Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “image generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,135 records · Page 63

Characterization of the upgraded single-line-of-sight time-resolved x-ray imager using short-pulse visible and UV lasers

The single-line-of-sight time-resolved x-ray imager (SLOS-TRXI), a fast-gated x-ray imager used for capturing x-ray self-emission in inertial confinement fusion experiments on OMEGA, has been upgraded and characterized. SLOS-TRXI combines an electron-dilation imager and a hybrid complementary metal–oxide–semiconductor (hCMOS) sensor to capture multiple gated frames on a single line of sight with a temporal resolution of ~40 ps and a spatial resolution of 10 µm. The original hCMOS sensor with four frames was replaced with a newer-generation hCMOS sensor having eight frames. Gate characterizations of both the sensor and the entire SLOS-TRXI diagnostic were performed using ~10-ps FWHM visible (2ω) and UV (4ω) short-pulse lasers, respectively. A stepped echelon was used to generate a train of five UV laser pulses having an interpulse separation of 30 ± 3 ps. Characterization results of the hCMOS gating (2.28 ± 0.02-ns FWHM on average) and a temporal resolution of the upgraded SLOS-TRXI (34 ± 4-ps FWHM on average) are presented. A temporal magnification for the electron-dilation imager between 40 and 60 was inferred from the characterization results. Furthermore, the spatial resolution of the upgraded SLOS-TRXI remains the same in light of this work.

47 OTHER INSTRUMENTATION↗

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗

QuGAN: A Quantum State Fidelity based Generative Adversarial Network

In the recent years, Generative Adversarial Networks (GANs) have been arguably one of the largest strides forward in Deep Learning. Many papers illustrate the use of GANs to accomplish extremely impressive goals, such as text-to-image or image augmentation. Specifically, GANs have seen this success in the computer vision domain. However, GANs are not without their own set of problems. GANs are computationally expensive, sometimes computationally prohibitive, and can suffer a multitude of convergence problems. As research on classical GANs continues to push the topic further, a branch of GANs, namely Quantum GANs, has seen research interest in the past years. In this work, we intend to push this research further with an illustration of a Quantum GAN architecture that provide stable convergence of the model and is extended onto real data sets. Furthermore, unlike many other Quantum GANs out there, our model's GAN architecture runs the discriminator and the generator primarily on Quantum hardware through the use of a Quantum-based similarity metric. When compared to the very few other Quantum GAN papers, our architecture leads to significantly better results in almost all aspects.

Stein, Samuel A.↗

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↗

Root image collection from a genotype by environment (GxE) root architecture study of the bioenergy species, Populus trichocarpa

Here we present a curated dataset; raw images of fresh roots collected from a genotype by environment (growth matrix) greenhouse root architecture study of the bioenergy species, Populus trichocarpa. Five separate experiments were performed to generate the dataset. Biological replicates (ramets, vegetative propagants) of Populus trichocarpa genotypes BESC 24 and BESC 375 were used for all experiments. The first two experiments were an eight-week and a six-week pot experiment where plants with grown in 4" X 14" sized pots were filled with Farfard 3B potting soil (Fafard Sungro #3B), and watered twice daily. Average greenhouse humidity and growth temperature were around 50-60% and 23°C, respectively. Ramets of P. trichocarpa genotypes BESC 24 and BESC 375 were used in various experiments. The source of this material was dormant field cuttings grown in greenhouse. The second experiment was a Microcosm root architecture experiment. This was done in a microcosm built with double-decker tissue culture Magenta box. Tissue culture plants with new root initials were transferred to microcosm with pro choice rapid dry growth matrix with 1x Hoagland’s solution pH5.7 and grown for six weeks until harvest. Temperature was held at ~22°C. The closed container trapped moisture. The source material was tissue culture stock plants established from shoot tips of greenhouse stock plants (obtained from same set of dormant field cuttings as rest of the study). For the remaining two experiments, greenwood stem cuttings from greenhouse grown plants were grown in six-week rhizotron and two-week hydroponics experiments in the greenhouse. For rhizotron experiments, plants were grown in 2-D rhizotron with black panels on both sides (31cm H x 30cm L x 1.2cm W) and watered daily. For hydroponics experiment, plants were grown in a 15ml falcon tube with distilled water and covered in foil and shaken a few times a day. Greenhouse temperature was held at ~ 23°C and humidity was between 50-60%. Stems were cut off and the root system was separated, gently washed to rid of matrix, immersed in a water tray and scanned for obtaining raw root images reported here. All scans of roots floating in a water tray were performed using an Epson Perfection V850 Pro Photo Scanner. Additional meta data is embedded in the raw image files.

