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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Stereoscopic Planar Laser-Induced Fluorescence Imaging at 500 kHz

A new measurement technique for obtaining time- and spatially-resolved image sequences in hypersonic flows is developed. Nitric-oxide planar laser-induced fluorescence (NO PLIF) has previously been used to investigate transition from laminar to turbulent flow in hypersonic boundary layers using both planar and volumetric imaging capabilities. Low flow rates of NO were typically seeded into the flow, minimally perturbing the flow. The volumetric imaging was performed at a measurement rate of 10 Hz using a thick planar laser sheet that excited NO fluorescence. The fluorescence was captured by a pair of cameras having slightly different views of the flow. Subsequent stereoscopic reconstruction of these images allowed the three-dimensional flow structures to be viewed. In the current paper, this approach has been extended to 50,000 times higher repetition rates. A laser operating at 500 kHz excites the seeded NO molecules, and a camera, synchronized with the laser and fitted with a beam-splitting assembly, acquires two separate images of the flow. The resulting stereoscopic images provide three-dimensional flow visualizations at 500 kHz for the first time. The 200 ns exposure time in each frame is fast enough to freeze the flow while the 500 kHz repetition rate is fast enough to time-resolve changes in the flow being studied. This method is applied to visualize the evolving hypersonic flow structures that propagate downstream of a discrete protuberance attached to a flat plate. The technique was demonstrated in the NASA Langley Research Center s 31-Inch Mach 10 Air Tunnel facility. Different tunnel Reynolds number conditions, NO flow rates and two different cylindrical protuberance heights were investigated. The location of the onset of flow unsteadiness, an indicator of transition, was observed to move downstream during the tunnel runs, coinciding with an increase in the model temperature.

Medford, Taylor L.↗
DOE OSTI2020

Model-based Reconstruction for Single Particle Cryo-Electron Microscopy

Single particle cryo-electron microscopy is a vital tool for 3D characterization of protein structures. A typical workflow involves acquiring projection images of a collection of randomly oriented particles, picking and classifying individual particle projections by orientation, and finally using the individual particle projections to reconstruct a 3D map of the electron density profile. The reconstruction is challenging because of the low signal-to-noise ratio of the data, the unknown orientation of the particles, and the sparsity of data especially when dealing with flexible proteins where there may not be sufficient data corresponding to each class to obtain an accurate reconstruction using standard algorithms. In this paper we present a model-based image reconstruction technique that uses a regularized cost function to reconstruct the 3D density map by assuming known orientations for the particles. Our method casts the reconstruction as minimizing a cost function involving a novel forward model term that accounts for the contrast transfer function of the microscope, the orientation of the particles and the center of rotation offsets. We combine the forward model term with a regularizer that enforces desirable properties in the volume to be reconstructed. Using simulated data, we demonstrate how our method can significantly improve upon the typically used approach.

Venkatakrishnan, Singanallur↗
DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗
NASA NTRS1971

The automation of the stellar proper motion survey

A microdensitometer, scanning pairs of star plates of identical areas of the sky taken a decade apart, is coupled to a magnetic tape unit through a data acquisition system. This system performs an image density threshold level selection for each plate and a buffer memory system to smooth the data flow as well as analog and digital display controls. The data from the tape are processed later by a large scale high speed computer which reconstructs the scanned images, discovers, measures, and documents stellar proper motions by precise comparison of corresponding areas of the two star plates to detect those images which have moved at least 0.10 seconds annually in the time interval between the exposures.

Newcomb, J. S.↗
DOE OSTI2023

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗
DOE OSTI2021

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗
NASA NTRS1973

Martian lineaments from Mariner 6 and 7 images

Mariner 6 and 7 images are used to investigate the nature and importance of linear surface trends on Mars. Cross correlations of frequency-azimuth distributions of linear trends from different Mariner frames indicate that lineations not recognized as topographic features have a component of artifacts, probably introduced during digital reconstruction of the images. Consequently, topographic and nontopographic lineations should be treated separately prior to interpretation of the data. Similar statistical tests may aid in the analysis of surface trends from future satellites and space probes.

Schultz, P. H.↗
DOE OSTI2020

Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC

ynchrotron light sources are routinely used to perform imaging experiments. In this paper, we review the relevant computational stages, identify bottlenecks, and highlight future opportunities to streamline data acquisition for experimental microscopy workflows. We demonstrate our preliminary exploration with an end-to-end scientific workflow on Summit based on micro-computed tomography data. Computational elements include: 1) reconstruction of volumetric image data; 2) denoising with deep neural networks; and 3) non-local means based segmentation and quantitative analysis.

