time scales.

47 OTHER INSTRUMENTATION↗
NASA NTRS2014

Infrared Contrast Analysis Technique for Flash Thermography Nondestructive Evaluation

The paper deals with the infrared flash thermography inspection to detect and analyze delamination-like anomalies in nonmetallic materials. It provides information on an IR Contrast technique that involves extracting normalized contrast verses time evolutions from the flash thermography infrared video data. The paper provides the analytical model used in the simulation of infrared image contrast. The contrast evolution simulation is achieved through calibration on measured contrast evolutions from many flat bottom holes in the subject material. The paper also provides formulas to calculate values of the thermal measurement features from the measured contrast evolution curve. Many thermal measurement features of the contrast evolution that relate to the anomaly characteristics are calculated. The measurement features and the contrast simulation are used to evaluate flash thermography inspection data in order to characterize the delamination-like anomalies. In addition, the contrast evolution prediction is matched to the measured anomaly contrast evolution to provide an assessment of the anomaly depth and width in terms of depth and diameter of the corresponding equivalent flat-bottom hole (EFBH) or equivalent uniform gap (EUG). The paper provides anomaly edge detection technique called the half-max technique which is also used to estimate width of an indication. The EFBH/EUG and half-max width estimations are used to assess anomaly size. The paper also provides some information on the "IR Contrast" software application, half-max technique and IR Contrast feature imaging application, which are based on models provided in this paper.

Koshti, Ajay↗
NASA NTRS1995

Flame-vortex interactions imaged in microgravity

The scientific objective is to obtain high quality color-enhanced digital images of a vortex exerting aerodynamic strain on premixed and nonpremixed flames with the complicating effects of buoyancy removed. The images will provide universal (buoyancy free) scaling relations that are required to improve several types of models of turbulent combustion, including KIVA-3, discrete vortex, and large-eddy simulations. The images will be used to help quantify several source terms in the models, including those due to flame stretch, flame-generated vorticity, flame curvature, and preferential diffusion, for a range of vortex sizes and flame conditions. The experiment is an ideal way to study turbulence-chemistry interactions and isolate the effect of vortices of different sizes and strengths in a repeatable manner. A parallel computational effort is being conducted which considers full chemistry and preferential diffusion.

Driscoll, James F.↗
NASA NTRS2000

BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MODIS Airborne Simulator (MAS) images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.

Hall, Forrest G.↗
DOE OSTI2025

Intrinsic Defect-Induced Local Semiconducting-to-Metallic Regions Within Monolayer 1T-TiS2 Displayed by First-Principles Calculations and Scanning Tunneling Microscopy

Using density functional theory (DFT) and scanning tunneling microscopy (STM), the intrinsic point defects, formation energy, and electronic structure of 1T-TiS2 were investigated. Defect systems include single-atom vacancies, interstitial and adatom additions, and direct atomic substitution. Using a collective approach for analyzing realistic systems for point defect investigation, we provide a more straightforward comparison to the experimental measurements, reproducing more realistic environmental conditions related to thin film growth. STM images are compared to computationally simulated electron density images to identify specific geometries that result from favorable point defects. DFT suggests that titanium interstitials are the most energetically favorable intrinsic defect, and sulfur vacancies are more likely to form than titanium vacancies within this realistic analysis, which is in agreement with STM data. A pristine, stoichiometric monolayer system is calculated to have a direct band gap of 0.422 eV, which varies based on local point defects. Local semiconducting-to-metallic electronic transitions are predicted to occur based on the presence of Ti interstitials.

Keeney, P. J.↗
DOE OSTI2018

Analysis of contour images using optics of spiral beams

An approach is outlined to the recognition of contour images using computer technology based on coherent optics principles. A mathematical description of the recognition process algorithm and the results of numerical modelling are presented. The developed approach to the recognition of contour images using optics of spiral beams is described and justified. (image recognition)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Reconstructing the exit wave of 2D materials in high-resolution transmission electron microscopy using machine learning

Reconstruction of the exit wave function is an important route to interpreting high-resolution transmission electron microscopy (HRTEM) images. Here we demonstrate that convolutional neural networks can be used to reconstruct the exit wave from a short focal series of HRTEM images, with a fidelity comparable to conventional exit wave reconstruction. We use a fully convolutional neural network based on the U-Net architecture, and demonstrate that we can train it on simulated exit waves and simulated HRTEM images of graphene-supported molybdenum disulphide (an industrial desulfurization catalyst). We then apply the trained network to analyse experimentally obtained images from similar samples, and obtain exit waves that clearly show the atomically resolved structure of both the MoS 2 nanoparticles and the graphene support. We also show that it is possible to successfully train the neural networks to reconstruct exit waves for 3400 different two-dimensional materials taken from the Computational 2D Materials Database of known and proposed two-dimensional materials.

2D materials↗