59 BASIC BIOLOGICAL SCIENCES↗

Wire, hybrid, and laser-cut X-pinches as Talbot–Lau backlighters for electron density diagnostics

Talbot–Lau x-ray deflectometry (TXD) enables refraction-based imaging for high-energy-density physics experiments, and thus, it has been studied and developed with the goal of diagnosing plasmas relevant to inertial confinement and magnetic liner inertial fusion. X-pinches, known for reliably generating fast (~1 ns), small (~1 µm) x-ray sources, were driven on the compact current driver generator for ablation structure and implosion studies (~200 kA, 150 ns) as a potential backlighter source for TXD. Considering that different X-pinch configurations have characteristic advantages and drawbacks as x-ray generating loads, three distinct copper X-pinch configurations were studied: the wire X-pinch, the hybrid X-pinch, and the laser-cut X-pinch. Furthermore, the Cu K-shell emission from each configuration was characterized and analyzed regarding the specific backlighter requirements for an 8 keV TXD system: spatial and temporal resolution, number of sources, time of emission, spectrum, and reproducibility. Recommendations for future experimental improvements and applications are presented. The electron density of static objects was retrieved from Moiré images obtained through TXD. This allowed to calculate the mass density of static samples within 4% of the expected value for laser-cut X-pinches, which were found to be the optimal X-pinch configuration for TXD due to their high reproducibility, small source size (≤5 µm), short duration (~1 ns), and up to 106 W peak power near 8 keV photon energy. Plasma loads were imaged through TXD for the first-time using laser-cut X-pinch backlighting. Experimental images were compared with simulations from the x-ray wave-front propagation code, demonstrating that TXD can be a powerful x-ray refraction-based diagnostic for dense Z-pinch loads. Future plans for Talbot–Lau interferometry diagnostics in the pulsed-power environment are described.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Megahertz Rate Optical Diagnostics of Explosively Generated Soot

Detonation of a solid explosive produces a turbulent and luminous post‐detonation fireball containing condensed carbon soot. Diagnostics of soot dynamics are needed for model validation and to interpret emission signals. Diffuse back‐illumination extinction imaging (DBI‐EI) and laser‐induced incandescence (LII) are two common optical diagnostics for flame soot. This work extends both to measure time‐resolved soot dynamics from a 12 mm HMX hemisphere. DBI‐EI measured line‐of‐sight optical extinction exceeds 99% in some regions. Results are tomographically inverted to obtain a signal proportional to the soot volume fraction. Pulse‐burst LII measures are presented at 1 MHz. For the first time, LII results are combined with DBI‐EI extinction measurements to quantify and correct for signal trapping. Following this, spatially and temporally resolved DBI‐EI and LII measures are shown to be in reasonable agreement. Finally, experimental results are compared against recently developed simulations. Quantitative differences in the soot mixing dynamics are resolved. These findings motivate future model improvements and demonstrate ongoing needs for diagnostic advancements for heavily sooting environments.

diffuse back-illumination extinction imaging↗

Finding Hidden Patterns in High Resolution Wind Flow Model Simulations

Wind flow data is critical in terms of investment decisions and policy making. High resolution data from wind flow model simulations serve as a supplement to the limited resource of original wind flow data collection. Given the large size of data, finding hidden patterns in wind flow model simulations are critical for reducing the dimensionality of the analysis. In this work, we first perform dimension reduction with two autoencoder models: the CNN-based autoencoder (CNN-AE) [1], and hierarchical autoencoder (HIER-AE) [2], and compare their performance with the Principal Component Analysis (PCA). We then investigate the super-resolution of the wind flow data. By training a Generative Adversarial Network (GAN) with 300 epochs, we obtained a trained model with 2× resolution enhancement. We compare the results of GAN with Convolutional Neural Network (CNN), and GAN results show finer structure as expected in the data field images. Also, the kinetic energy spectra comparisons show that GAN outperforms CNN in terms of reproducing the physical properties for high wavenumbers and is critical for analysis where high-wavenumber kinetics play an important role.

97 MATHEMATICS AND COMPUTING↗

Boron-Based Neutron Scintillator Screen Characterization with X-Rays and Neutrons

Recent work on boron-based neutron scintillator screens suggests these screens can offer superior performance when compared to commonly used screens. Borated neutron scintillator screens perform well in terms of light output (5-6 times greater than a standard Gadox screen) and detection effi-ciency (larger than standard LiF+ZnS screens). However, previously manu-factured boron-based screens have exhibited non-uniform surface coating and a poor mixture between phosphor and converter particles. The objective of this work was to evaluate newly fabricated scintillator screens to deter-mine if enhanced fabrication methods produced a more homogeneous distribution between neutron converter and scintillation phosphor particles. Uniformity of scintillator material deposition was also inspected. This new iteration of screens appeared more uniform than previous generations with the new coating method improving surface chemistry and scintillator material homogeneity. Additionally, a new methodology for screen characterization, involving the correlation of a neutron image taken with a borated scintillator screen to X-ray computed tomography of that same screen, was demonstrated to elucidate a relationship between scintillator screen thickness and relative light output of the screen under neutron exposure. This method suggested that the ideal thickness of scintillator material was ~150 µm to maximize light output of the screen.

