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Results for “3D image processing”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Super-resolution image display using diffractive decoders

High-resolution image projection over a large field of view (FOV) is hindered by the restricted space-bandwidth product (SBP) of wavefront modulators. We report a deep learning–enabled diffractive display based on a jointly trained pair of an electronic encoder and a diffractive decoder to synthesize/project super-resolved images using low-resolution wavefront modulators. The digital encoder rapidly preprocesses the high-resolution images so that their spatial information is encoded into low-resolution patterns, projected via a low SBP wavefront modulator. The diffractive decoder processes these low-resolution patterns using transmissive layers structured using deep learning to all-optically synthesize/project super-resolved images at its output FOV. This diffractive image display can achieve a super-resolution factor of ~4, increasing the SBP by ~16-fold. We experimentally validate its success using 3D-printed diffractive decoders that operate at the terahertz spectrum. This diffractive image decoder can be scaled to operate at visible wavelengths and used to design large SBP displays that are compact, low power, and computationally efficient.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Spatially Tracked Hand-held Gamma Camera for Surgery

The goal of the project was to develop and test a 3-dimensional (3D) imaging technology designed to overcome limitations of current non-imaging lymph node mapping methods by integrating a newly developed, unique hand-held gamma camera (HGC) into a platform for freehand SPECT (single photon emission computed tomography). Sentinel lymph node biopsy is a vital component of surgical oncology in the process of establishing the extent of disease and likelihood of metastasis. The team was successful in the development and testing of the device.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2009

Three-Dimensional Optical Coherence Tomography

Three-dimensional (3D) optical coherence tomography (OCT) is an advanced method of noninvasive infrared imaging of tissues in depth. Heretofore, commercial OCT systems for 3D imaging have been designed principally for external ophthalmological examination. As explained below, such systems have been based on a one-dimensional OCT principle, and in the operation of such a system, 3D imaging is accomplished partly by means of a combination of electronic scanning along the optical (Z) axis and mechanical scanning along the two axes (X and Y) orthogonal to the optical axis. In 3D OCT, 3D imaging involves a form of electronic scanning (without mechanical scanning) along all three axes. Consequently, the need for mechanical adjustment is minimal and the mechanism used to position the OCT probe can be correspondingly more compact. A 3D OCT system also includes a probe of improved design and utilizes advanced signal- processing techniques. Improvements in performance over prior OCT systems include finer resolution, greater speed, and greater depth of field.

Gutin, Mikhail↗
DOE OSTI2020

Critical instability at moving keyhole tip generates porosity in laser melting

Laser powder bed fusion is a dominant metal 3D printing technology. However, porosity defects remain a challenge for fatigue-sensitive applications. Some porosity is associated with deep and narrow vapor depressions called keyholes, which occur under high-power, low–scan speed laser melting conditions. High-speed x-ray imaging enables operando observation of the detailed formation process of pores in Ti-6Al-4V caused by a critical instability at the keyhole tip. We found that the boundary of the keyhole porosity regime in power-velocity space is sharp and smooth, varying only slightly between the bare plate and powder bed. The critical keyhole instability generates acoustic waves in the melt pool that provide additional yet vital driving force for the pores near the keyhole tip to move away from the keyhole and become trapped as defects.

