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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

CALIBRATED ULTRA FAST IMAGE SIMULATIONS FOR THE DARK ENERGY SURVEY

Image simulations are becoming increasingly important in understanding the measurement process of the shapes of galaxies for weak lensing and the associated systematic effects. For this purpose we present the first implementation of the Monte Carlo Control Loops (MCCL), a coherent framework for studying systematic effects in weak lensing. It allows us to model and calibrate the shear measurement process using image simulations from the Ultra Fast Image Generator (UFig) and the image analysis software SExtractor. We apply this framework to a subset of the data taken during the Science Verification period (SV) of the Dark Energy Survey (DES). We calibrate the UFig simulations to be statistically consistent with one of the SV images, which covers ∼0.5 square degrees. We then perform tolerance analyses by perturbing six simulation parameters and study their impact on the shear measurement at the one-point level. This allows us to determine the relative importance of different parameters. For spatially constant systematic errors and point-spread function, the calibration of the simulation reaches the weak lensing precision needed for the DES SV survey area. Furthermore, we find a sensitivity of the shear measurement to the intrinsic ellipticity distribution, and an interplay between the magnitude-size and the pixel value diagnostics in constraining the noise model. This work is the first application of the MCCL framework to data and shows how it can be used to methodically study the impact of systematics on the cosmic shear measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

FEbeam: Cavity and electron emission data conversion, processing, and analysis. A freeware toolkit for rf injectors

FEbeam is an all-in-one field emission data processing interface with the capability to analyze the field emission cathode performance in an rf injector by extracting the field enhancement factor, local field, and effective emission area from the Fowler–Nordheim equations. It also has the capability of processing beam imaging micrographs using its sister software, FEpic. Furthermore, the current version of FEbeam was designed for the Argonne Cathode Test-stand of the Argonne Wakefield Accelerator facility switch yard. With slight modifications, FEbeam could work for many rf field emission injectors. This software is open-source and can be found at GitHub.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach

Highlights: • Surface degradation was monitored via mass loss measurement. • Observation of surface damage destruction was done using image analysis. • Shape parameters of surface defects change during cavitation. • Shape parameters changes are correlated to mass loss measurements. - Abstract: The aim of this study was to examine the influence of cavitation erosion on the morphology of defects formed on the surfaces of alumina-based materials. The alumina-based samples were exposed to cavitation erosion for 42 min. The damages that occurred were monitored at predefined time intervals by measuring the mass loss and observing the sample surfaces. Digital images of surfaces were processed using an image analysis software package to define morphological characteristics of the damages occurred. The calculated morphological parameters were subjected to analysis by pattern recognition techniques to correlate the appearance of particular morphological characteristics with the behavior of the material during cavitation erosion. The newly established method in describing cavitation erosion which uses pattern recognition approach for treatments of morphological parameters calculated for damages by image analysis tools gave the results efficient for material characterization as the traditional one.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Few-view cone-beam CT reconstruction with deformed prior image

Purpose: Prior images can be incorporated into the image reconstruction process to improve the quality of subsequent cone-beam CT (CBCT) images from sparse-view or low-dose projections. The purpose of this work is to develop a deformed prior image-based reconstruction (DPIR) strategy to mitigate the deformation between the prior image and the target image. Methods: The deformed prior image is obtained by a projection-based registration approach. Specifically, the deformation vector fields used to deform the prior image are estimated through iteratively matching the forward projection of the deformed prior image and the measured on-treatment projections. The deformed prior image is then used as the prior image in the standard prior image constrained compressed sensing (PICCS) algorithm. A simulation study on an XCAT phantom and a clinical study on a head-and-neck cancer patient were conducted to evaluate the performance of the proposed DPIR strategy. Results: The deformed prior image matches the geometry of the on-treatment CBCT more closely as compared to the original prior image. Consequently, the performance of the DPIR strategy from few-view projections is improved in comparison to the standard PICCS algorithm, based on both visual inspection and quantitative measures. In the XCAT phantom study using 20 projections, the average root mean squared error is reduced from 14% in PICCS to 10% in DPIR, and the average universal quality index increases from 0.88 in PICCS to 0.92 in DPIR. Conclusions: The present DPIR approach provides a practical solution to the mismatch problem between the prior image and target image, which improves the performance of the original PICCS algorithm for CBCT reconstruction from few-view or low-dose projections.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

System and method for remote detection and location of gas leaks

A system for monitoring for a gas leak from a gas containing structure is disclosed. The system includes a lens that directs an image of a scene of interest through an optical filter onto a detector. The filter is associated with the lens and the filter has one or more passbands that passes wavelengths which match one or more emission or reflectively wavelengths of the gas being monitored. A detector receives the image after the image passes through the lens and the filter. The detector generates image data representing the scene including the gas containing structure. A processor is configured to process the image data by executing machine executable code stored on a memory. The machine executable code processes the image data to identify turbulence flows in the image data such that turbulence flow indicates a gas leak, and generate and send an alert in response to the identification of a turbulence flow.