Mcclure, James↗
DOE OSTI2026

SBND Shower Reconstruction with SPINE

The Short-Baseline Near Detector (SBND) is a liquid argon time projection chamber (LArTPC) neutrino detector in the Short-Baseline Neutrino (SBN) program at Fermilab. SBND is designed to investigate the Low-Energy Excess (LEE), an unexplained excess of electron-like events observed by previous short-baseline neutrino experiments that may point to physics beyond the Standard Model. In LArTPC detectors, precise shower reconstruction is essential for distinguishing electrons from photons, a key requirement for testing possible explanations of the LEE and improving $\nu_e$ event selection. In this poster, the reconstruction studies using the Scalable Particle Imaging with Neural Embeddings (SPINE), a machine learning based reconstruction framework for particle imaging detectors will be presented. SPINE combines sparse convolutional neural networks (CNN) and graph neural networks (GNN) to enable detailed reconstruction and characterization of neutrino interactions in LArTPC detectors. Shower calorimetry and kinematic reconstruction are performed in dedicated post-processing stages. Strong agreement between data and Monte Carlo simulation will be demonstrated, indicating high-precision detector calibration and reconstruction performance. The agreement between reconstructed and true electron shower energy will also be discussed, emphasizing the robustness of the shower reconstruction performance. These results demonstrate the unprecedented precision achievable with SPINE in SBND, highlighting their potential for future high-resolution neutrino measurements.

Fan, Castaly [Florida U.; Fermilab] (ORCID:0000000↗
DOE OSTI2022

A comparison of deep-learning-based inpainting techniques for experimental X-ray scattering

The implementation is proposed of image inpainting techniques for the reconstruction of gaps in experimental X-ray scattering data. The proposed methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution neural networks and mixed-scale dense networks, to reconstruct the missing information in experimental scattering images. In particular, the recovered pixel intensities are evaluated against their corresponding ground-truth values using the mean absolute error and the correlation coefficient metrics. The results demonstrate that the proposed methods achieve better performance than traditional inpainting algorithms such as biharmonic functions. Overall, tunable U-Net and mixed-scale dense network architectures achieved the best reconstruction performance among all the tested algorithms, with correlation coefficient scores greater than 0.9980.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Progress Toward Gamma-Ray Imaging for Automated Holdup Measurement in Gloveboxes

Shielded gloveboxes are currently being constructed to facilitate dilution and disposal of many tons of excess plutonium oxide. Measuring holdup in these gloveboxes is expected to be challenging because of the limited available lines of sight through the glovebox shielding. A system of gamma-ray imagers is being developed to provide localization and quantification for holdup. The system will be mounted above the glovebox, where there is minimal shielding. Multiple imagers with overlapping coded-aperture fields of view are employed to enable three-dimensional reconstruction. Compton reconstruction is also available to localize sources outside the coded-aperture field of view. Improved uncertainties with respect to current techniques are expected by virtue of the fixed installation, spectroscopic performance of the detectors, and iterative image reconstruction techniques. Measurement campaigns have been undertaken at an active glovebox at Savannah River Site to test the gamma-ray imaging system in an operational environment, providing a simple test of a single imager that mimics the geometry of the installation proposed for future shielded gloveboxes. Data taken during quiescent periods in the glovebox were used to measure the buildup of material on an outlet filter and record a trend over time. Calibration data was taken with known sources to simplify analysis and provide a reliable assay of the filter. Resulting images make it possible to isolate the filter from other sources and recognize compromised data. This paper will present details of the measurement and analysis methods.

Schmitt, Kyle↗
DOE OSTI2021

Global field reconstruction from sparse sensors with Veronoi tessellation-assisted deep learning