47 OTHER INSTRUMENTATION↗
NASA NTRS2011

NASA Tech Briefs, March 2011

Topics covered include: Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation; Airborne Radar Interferometric Repeat-Pass Processing; Plug-and-Play Environmental Monitoring Spacecraft Subsystem; Power-Combined GaN Amplifier with 2.28-W Output Power at 87 GHz; Wallops Ship Surveillance System; Source Lines Counter (SLiC) Version 4.0; Guidance, Navigation, and Control Program; Single-Frame Terrain Mapping Software for Robotic Vehicles; Auto Draw from Excel Input Files; Observation Scheduling System; CFDP for Interplanetary Overlay Network; X-Windows Widget for Image Display; Binary-Signal Recovery; Volumetric 3D Display System with Static Screen; MMIC Replacement for Gunn Diode Oscillators; Feature Acquisition with Imbalanced Training Data; Mount Protects Thin-Walled Glass or Ceramic Tubes from Large Thermal and Vibration Loads; Carbon Nanotube-Based Structural Health Monitoring Sensors; Wireless Inductive Power Device Suppresses Blade Vibrations; Safe, Advanced, Adaptable Isolation System Eliminates the Need for Critical Lifts; Anti-Rotation Device Releasable by Insertion of a Tool; A Magnetically Coupled Cryogenic Pump; Single Piezo-Actuator Rotary-Hammering Drill; Fire-Retardant Polymeric Additives; Catalytic Generation of Lift Gases for Balloons; Ionic Liquids to Replace Hydrazine; Variable Emittance Electrochromics Using Ionic Electrolytes and Low Solar Absorptance Coatings; Spacecraft Radiator Freeze Protection Using a Regenerative Heat Exchanger; Multi-Mission Power Analysis Tool; Correction for Self-Heating When Using Thermometers as Heaters in Precision Control Applications; Gravitational Wave Detection with Single-Laser Atom Interferometers; Titanium Alloy Strong Back for IXO Mirror Segments; Improved Ambient Pressure Pyroelectric Ion Source; Multi-Modal Image Registration and Matching for Localization of a Balloon on Titan; Entanglement in Quantum-Classical Hybrid; Algorithm for Autonomous Landing; Quantum-Classical Hybrid for Information Processing; Small-Scale Dissipation in Binary-Species Transitional Mixing Layers; Superpixel-Augmented Endmember Detection for Hyperspectral Images; Coding for Parallel Links to Maximize the Expected Value of Decodable Messages; and Microwave Tissue Soldering for Immediate Wound Closure.

Source record↗
DOE OSTI2019

In Situ Time-Resolved X-ray Scattering Study of Isotactic Polypropylene in Additive Manufacturing

In this study, we used a specially designed apparatus, which collects simultaneous temperature and X-ray scattering data, to perform in situ measurements of the filament during MatEx 3D printing. The data show that the MatEx 3D printing extrusion process provides sufficient shear to form shish-kebab structures, which initially nucleate at the filament surface and spread into the filament core. Time-resolved measurements show that the kebab component near the surface relaxes after deposition of the second filament and enhances chain diffusion across the interface. SEM images indicate near complete interfacial merging of the filaments, which results in excellent mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In situ Bragg coherent X-ray diffraction imaging of corrosion in a Co–Fe alloy microcrystal

Corrosion is a major concern for many industries, as corrosive environments can induce structural and morphological changes that lead to material dissolution and accelerate material failure. The progression of corrosion depends on nanoscale morphology, stress, and defects present. Experimentally monitoring this complex interplay is challenging. Here we implement in situ Bragg coherent X-ray diffraction imaging (BCDI) to probe the dissolution of a Co-Fe alloy microcrystal exposed to hydrochloric acid (HCl). By measuring five Bragg reflections from a single isolated microcrystal at ambient conditions, we compare the full three-dimensional (3D) strain state before corrosion and the strain along the [111] direction throughout the corrosion process. We find that the strained surface layer of the crystal dissolves to leave a progressively less strained surface. Interestingly, the average strain closer to the centre of the crystal increases during the corrosion process. We determine the localised corrosion rate from BCDI data, revealing the preferential dissolution of facets more exposed to the acid stream, highlighting an experimental geometry effect. These results bring new perspectives to understanding the interplay between crystal strain, morphology, and corrosion; a prerequisite for the design of more corrosion-resistant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles

Tri-structural isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging because of the strong attenuation of the x-ray beam by the uranium core, leading to severe photon starvation in a substantial fraction of the measurements. Furthermore, the overall acquisition time for a high-resolution CT scan can be very long when using conventional laboratory-based x-ray systems and reconstruction algorithms. Specifically, when analytic methods such as the Feldkamp–Davis–Kress (FDK) algorithm are used for reconstruction, it results in severe streak artifacts and noise in the corresponding 3D volume, which makes subsequent analysis of the particles challenging. In this paper, we develop and apply model-based image reconstruction (MBIR) algorithms to improve the quality of CT reconstructions for TRISO particles to facilitate better characterization. We demonstrate that the proposed MBIR algorithms can significantly suppress artifacts with minimal pre-processing compared to conventional approaches. We also demonstrate that the proposed MBIR approach can obtain high-quality reconstruction compared to the FDK approach even when using a fraction of the typically acquired measurements, thereby enabling dramatically faster measurement times for TRISO particles.