O'Neill, Mary D.↗
DOE OSTI2018

Graphene milling dynamics during helium ion beam irradiation

We explore the potential of the Helium Ion Microscope (HIM) as a tool for direct-write patterning of graphene and describe the underlying processes of graphene milling with image data processing. Controlled helium ion irradiation of suspended graphene conducted while monitoring the mill in-situ revealed the localized formation of nanopores, their growth, and coalescence. We also explore the effects of defects on the milling dynamics, and show that pre-exposed membranes rupture by cracking and rapid crack propagation at the edges of the growing defects. The mechanism for the rupturing process is described by local defect formation by excessive irradiation of helium ions, dictated by the scanning direction of the beam. As a result, these findings enrich fundamental understanding of the graphene milling process with a helium ion beam that, is necessary for high-resolution and high throughput patterning of graphene with nanoscale precision.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A small-volume, high-throughput approach for surface tension and viscosity measurements of liquid fuels

An ongoing effort looking at bioblendstocks to function as drop-in replacements or blending components for gasoline has identified a large number of candidate fuels. This work documents an approach for rapid screening of candidate fuels using relatively small sample sizes ($\mathcal{O}(\mu\,{\rm l})$) that targets two key physical properties of liquid fuels—surface tension and viscosity. The approach utilizes shape oscillation dynamics of single droplets generated by a piezo-electric device and their decay over time. Strobed imaging of the oscillation process is used along with image processing, edge detection, and data analysis to capture the decay of the oscillation over time. The time constant of the decay process along with oscillation frequency are then used to estimate viscosity and surface tension using a theory for small amplitude droplet oscillations. Measurements are obtained for primary reference fuels (isooctane and n-heptane) as well as candidate fuels from four bio-derived functional groups of interest. Measurement results for surface tension and viscosity are correlated with literature data as well as measurements from standard reference instruments. The measurement results show that the droplet oscillation based approach is capable of reproducing surface tension and viscosity values for the tested fuels within deviations of 7% and 13% respectively from literature data. Results are obtained using an average of 5 µl per fuel within about 20 s, thus demonstrating a small-volume, high-throughput approach that can be used for screening of candidate bioblendstock fuels.

09 BIOMASS FUELS↗
DOE OSTI2017

The Hyper Suprime-Cam software pipeline

Here in this article, we describe the optical imaging data processing pipeline developed for the Subaru Telescope’s Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope’s Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Compressed video camera with a moving patterned disk

A high-speed video system is disclosed that includes a moving image absorbing disk at an image plane. The disk has a pattern that passes and blocks image data. The disk is located between an event and an image sensor, or reflects an image to the image sensor. The disk is rotated at a speed that matches the desired reconstructed image frame rate. The image sensor frame data is processed using image reconstruction techniques, such as the D-AMP or TWIST algorithm, to recover a time sequence of reconstructed images. Additional images can be reconstructed for each image sensor frame if some spatial resolution is sacrificed. For continuous video, the disk speed is adjusted to the sensor frame rate. For burst mode, a single sensor image is acquired and a short image sequence is reconstructed. This image capture system works with a variety of radiations, including infrared, light, UV and X-rays.

42 ENGINEERING↗
DOE OSTI2025

Evaluating User Errors and Temporal Trends in Marine Fish Communities Using 360-Degree Underwater Photography

The use of environmental DNA (eDNA) sampling has been proposed as a complementary method to monitor fish species in marine environments, offering a non-invasive and potentially more efficient approach to marine species observations. eDNA monitoring could be especially useful in and around sites targeted for marine energy generation as these regions need regular monitoring that would be impractical with traditional techniques. Before we can fully rely upon eDNA, we must first verify its accuracy against other proven methods, such as the use of underwater photography. In this study, I deployed a 360-degree camera in the tidal channel of Sequim Bay once a month during several hours overlapping slack tide. I investigated how having multiple people identify and count fish on underwater images could affect the overall results. Using chi square tests in R, I compared my fish identifications and counts to those made by another intern on the same images recorded in August. I found significant differences in the number of species identified and the total individual counts between the two different datasets. I also tested the statistical differences in both Shannon diversity and Pielou evenness indices between the August, September, and November camera deployments using a Hutcheson t-test. Only one significant difference was found in the Shannon index comparisons, and none were found between the Pielou evenness comparisons. These findings show that if multiple identifiers are used to process underwater images, quality control checks must be made to reduce the potential for error. This also points toward the possibility to leverage more advanced image analysis processes, such as automated image analysis software. The findings from this study also show that the dynamics of marine fish communities can vary over a few months; however, further analysis is needed to determine the extent of the seasonal changes in Sequim Bay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗
DOE OSTI2018

