Container Surface Evaluation: Background Estimation, Background Removal, Feature Detection, and Image Ranking
No abstract available.
47 OTHER INSTRUMENTATION↗
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Results for “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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Transportable, Low-Dose Active Fast-Neutron Imaging
This document contains a description of the method of transportable, low-dose active fast-neutron imaging as developed by ORNL. The discussion begins with the technique and instrumentation and continues with the image reconstruction and analysis. The analysis discussion includes an example of how a gap smaller than the neutron production spot size and detector size can be detected and characterized depending upon the measurement time.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Spotlight SAR Data Collection Geometry from ECEF Coordinates
High-performance spotlight Synthetic Aperture Radar (SAR) requires measurement of the radars motion during the synthetic aperture. A convenient coordinate frame for motion measurement is often not the convenient coordinate frame for motion compensation during the SAR data generation and image formation processing. A convenient frame for radar motion measurement is the Earth-Centered Earth-Fixed (ECEF) coordinate frame, whereas spotlight SAR processing typically require s polar coordinates from a selected Scene Reference Point (SRP). This report presents the conversion from ECEF coordinates to appropriate parameters for SAR processing.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Dewarping Algorithm Comparison: Local vs. Global 2D Polynomial Interpolation for Dewarping
This is a short report for collaborators in the radiography working group related to Cygnus radiography.
97 MATHEMATICS AND COMPUTING↗
The Tiny Heater: Creating Heat with Hybrid Nano-Antennas [LDRD HQ Highlights Article]
SRNL scientists demonstrate that an electromagnetic field, either as a light or magnetic field, is selectively coupled to shape-selective hybrid nano-antennas for efficient thermal processes. Localized heating occurs extremely fast, reducing the ‘wasted' thermal load on the environment. Being non-contact, efficient, and highly selective, the required input energy is greatly diminished. By strategically placing nano-antennas at desired locations, heat can be controlled at the nano-level. The location for nano-antennas, and the subsequent energy deposition, may be fine-tuned through specific chemical, steric, or magnetic interactions. The nano-antennas, composed of combinations of plasmonic, magnetic, and hydride components, are used for controlled release of hydrogen isotopes, chemotherapy drugs, environmental contaminants, enhanced catalytic processes, (bio)imaging and therapeutics.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Predictive Data-driven Platform for Subsurface Energy Production
Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.
58 GEOSCIENCES↗
Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery
Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this project, we used UAV-based multispectral imagery collected from MicaSense RedEdge-M on a DJI Matrice 600 Pro for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. The raw images were processed with Pix4D Mapper to create the reflectance data, and vegetation indices were calculated from a UAV-based multispectral camera. Statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potential for multiple traits associated with sustainable production of switchgrass. One statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait.
CBI↗
Sharing leaky-integrate-and-fire neurons for memory-efficient spiking neural networks
Spiking Neural Networks (SNNs) have gained increasing attention as energy-efficient neural networks owing to their binary and asynchronous computation. However, their non-linear activation, that is Leaky-Integrate-and-Fire (LIF) neuron, requires additional memory to store a membrane voltage to capture the temporal dynamics of spikes. Although the required memory cost for LIF neurons significantly increases as the input dimension goes larger, a technique to reduce memory for LIF neurons has not been explored so far. To address this, we propose a simple and effective solution, EfficientLIF-Net, which shares the LIF neurons across different layers and channels. Our EfficientLIF-Net achieves comparable accuracy with the standard SNNs while bringing up to ~4.3× forward memory efficiency and ~21.9× backward memory efficiency for LIF neurons. We conduct experiments on various datasets including CIFAR10, CIFAR100, TinyImageNet, ImageNet-100, and N-Caltech101. Furthermore, we show that our approach also offers advantages on Human Activity Recognition (HAR) datasets, which heavily rely on temporal information. The code has been released at https://github.com/Intelligent-Computing-Lab-Yale/EfficientLIF-Net.