36 - MATERIALS SCIENCE↗

Computing diffraction patterns of microstructures from phase-field simulations

The diffraction pattern of a material contains information not only on the crystal structures of its constituting phases, but also on its mesoscale spatial distributions of phases, grains, and ferroelastic, ferroelectric, and ferromagnetic domains. While diffraction patterns from experiments such as X-ray diffraction are presented in the reciprocal or Fourier space, mesoscale microstructure models such as the phase-field method naturally produce real-space images of spatial distribution of chemical composition, structural, and ferroic domains. Although one could rather readily compute the Fourier amplitudes of chemical and structural domain distributions generated by mesoscale simulations, they only contain information about the length scale and alignment of the real-space chemical and structure domains. Therefore, a direct comparison between diffraction experiments and mesoscale microstructure simulations is not possible. Here, we develop a theoretical approach to directly compute the crystal diffraction patterns of microstructures predicted by phase-field simulations. In particular, we consider five representative examples of microstructure patterns involving purely compositional domains, a single pair of tetragonal twin structures, multiple twin variants in a hexagonal system, ferroelectric polar vortices, and polycrystalline grains. The results are compared with previous experimental observations as well as X-ray diffraction experiments performed in the present study. Furthermore, the theoretical framework allows one to directly connect material microstructures and diffraction patterns predicted from phase-field simulations and the corresponding diffraction patterns from experiments, and thus providing guidance to experimental diffraction characterization and interpretation of microstructures.

36 MATERIALS SCIENCE↗

Experimental data for damage mechanics simulation challenge

While there are many computational approaches for simulating damage in rock and other materials, few have been ground truth tested with either known experimental data or with blind data sets. Here, in this work, we present a bench-mark laboratory data set for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile materials. The samples were fabricated through additive manufacturing to produce repeatable specimens designed to fail in controlled ways. The failure was induced in the samples using a 3-point bending test to produce different Modes such as Mode I and mixed Modes including I-II, I-III and I-II-III Modes to generate a calibration data set and a blind challenge data set. Data collected included spatial and temporal measurements from traditional digital load–displacement sensors, 2D digital image correlation measurement to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry, and laser profilometry to capture surface roughness. The data sets are available, on a data repository, to the community to advance computational models to improve our ability to predict damage in brittle-ductile materials.

3-point bending↗

Persistent global greening over the last four decades using novel long-term vegetation index data with enhanced temporal consistency

Advanced Very High-Resolution Radiometer (AVHRR) satellite observations have provided the longest global daily records from 1980s, but the remaining temporal inconsistency in vegetation index datasets has hindered reliable assessment of vegetation greenness trends. To tackle this, we generated novel global long-term Normalized Difference Vegetation Index (NDVI) and Near-Infrared Reflectance of vegetation (NIRv) datasets derived from AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS). We addressed residual temporal inconsistency through three-step post processing including cross-sensor calibration among AVHRR sensors, orbital drifting correction for AVHRR sensors, and machine learning-based harmonization between AVHRR and MODIS. After applying each processing step, we confirmed the enhanced temporal consistency in terms of detrended anomaly, trend and interannual variability of NDVI and NIRv at calibration sites. Our refined NDVI and NIRv datasets showed a persistent global greening trend over the last four decades (NDVI: 0.0008 yr -1 ; NIRv: 0.0003 yr -1 ), contrasting with those without the three processing steps that showed rapid greening trends before 2000 (NDVI: 0.0017 yr -1 ; NIRv: 0.0008 yr -1 ) and weakened greening trends after 2000 (NDVI: 0.0004 yr -1 ; NIRv: 0.0001 yr -1 ). These findings highlight the importance of minimizing temporal inconsistency in long-term vegetation index datasets, which can support more reliable trend analysis in global vegetation response to climate changes.

54 ENVIRONMENTAL SCIENCES↗

Microcavity-like exciton-polaritons can be the primary photoexcitation in bare organic semiconductors

Strong-coupling between excitons and confined photonic modes can lead to the formation of new quasi-particles termed exciton-polaritons which can display a range of interesting properties such as super-fluidity, ultrafast transport and Bose-Einstein condensation. Strong-coupling typically occurs when an excitonic material is confided in a dielectric or plasmonic microcavity. Here, we show polaritons can form at room temperature in a range of chemically diverse, organic semiconductor thin films, despite the absence of an external cavity. We find evidence of strong light-matter coupling via angle-dependent peak splittings in the reflectivity spectra of the materials and emission from collective polariton states. We additionally show exciton-polaritons are the primary photoexcitation in these organic materials by directly imaging their ultrafast (5 × 10 6 m s –1 ), ultralong (~270 nm) transport. These results open-up new fundamental physics and could enable a new generation of organic optoelectronic and light harvesting devices based on cavity-free exciton-polaritons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatial resolution in secondary-electron microscopy