Venkatakrishnan, Singanallur↗
NASA NTRS2010

NASA Tech Briefs, September 2010

Topics covered include: Instrument for Measuring Thermal Conductivity of Materials at Low Temperatures; Multi-Axis Accelerometer Calibration System; Pupil Alignment Measuring Technique and Alignment Reference for Instruments or Optical Systems; Autonomous System for Monitoring the Integrity of Composite Fan Housings; A Safe, Self-Calibrating, Wireless System for Measuring Volume of Any Fuel at Non-Horizontal Orientation; Adaptation of the Camera Link Interface for Flight-Instrument Applications; High-Performance CCSDS Encapsulation Service Implementation in FPGA; High-Performance CCSDS AOS Protocol Implementation in FPGA; Advanced Flip Chips in Extreme Temperature Environments; Diffuse-Illumination Systems for Growing Plants; Microwave Plasma Hydrogen Recovery System; Producing Hydrogen by Plasma Pyrolysis of Methane; Self-Deployable Membrane Structures; Reactivation of a Tin-Oxide-Containing Catalys; Functionalization of Single-Wall Carbon Nanotubes by Photo-Oxidation; Miniature Piezoelectric Macro-Mass Balance; Acoustic Liner for Turbomachinery Applications; Metering Gas Strut for Separating Rocket Stages; Large-Flow-Area Flow-Selective Liquid/Gas Separator; Counterflowing Jet Subsystem Design; Water Tank with Capillary Air/Liquid Separation; True Shear Parallel Plate Viscometer; Focusing Diffraction Grating Element with Aberration Control; Universal Millimeter-Wave Radar Front End; Mode Selection for a Single-Frequency Fiber Laser; Qualification and Selection of Flight Diode Lasers for Space Applications; Plenoptic Imager for Automated Surface Navigation; Maglev Facility for Simulating Variable Gravity; Hybrid AlGaN-SiC Avalanche Photodiode for Deep-UV Photon Detection; High-Speed Operation of Interband Cascade Lasers; 3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events; Charge-Spot Model for Electrostatic Forces in Simulation of Fine Particulates; Hidden Statistics Approach to Quantum Simulations; Reconstituted Three-Dimensional Interactive Imaging; Determining Atmospheric-Density Profile of Titan; Digital Microfluidics Sample Analyzer; Radiation Protection Using Carbon Nanotube Derivatives; Process to Selectively Distinguish Viable from Non-Viable Bacterial Cells; and TEAMS Model Analyzer.

Source record↗
DOE OSTI2024

DLSIA: Deep Learning for Scientific Image Analysis

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing. DLSIA features easy-to-use architectures, such as autoencoders, tunable U-Nets and parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse mixed-scale networks (SMSNets), generated using random graphs, sparse connections and dilated convolutions connecting different length scales. For verification, several DLSIA-instantiated networks and training scripts are employed in multiple applications, including inpainting for X-ray scattering data using U-Nets and MSDNets, segmenting 3D fibers in X-ray tomographic reconstructions of concrete using an ensemble of SMSNets, and leveraging autoencoder latent spaces for data compression and clustering. As experimental data continue to grow in scale and complexity, DLSIA provides accessible CNN construction and abstracts CNN complexities, allowing scientists to tailor their machine learning approaches, accelerate discoveries, foster interdisciplinary collaboration and advance research in scientific image analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Examining phase separation and crystallization in glasses with X-ray nano-computed tomography

X-ray nano-computed tomography (nano-CT) is a powerful technique to characterize and visualize 3 dimensional (3D) phenomena in complex glasses at the nanoscale. This technique can offer a unique opportunity to explore the intricate morphology of multicomponent glass and glass-ceramic samples, due to its low X-ray energy and high spatial resolution (down to 50 nm). In the current demonstration paper, nano-CT provided insight into crystallization and phase separation, as well as a variety of other phenomena, including corrosion, fracture, and porosity. At scales ranging from 100 to 20 μm, the microstructures of phase separation in borosilicate, complex silicate, and chalcogenide glass compositions were examined. In addition, crystallites present in simulant nuclear waste glasses, volcanic glasses, and other related samples were explored. Nano-CT analysis can add to the understanding of (1) the formation processes, (2) distributions, interactions, and compositions of phases, and (3) the mechanisms, structures, and growth of crystallization and phase separation. Nano-CT offers wide potential in the field of glass science, especially when (1) common characterization methods are insufficient, (2) simple sample preparation is required, (3) 3D rendering is needed, or (4) compelling images of small, complex features are desired.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Dynamic super-resolution structured illumination imaging in the living brain