60 APPLIED LIFE SCIENCES↗
Digital Miniature Cathode Ray Magnetometer
In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of operating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which then emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only records the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innovation lies in the combination of electron beam projection, CMOS imager scintillation-based detection, and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device’s utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe’s performance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.
Turqueti, Marcos↗
On a Method For Reconstructing Computed Tomography Datasets from an Unstable Source
As work continues in neutron computed tomography, at Los Alamos Neutron Science Center (LANSCE) and other locations, source reliability over the long imaging times is an issue of increasing importance. Moreover, given the time commitment involved in a single neutron image, it is impractical to simply discard a scan and restart in the event of beam instability. In order to mitigate the cost and time associated with these options, strategies are presented in the current work to produce a successful reconstruction of computed tomography data from an unstable source. The present work uses a high energy neutron tomography dataset from a simulated munition collected at LANSCE to demonstrate the method, which is general enough to be of use in conjunction with unstable X-ray computed tomography sources as well.
47 OTHER INSTRUMENTATION↗
Gold Nanoparticles AuNP Decorated on Fused Graphene-like Materials for Application in a Hydrogen Generation
The search for a sustainable, alternative fuel source to replace fossil fuels has led to an increased interest in hydrogen fuel. This combustible gas is not only clean-burning but can readily be produced via the hydrolysis of sodium borohydride. The main drawback of this reaction is that the reaction occurs relatively slowly and requires a catalyst to improve efficiency. This study explored a novel composite material made by combining gold nanoparticles and fused graphene-like materials (AuFGLM) as a catalyst for generating hydrogen via sodium borohydride. The novel fused graphene-like material (FGLM) was made with a sustainable dextrose solution and by using a pressure-processing method. Imaging techniques showed that FGLM appears to be an effective support template for nanoparticles. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and Raman spectroscopy were used to characterize and determine the size, shape, and structure of nanoparticles and composites. The TEM study characterized the fused carbon backbone as it began to take on a rounder shape. The TEM images also revealed that the average diameter of the gold nanoparticle was roughly 23 nm. The FTIR study confirmed O-H, C-C, and C=O as functional groups in the materials. The EDS analysis showed that the composite contained approximately 6.3% gold by weight. The crystal structures of FGLM and AuFGLM were identified via P-XRD analysis. Various reaction conditions were used to test the catalytic ability of AuFGLM, including various solution pHs, temperatures, and doses of NaBH 4 . It was observed that optimal reaction conditions included high temperature, an acidic solution pH, and a higher dose of NaBH 4 . The activation energy of the reaction was determined to be 45.5 kJ mol -1 , and it was found that the catalyst could be used multiple times in a row with an increased volume of hydrogen produced in ensuing trials. The activation energy of this novel catalyst is competitive compared to similar catalysts and its ability to produce hydrogen over multiple uses makes the material an exciting choice for catalyzing the hydrolysis of NaBH 4 for use as a hydrogen fuel source.
08 HYDROGEN↗
Region-Based Convolutional Neural Network for Wind Turbine Wake Characterization in Complex Terrain
We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.
17 WIND ENERGY↗
TEMPORAL EVOLUTION OF CHROMOSPHERIC OSCILLATIONS IN FLARING REGIONS: A PILOT STUDY
We have analyzed H α intensity images obtained at a 1 minute cadence with the Global Oscillation Network Group (GONG) system to investigate the properties of oscillations in the 0–8 mHz frequency band at the location and time of strong M- and X-class flares. For each of three subregions within two flaring active regions, we extracted time series from multiple distinct positions, including the flare core and quieter surrounding areas. The time series were analyzed with a moving power-map analysis to examine power as a function of frequency and time. We find that, in the flare core of all three subregions, the low-frequency power (∼1–2 mHz) is substantially enhanced immediately prior to and after the flare, and that power at all frequencies up to 8 mHz is depleted at flare maximum. This depletion is both frequency- and time-dependent, which probably reflects the changing depths visible during the flare in the bandpass of the filter. These variations are not observed outside the flare cores. The depletion may indicate that acoustic energy is being converted into thermal energy at flare maximum, while the low-frequency enhancement may arise from an instability in the chromosphere and provide an early warning of the flare onset. Dark lanes of reduced wave power are also visible in the power maps, which may arise from the interaction of the acoustic waves and the magnetic field.