Here, we first review the significance of resolution and contrast in electron microscopy, and the effect of the electron optics on these two quantities. We then outline the physics of the generation of secondary electrons (SE) and their transport and emission from the surface of a specimen. Contrast and resolution are discussed for different kinds of SE imaging in scanning (SEM) and scanning-transmission (STEM) instruments, with some emphasis on the observation of individual atoms and atomic columns in a thin specimen. The possibility of achieving atomic resolution from a bulk specimen at SEM energies is also considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On the impact of the galaxy window function on cosmological parameter estimation

One important source of systematics in galaxy redshift surveys comes from the estimation of the galaxy window function. Up until now, the impact of the uncertainty in estimating the galaxy window function on parameter inference has not been properly studied. In this paper, we show that the uncertainty and the bias in estimating the galaxy window function will be salient for ongoing and next-generation galaxy surveys using a simulation-based approach. With a specific case study of cross-correlating emission-line galaxies from the DESI Legacy Imaging Surveys and the Planck cosmic microwave background lensing map, we show that neural network-based regression approaches to modelling the window function are superior in comparison to linear regression-based models. Here, we additionally show that the definition of the galaxy overdensity estimator can impact the overall signal-to-noise of observed power spectra. Finally, we show that the additive biases coming from the window functions can significantly bias the modes of the inferred parameters and also degrade their precision. Thus, a careful understanding of the window functions will be essential to conduct cosmological experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Structural basis for ring-opening fluorescence by the RhoBAST RNA aptamer

Abstract Tagging RNAs with fluorogenic aptamers has enabled imaging of transcripts in living cells, revealing novel aspects of RNA metabolism and dynamics. While a diverse set of fluorogenic aptamers has been developed, a new generation of aptamers uses the ring-opening of spirocyclic rhodamine dyes to achieve robust performance in live mammalian cells. These fluorophores have two chemical states: a cell-permeable spirocyclic state and a fluorescent zwitterionic state. The SpyRho555 dye is mostly non-fluorescent in solution and becomes fluorescent in complex with the RhoBAST aptamer. To understand the basis for RhoBAST-SpyRho555 fluorogenicity, we have determined crystal structures of RhoBAST in complex with 5-carboxytetramethylrhodamine and a SpyRho555 analogue, MaP555. RhoBAST is organized by a perfect four-way junction that positions two loops to form the dye-binding pocket. The core of the ligand resides between a tri-adenine floor and a single guanine base, largely driven by π-stacking interactions. Importantly, the unpaired guanine interacts with the 3-position group of MaP555 to stabilize the open conformation, supported by mutagenesis data, and may play an active role in promoting the open conformation of the dye. This work has implications for the development of new fluorogenic aptamers with improved properties using structure-guided design approaches.

Biochemistry & Molecular Biology↗

Cycle-Consistent Adversarial Networks for Realistic Pervasive Change Generation in Remote Sensing Imagery

This paper introduces a new method of generating realistic pervasive changes in the context of evaluating the effectiveness of change detection algorithms in controlled settings. The method - a cycle-consistent adversarial network (CycleGAN) - requires low quantities of training data to generate realistic changes. Here we show an application of CycleGAN in creating realistic snow-covered scenes of multispectral Sentinel-2 imagery, and demonstrate how these images can be used as a test bed for anomalous change detection algorithms.

97 MATHEMATICS AND COMPUTING↗

Multiscale characterization and representation of variability in ceramic matrix composites

Low density, high strength, and high creep and oxidation resistance properties of ceramic matrix composites (CMCs) make them an ideal choice for use in extreme environments in space and military applications. This paper presents a detailed characterization study of structural and manufacturing flaws in Carbon fiber Silicon-Carbide-Nitride matrix (C/SiNC) CMCs at different length-scales. Energy-dispersive spectroscopy (EDS) is used for the chemical characterization of the material’s elemental constituents. High-resolution multiscale graphs obtained from scanning electron microscope (SEM) and confocal laser scanning microscope (LSM) are used to characterize the distribution and morphology of defects at different length scales. This is followed by the classification and quantification of the common manufacturing defects. An image processing algorithm based on the image segmentation process is developed to quantify the variability of various scale-dependent architectural parameters. Finally, a three-dimensional stochastic representative volume element (SRVE) generation algorithm is developed to provide precise representations of material textures at multiple length scales. The developed algorithm accurately accounts for material features and flaws based on a range of multiscale structural and defects characterization results.

36 MATERIALS SCIENCE↗