Cells in the brain act as components of extended networks. Therefore, to understand neurobiological processes in a physiological context, it is essential to study them in vivo. Super-resolution microscopy has spatial resolution beyond the diffraction limit, thus promising to provide structural and functional insights that are not accessible with conventional microscopy. However, to apply it to in vivo brain imaging, we must address the challenges of 3D imaging in an optically heterogeneous tissue that is constantly in motion. We optimized image acquisition and reconstruction to combat sample motion and applied adaptive optics to correcting sample-induced optical aberrations in super-resolution structured illumination microscopy (SIM) in vivo. Lastly, we imaged the brains of live zebrafish larvae and mice and observed the dynamics of dendrites and dendritic spines at nanoscale resolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

PIMS: A Lightweight Processing-in-Memory Accelerator for Stencil Computations

Stencil computation is a classic computational kernel present in many high-performance scientific applications, like image process- ing and partial differential equation solvers (PDE). A stencil compu- tation sweeps over a multi-dimensional grid and repeatedly updates values associated with points using the values from neighboring points. Stencil computations often employ large datasets that ex- ceed cache capacity, leading to excessive accesses to the memory subsystem. As such, 3D stencil computations on large grid sizes are memory-bound. In this paper we present PIMS, an in-memory accelerator for stencil computations. PIMS, implemented in the logic layer of a 3D- stacked memory, exploits the high bandwidth provided by through- silicon vias to reduce redundant memory traffic. Our comprehensive evaluation using three different grid sizes with six categories of orders indicate that the proposed architecture reduces 48.25% of data movement on average and obtains up to 65.55% of bank conflict reduction.

Li, Jie↗
NASA NTRS2008

Full-field Strain Methods for Investigating Failure Mechanisms in Triaxial Braided Composites

Composite materials made with triaxial braid architecture and large tow size carbon fibers are beginning to be used in many applications, including composite aircraft and engine structures. Recent advancements in braiding technology have led to commercially viable manufacturing approaches for making large structures with complex shape. Although the large unit cell size of these materials is an advantage for manufacturing efficiency, the fiber architecture presents some challenges for materials characterization, design, and analysis. In some cases, the static load capability of structures made using these materials has been higher than expected based on material strength properties measured using standard coupon tests. A potential problem with using standard tests methods for these materials is that the unit cell size can be an unacceptably large fraction of the specimen dimensions. More detailed investigation of deformation and failure processes in large unit cell size triaxial braid composites is needed to evaluate the applicability of standard test methods for these materials and to develop alternative testing approaches. In recent years, commercial equipment has become available that enables digital image correlation to be used on a more routine basis for investigation of full field 3D deformation in materials and structures. In this paper, some new techniques that have been developed to investigate local deformation and failure using digital image correlation techniques are presented. The methods were used to measure both local and global strains during standard straight-sided coupon tensile tests on composite materials made with 12 and 24 k yarns and a 0/+60/-60 triaxial braid architecture. Local deformation and failure within fiber bundles was observed, and this local failure had a significant effect on global stiffness and strength. The matrix material had a large effect on local damage initiation for the two matrix materials used in this investigation. Premature failure in regions of the unit cell near the edge of the straight-sided specimens was observed for transverse tensile tests in which the braid axial fibers were perpendicular to the specimen axis and the bias fibers terminated on the cut edges in the specimen gage section. This edge effect is one factor that could contribute to a measured strength that is lower than the actual material strength in a structure without edge effects.

Littell, Justin D.↗
NASA NTRS2024

Exploring Standing and Reflected Slow-mode Waves in Flaring Coronal Loops: A Parametric Study Using 2.5D MHD Modeling