79 ASTRONOMY AND ASTROPHYSICS↗
Quasar variability in the mid-infrared
The Decadal IRAC Boötes Survey is a mid-IR variability survey of the ∼9 sq. deg. of the NDWFS Boötes Field and extends the time baseline of its predecessor, the Spitzer Deep, Wide-Field Survey (SDWFS), from 4 to 10 years. The Spitzer Space Telescope visited the field five times between 2004 and 2014 at 3.6 and 4.5 μm. We provide the difference image analysis photometry for a half a million mostly extragalactic sources. In mid-IR color–color plane, sources with quasar colors constitute the largest variability class (75%), 16% of the variable objects have stellar colors and the remaining 9% have the colors of galaxies. Adding the fifth epoch doubles the number of variable active galactic nuclei (AGNs) for the same false positive rates as in SDWFS, or increases the number of sources by 20% while decreasing the false positive rates by factors of 2–3 for the same variability amplitude. We quantify the ensemble mid-IR variability of ∼1500 spectroscopically confirmed AGNs using single power-law structure functions (SFs), which we find to be steeper (index γ≈0.45) than in the optical (γ≈0.3), leading to much lower amplitudes at short time-lags. This provides evidence for large emission regions, smoothing out any fast UV/optical variations, as the origin of infrared quasar variability. The mid-IR AGN SF slope γ seems to be uncorrelated with both the luminosity and rest-frame wavelength, while the amplitude shows an anti-correlation with the luminosity and a correlation with the rest-frame wavelength.
79 ASTRONOMY AND ASTROPHYSICS↗
SEARCHING FOR BINARY Y DWARFS WITH THE GEMINI MULTI-CONJUGATE ADAPTIVE OPTICS SYSTEM (GeMS)
The NASA Wide-field Infrared Survey Explorer (WISE) has discovered almost all the known members of the new class of Y-type brown dwarfs. Most of these Y dwarfs have been identified as isolated objects in the field. It is known that binaries with L- and T-type brown dwarf primaries are less prevalent than either M-dwarf or solar-type primaries, they tend to have smaller separations and are more frequently detected in near-equal mass configurations. The binary statistics for Y-type brown dwarfs, however, are sparse, and so it is unclear if the same trends that hold for L- and T-type brown dwarfs also hold for Y-type ones. In addition, the detection of binary companions to very cool Y dwarfs may well be the best means available for discovering even colder objects. We present results for binary properties of a sample of five WISE Y dwarfs with the Gemini Multi-Conjugate Adaptive Optics System. We find no evidence for binary companions in these data, which suggests these systems are not equal-luminosity (or equal-mass) binaries with separations larger than ∼0.5–1.9 AU. For equal-mass binaries at an age of 5 Gyr, we find that the binary binding energies ruled out by our observations (i.e., 10{sup 42} erg) are consistent with those observed in previous studies of hotter ultra-cool dwarfs.