Gamma Imaging Improvements for GrayQb™

SRNL’s Imaging, Robotics, and Radiation Systems Group has had several successful field deployments with the GrayQb™, a custom designed radiation mapping device. The GrayQb™ returned consistent radiation contour maps through its deployment and demonstrated its effectiveness in quickly and inexpensively capturing images of radiation hot spots. To process the images from the GrayQb™, the device must be recovered between each deployment. This is due to the GrayQb™’s use of Phosphor Storage Plates (PSPs), which are a standard X-ray imaging material in dentistry and oral applications. PSPs are highly sensitive to radiation; however, currently they must be processed through an external scanner. SRNL designed the GrayQb™ for radiation areas, and much effort is required to deploy and recover the GrayQb™. To reduce time and resources spent deploying and recovering the GrayQb™, SRNL is working to upgrade the device to read PSP images and transmit image data to an external location using an internal camera system eliminating the need to remove the PSP.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Purpose: Monte Carlo simulations were performed with the goal of verifying previously published physical measurements characterizing scatter as a function of apparent thickness. A secondary goal was to provide a way of determining what effect tissue glandularity might have on the scatter characteristics of breast tissue. The overall reason for characterizing mammography scatter in this research is the application of these data to an image processing-based scatter-correction program. Methods: MCNPX was used to simulate scatter from an infinitesimal pencil beam using typical mammography geometries and techniques. The spreading of the pencil beam was characterized by two parameters: mean radial extent (MRE) and scatter fraction (SF). The SF and MRE were found as functions of target, filter, tube potential, phantom thickness, and the presence or absence of a grid. The SF was determined by separating scatter and primary by the angle of incidence on the detector, then finding the ratio of the measured scatter to the total number of detected events. The accuracy of the MRE was determined by placing ring-shaped tallies around the impulse and fitting those data to the point-spread function (PSF) equation using the value for MRE derived from the physical measurements. The goodness-of-fit was determined for each data set as a means of assessing the accuracy of the physical MRE data. The effect of breast glandularity on the SF, MRE, and apparent tissue thickness was also considered for a limited number of techniques. Results: The agreement between the physical measurements and the results of the Monte Carlo simulations was assessed. With a grid, the SFs ranged from 0.065 to 0.089, with absolute differences between the measured and simulated SFs averaging 0.02. Without a grid, the range was 0.28–0.51, with absolute differences averaging −0.01. The goodness-of-fit values comparing the Monte Carlo data to the PSF from the physical measurements ranged from 0.96 to 1.00 with a grid and 0.65 to 0.86 without a grid. Analysis of the data suggested that the nongrid data could be better described by a biexponential function than the single exponential used here. The simulations assessing the effect of breast composition on SF and MRE showed only a slight impact on these quantities. When compared to a mix of 50% glandular/50% adipose tissue, the impact of substituting adipose or glandular breast compositions on the apparent thickness of the tissue was about 5%. Conclusions: The findings show agreement between the physical measurements published previously and the Monte Carlo simulations presented here; the resulting data can therefore be used more confidently for an application such as image processing-based scatter correction. The findings also suggest that breast composition does not have a major impact on the scatter characteristics of breast tissue. Application of the scatter data to the development of a scatter-correction software program can be simplified by ignoring the variations in density among breast tissues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Morphotype-resolved characterization of microalgal communities in a nutrient recovery process with ARTiMiS flow imaging microscopy

Microalgae-driven nutrient recovery represents a promising technology for phosphorus removal from wastewater while simultaneously generating biomass that can be valorized to offset treatment costs. As full-scale processes come online, system parameters including biomass composition must be carefully monitored to optimize performance and prevent culture crashes. In this study, flow imaging microscopy (FIM) was leveraged to characterize microalgal community composition in near real-time at a full-scale municipal wastewater treatment plant (WWTP) in Wisconsin, USA, and population and morphotype dynamics were examined to identify relationships between water chemistry, biomass composition, and system performance. Two FIM technologies, FlowCam and ARTiMiS, were evaluated as monitoring tools. ARTiMiS provided a more accurate estimate of total system biomass, and estimates derived from particle area as a proxy for biovolume yielded better approximations than particle counts. Deep learning classification models trained on annotated image libraries demonstrated equivalent performance between FlowCam and ARTiMiS, and convolutional neural network (CNN) classifiers proved significantly more accurate when compared to feature table-based dense neural network (DNN) models. Across a two-year study period, Scenedesmus spp. appeared most important for phosphorus removal, and were negatively impacted by elevated temperatures and increase in nitrite/nitrate concentrations. Chlorella and Monoraphidium also played an important role in phosphorus removal. For both Scenedesmus and Chlorella, smaller morphological types were more often associated with better system performance, whereas larger morphotypes likely associated with stress response(s) correlated with poor phosphorus recovery rates. Furthermore, these results demonstrate the potential of FIM as a critical technology for high-resolution characterization of industrial microalgal processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Impact of bowtie filter and object position on the two-dimensional noise power spectrum of a clinical MDCT system