Achieving accurate and robust global situational awareness of a complex time-evolving field from a limited number of sensors has been a longstanding challenge. This reconstruction problem is especially difficult when sensors are sparsely positioned in a seemingly random or unorganized manner, which is often encountered in a range of scientific and engineering problems. Moreover, these sensors can be in motion and can become online or offline over time. The key leverage in addressing this scientific issue is the wealth of data accumulated from the sensors. As a solution to this problem, we propose a data-driven spatial field recovery technique founded on a structured grid-based deep-learning approach for arbitrary positioned sensors of any numbers. It should be noted that the naïve use of machine learning becomes prohibitively expensive for global field reconstruction and is furthermore not adaptable to an arbitrary number of sensors. In the present work, we consider the use of Voronoi tessellation to obtain a structured-grid representation from sensor locations enabling the computationally tractable use of convolutional neural networks. One of the central features of the present method is its compatibility with deep-learning based super-resolution reconstruction techniques for structured sensor data that are established for image processing. The proposed reconstruction technique is demonstrated for unsteady wake flow, geophysical data, and three-dimensional turbulence. The current framework is able to handle an arbitrary number of moving sensors, and thereby overcomes a major limitation with existing reconstruction methods. The presented technique opens a new pathway towards the practical use of neural networks for real-time global field estimation.

Fukami, Kai↗
NASA NTRS2018

System and Method for Active Multispectral Imaging and Optical Communications

Provided is a system and method for active multispectral imaging having a transmitter that uses narrowband optical radiation to dynamically illuminate an object with modulated structured light in multiple spectral bands, and a receiver that includes an independent panchromatic imager. The transmitter and receiver can be operated in a bistatic decoupled configuration to enable passive multispectral synthesis, illumination-invariant sensing, optical communications, and the ability for the transmitter to emit a sequence of spectral bands in an order that is unknown to the receiver, and the receiver is able to passively decode the spectral identity from a band identifier embedded in the modulated structured light. The receiver passively decodes embedded high-bandwidth simplex communications while reconstructing calibrated multispectral images at video frame rates.

Chirayath, Ved↗
NASA NTRS1973

Design and evaluation of controls for drift, video gain, and color balance in spaceborne facsimile cameras

The facsimile camera is an optical-mechanical scanning device which has become an attractive candidate as an imaging system for planetary landers and rovers. This paper presents electronic techniques which permit the acquisition and reconstruction of high quality images with this device, even under varying lighting conditions. These techniques include a control for low frequency noise and drift, an automatic gain control, a pulse-duration light modulation scheme, and a relative spectral gain control. Taken together, these techniques allow the reconstruction of radiometrically accurate and properly balanced color images from facsimile camera video data. These techniques have been incorporated into a facsimile camera and reproduction system, and experimental results are presented for each technique and for the complete system.

Katzberg, S. J.↗
DOE OSTI2025

Three-dimensional reconstruction of THz near-fields from a LiNbO3 optical rectification source

Terahertz (THz) generation by optical rectification in LiNbO3 (LN) is a widely used technique for generating intense THz radiation. The spatiotemporal characterization of THz pulses from these sources is currently limited to far-field methods. While simulations of tilted pulse front THz generation have been published, little work has been done to measure the near-field properties of the THz source. A better understanding of the THz near-field properties will improve optimization of THz generation efficiency, transport, and coupling. We demonstrate a technique for quantitative spatiotemporal characterization of single-cycle strong-field THz pulses with 2-D near-field electro-optic imaging. We have reconstructed the full temporal 3D THz near-field and shown how the phase front can be tailored by controlling the incident pump pulse.

Gabriel, Annika↗
DOE OSTI2025

ED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation

The Erosion-Dilation continuous Phase-Size Distribution, ED-cPSD, is an application for calculating continuous pore and particle-size distribution from digital reconstructions and/or image-based structural data. It is based on the erosion-dilation continuous phase-size distribution method. A continuous size distribution is a measure of the probability density of finding a particle or pore of a certain size. These distributions are of interest in any field of study involving porous media, including but not limited to electrochemistry, petroleum engineering, geology, and food science. The algorithm behind the software provides a computationally efficient way to calculate phase-size distributions for large domains. For a 3D battery electrode reconstruction with 1.3 x 10 8 voxels, the particle size distribution is derived in under 2 min on a desktop, while also retaining flexibility and computational efficiency for HPC-scale multi-threading. The software can handle structures with over 10 9 voxels. The algorithm is roughly 280 times faster than a previous version on the same task.

Characterization↗
DOE OSTI2022

Machine Learning of In-situ Temperature Reconstruction from Metal-nanoparticle Thermometry on Transmission Electron Microscopy

Utilizing Python programming language and third-party libraries, 2D temperature fields were reconstructed from TEM images demonstratively and a GUI was created. Local temperatures can be fast read on TEM at the nanoscale based on the nanoparticle thermometry. The Artificial Intelligence technique would speed up the in-situ heating TEM research and make real-time in-situ temperature monitoring possible at nanoscale.

42 ENGINEERING↗