79 ASTRONOMY AND ASTROPHYSICS↗
Kiloparsec mass/light offsets in the galaxy pair-Lyα emitter lens system SDSS J1011+0143
We report the discovery of significant mass/light offsets in the strong gravitational lensing system SDSS J1011+0143. We use the high-resolution Hubble Space Telescope (HST) F555W- and F814W-band imaging and Sloan Digital Sky Survey (SDSS) spectroscopy of this system, which consists of a close galaxy pair with a projected separation of ≈4.2 kpc at z{sub lens} ∼ 0.331 lensing an Lyα emitter (LAE) at z{sub source} = 2.701. Comparisons between the mass peaks inferred from lens models and light peaks from HST imaging data reveal significant spatial mass/light offsets as large as 1.72 ± 0.24 ± 0.34 kpc in both filter bands. Such large mass/light offsets, not seen in isolated field lens galaxies and relaxed galaxy groups, may be related to the interactions between the two lens galaxies. The detected mass/light offsets can potentially serve as an important test for the self-interacting dark matter model. However, other mechanisms such as dynamical friction on spatially differently distributed dark matter and stars could produce similar offsets. Detailed hydrodynamical simulations of galaxy–galaxy interactions with self-interacting dark matter could accurately quantify the effects of different mechanisms. The background LAE is found to contain three distinct star-forming knots with characteristic sizes from 116 to 438 pc. It highlights the power of strong gravitational lensing in probing the otherwise too faint and unresolved structures of distance objects below subkiloparsec or even 100 pc scales through its magnification effect.
79 ASTRONOMY AND ASTROPHYSICS↗
SEARCHING FOR THE HR 8799 DEBRIS DISK WITH HST /STIS
We present a new algorithm for space telescope high contrast imaging of close-to-face-on planetary disks called Optimized Spatially Filtered (OSFi) normalization. This algorithm is used on HR 8799 Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph (STIS) coronagraphic archival data, showing an over-luminosity after reference star point-spread function (PSF) subtraction that may be from the inner disk and/or planetesimal belt components of this system. The PSF-subtracted radial profiles in two separate epochs from 2011 and 2012 are consistent with one another, and self-subtraction shows no residual in both epochs. We explore a number of possible false-positive scenarios that could explain this residual flux, including telescope breathing, spectral differences between HR 8799 and the reference star, imaging of the known warm inner disk component, OSFi algorithm throughput and consistency with the standard spider normalization HST PSF subtraction technique, and coronagraph misalignment from pointing accuracy. In comparison to another similar STIS data set, we find that the over-luminosity is likely a result of telescope breathing and spectral difference between HR 8799 and the reference star. Thus, assuming a non-detection, we derive upper limits on the HR 8799 dust belt mass in small grains. In this scenario, we find that the flux of these micron-sized dust grains leaving the system due to radiation pressure is small enough to be consistent with measurements of other debris disk halos.
79 ASTRONOMY AND ASTROPHYSICS↗
High contrast imaging with Spitzer: constraining the frequency of giant planets out to 1000 au separations
We report results of a re-analysis of archival Spitzer IRAC direct imaging surveys encompassing a variety of nearby stars. Our sample is generated from the combined observations of 73 young stars (median age, distance, spectral type = 85 Myr, 23.3 pc, G5) and 48 known exoplanet host stars with unconstrained ages (median distance, spectral type = 22.6 pc, G5). While the small size of Spitzer provides a lower resolution than 8 m class AO-assisted ground-based telescopes, which have been used for constraining the frequency of 0.5–13 M {sub J} planets at separations of 10–10{sup 2} au, its exquisite infrared sensitivity provides the ability to place unmatched constraints on the planetary populations at wider separations. Here we apply sophisticated high-contrast techniques to our sample in order to remove the stellar point-spread function and to open up sensitivity to planetary mass companions down to 5″ separations. This enables sensitivity to 0.5–13 M {sub J} planets at physical separations on the order of 10{sup 2}–10{sup 3} au, allowing us to probe a parameter space that has not previously been systematically explored to any similar degree of sensitivity. Based on a color and proper motion analysis, we do not record any planetary detections. Exploiting this enhanced survey sensitivity, employing Monte Carlo simulations with a Bayesian approach, and assuming a mass distribution of dn/dm∝m{sup −1.31}, we constrain (at 95% confidence) a population of 0.5–13 M {sub J} planets at separations of 100–1000 au with an upper frequency limit of 9%.
79 ASTRONOMY AND ASTROPHYSICS↗