Purpose: Noise characteristics of clinical multidetector CT (MDCT) systems can be quantified by the noise power spectrum (NPS). Although the NPS of CT has been extensively studied in the past few decades, the joint impact of the bowtie filter and object position on the NPS has not been systematically investigated. This work studies the interplay of these two factors on the two dimensional (2D) local NPS of a clinical CT system that uses the filtered backprojection algorithm for image reconstruction. Methods: A generalized NPS model was developed to account for the impact of the bowtie filter and image object location in the scan field-of-view (SFOV). For a given bowtie filter, image object, and its location in the SFOV, the shape and rotational symmetries of the 2D local NPS were directly computed from the NPS model without going through the image reconstruction process. The obtained NPS was then compared with the measured NPSs from the reconstructed noise-only CT images in both numerical phantom simulation studies and experimental phantom studies using a clinical MDCT scanner. The shape and the associated symmetry of the 2D NPS were classified by borrowing the well-known atomic spectral symbols s, p, and d, which correspond to circular, dumbbell, and cloverleaf symmetries, respectively, of the wave function of electrons in an atom. Finally, simulated bar patterns were embedded into experimentally acquired noise backgrounds to demonstrate the impact of different NPS symmetries on the visual perception of the object. Results: (1) For a central region in a centered cylindrical object, an s-wave symmetry was always present in the NPS, no matter whether the bowtie filter was present or not. In contrast, for a peripheral region in a centered object, the symmetry of its NPS was highly dependent on the bowtie filter, and both p-wave symmetry and d-wave symmetry were observed in the NPS. (2) For a centered region-ofinterest (ROI) in an off-centered object, the symmetry of its NPS was found to be different from that of a peripheral ROI in the centered object, even when the physical positions of the two ROIs relative to the isocenter were the same. (3) The potential clinical impact of the highly anisotropic NPS, caused by the interplay of the bowtie filter and position of the image object, was highlighted in images of specific bar patterns oriented at different angles. The visual perception of the bar patterns was found to be strongly dependent on their orientation. Conclusions: The NPS of CT depends strongly on the bowtie filter and object position. Even if the location of the ROI with respect to the isocenter is fixed, there can be different symmetries in the NPS, which depend on the object position and the size of the bowtie filter. For an isolated off-centered object, the NPS of its CT images cannot be represented by the NPS measured from a centered object.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

EXD HME MicroCT Data Acquisition, Processing and Data Request Overview

This document is a short summary of the steps required for MicroCT evaluation of a specimen. This includes data acquisition through image analysis, for the EXD HME program. Expected outputs for each stage are provided. Data shall be shipped to LLNL as described herein.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Full-frame, programmable hyperspectral imager

A programmable, many-band spectral imager based on addressable spatial light modulators (ASLMs), such as micro-mirror-, micro-shutter- or liquid-crystal arrays, is described. Capable of collecting at once, without scanning, a complete two-dimensional spatial image with ASLM spectral processing applied simultaneously to the entire image, the invention employs optical assemblies wherein light from all image points is forced to impinge at the same angle onto the dispersing element, eliminating interplay between spatial position and wavelength. This is achieved, as examples, using telecentric optics to image light at the required constant angle, or with micro-optical array structures, such as micro-lens- or capillary arrays, that aim the light on a pixel-by-pixel basis. Light of a given wavelength then emerges from the disperser at the same angle for all image points, is collected at a unique location for simultaneous manipulation by the ASLM, then recombined with other wavelengths to form a final spectrally-processed image.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

MO-DE-207-04: Imaging educational program on solutions to common pediatric imaging challenges

This imaging educational program will focus on solutions to common pediatric imaging challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. The educational program will begin with a detailed discussion of the optimal configuration of fluoroscopes for general pediatric procedures. Following this introduction will be a focused discussion on the utility of Dual Energy CT for imaging children. The third lecture will address the substantial challenge of obtaining consistent image post -processing in pediatric digital radiography. The fourth and final lecture will address best practices in pediatric MRI including a discussion of ancillary methods to reduce sedation and anesthesia rates. Learning Objectives: To learn techniques for optimizing radiation dose and image quality in pediatric fluoroscopy To become familiar with the unique challenges and applications of Dual Energy CT in pediatric imaging To learn solutions for consistent post-processing quality in pediatric digital radiography To understand the key components of an effective MRI safety and quality program for the pediatric practice.

60 APPLIED LIFE SCIENCES↗