Abstract Recent observations of reflected propagating and standing slow-mode waves in hot flaring coronal loops have spurred our investigation into their underlying excitation and damping mechanisms. To understand these processes, we conduct 2.5D magnetohydrodynamic (MHD) simulations using an arcade active region model that includes a hot and dense loop. Our simulations allow for in-depth parametric investigations complementing and expanding our previous 3D MHD modeling results. We excite these waves using a large-amplitude, flow pulse applied at one footpoint of the loop in two distinct models as motivated by observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA). The first model (Model 1) incorporates classical compressive viscosity coefficient, while the second model (Model 2) adopts a 10-times enhanced viscosity coefficient. We obtain the following major results: (1) Our 2.5D MHD simulations reinforce previous conclusions derived from 1D and 3D MHD models that significantly enhanced viscosity is crucial for the rapid excitation of standing slow waves with damping times consistent with observations by Wang et al. (2015). (2)We uncover that nonlinearity in Model 1 delays the conversion of a reflected propagating wave into a standing wave. In contrast, Model 2 exhibits a much weak influence of nonlinearity on the excitation time of standing waves, thanks to the suppression of these effects by enhanced viscosity. (3) Our results reveal that the transverse temperature structure holds more influence on wave behavior than the density structure. In Model 1, increased loop temperature contrast significantly enhances wave trapping within the structure, mitigating the impact of temperature-dependent viscous damping. Conversely, in Model 2, the impact of temperature structure on wave behavior weakens in comparison to the effect of viscosity. (4) Model 1 displays evident nonlinear coupling to the fast and kink magnetoacoustic waves and pronounced wave leakage into the corona. Model 2 exhibits significantly weaker effects in this regard. Analyzing three observed wave events by SDO/AIA aligns with Model 2 predictions, providing further support for the substantial viscosity increase. Our 2.5D study unravels the complex interplay of wave-flow phenomena and nonlinear processes in coronal loops, extending our previous 1D modeling results to incorporate more realistic loop geometry. This provides insights into scenarios where 3D effects may be neglected, thereby enhancing our understanding of the intricate dynamics of the solar corona.

Tongjiang Wang↗
DOE OSTI2023

Nondestructively Visualizing and Understanding the Mechano-Electro-chemical Origins of “Soft Short” and “Creeping” in All-Solid-State Batteries

All-solid-state Li-metal batteries (ASLMBs) represent a significant breakthrough in the quest to overcome limitations associated with traditional Li-ion batteries, particularly in energy density and safety aspects. However, widespread implementation is stymied due to a lack of profound understanding of the complex mechano-electro-chemical behavior of Li metal in the ASLMBs. Herein, operando neutron imaging and X-ray computed tomography (XCT) are leveraged to nondestructively visualize Li behaviors within ASLMBs. This approach offers real-time observations of Li evolutions, both pre- and post- occurrence of a “soft short”. The coordination of 2D neutron radiography and 3D neutron tomography enables charting of the terrain of Li metal deformation operando. Concurrently, XCT offers a 3D insight into the internal structure of the battery following a “soft short”. Despite the manifestation of a “soft short”, the persistence of Faradaic processes is observed. To study the elusive “soft short”, phase field modeling is coupled with electrochemistry and solid mechanics theory. The research unravels how external pressure curbs dendrite growth, potentially leading to dendrite fractures and thus uncovering the origins of both “soft” and “hard” shorts in ASLMBs. Furthermore, by harnessing finite element modeling, it dive deeper into the mechanical deformation and the fluidity of Li metal.

25 ENERGY STORAGE↗
DOE OSTI2024

The Toughness of Interlocking Metasurfaces

Interlocking metasurfaces (ILMs) are arrays of autogenous latching unit cells patterned across a surface. These create structural joints similar to bioinspired suture joints but patterned over a 2D surface rather than a 1D seam. This enables ILMs to be an alternative to conventional joining technologies such as bolts, welds, and adhesives. However, compared to conventional joining methods, relatively little is known of the engineering considerations for designing structural ILMs. Herein, the interfacial toughness of an archetypal ILM is examined for the first time. Under the conditions studied here, the ILM is substantially tougher than the material from which it is made, in this case, exhibiting up to a 50% increase in interfacial crack initiation energy over the solid base material, a photocured 3D‐printed polymer. Through experimental tests using in‐situ digital image correlation along with complementary computational analyses, the mechanism of toughening in the ILM structure and the origins of toughness anisotropy are revealed. The increase in toughness is associated with cross‐cell interactions, that is, load‐sharing across unit cells, which give rise to a finite process zone length with different effective material properties. In this way, ILM toughening is analogous to crack blunting in ductile materials or fiber bridging in composites; yet here, the ILM is composed of a single‐phase base material and so the architected toughening is geometric in nature and hence amenable to future topological optimization.

fracture↗