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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Non-invasive Optical End-to-End Test of a Large TMA Telescope (JWST) from the Intermediate Focus

The James Webb Space Telescope (JWST) requires testing of the full optical system in a cryogenic vacuum environment before launch. Challenges with the telescope architecture and the test environment lead to placing removable optical test sources at the Cassegrain intermediate focus of the Telescope. The Science Instrument suite will be used to align the telescope and to verify the wavefront error. The Science Instruments capture test images that are analyzed using focus diverse phase retrieval. The wavefront sensing algorithms have the large dynamic range required to measure the relatively small wavefronts of interest in the presence of the large aberrations resulting from the off-axis source locations at the intermediate focus. These inherent aberrations of the off-axis design are removed analytically from the measured data. The test design and in-situ wavefront sensing process enables a number of tests to verify the alignment and optical quality of the system.

Whitman, Tony↗
NASA NTRS2012

NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly.

Source record↗
DOE OSTI2023

n-Propylbenzene Droplet Combustion: Experiments and Numerical Modeling

n-Propylbenzene (PB, C9H12, 432K boiling point) is important as a constituent in surrogates for some transportation fuels but little is understood about its droplet burning characteristics. We present an experimental and numerical study of a fuel droplet burning under conditions where the sole means of gas transport is fuel evaporation at the droplet surface thereby creating a one-dimensional gas transport that is amenable to detailed numerical modeling. The one-dimensional gas transport that results is amenable to detailed numerical modeling. Initial droplet diameters (Do) ranged from 0.3 mm to about 5 mm to better understand the mechanisms that control burning over such a wide range of Do. For Do < 1 mm droplets were burned while anchored to 14 m SiC fibers within a sealed container in free-fall during which time the droplets were ignited by spark discharge and the burning process recorded by video cameras. Larger and free-floating droplets were studied in the spaced-based platform of the orbiting International Space Station for Do > 1.0 mm which provided unlimited times for experimental observation. Measurements of droplet, flame and soot shell diameters were made and are discussed in the presentation. The experimental results showed formation of optically thick soot clouds developing during burning that required a robust image analysis algorithm to enable measurement of droplet diameter. The measured droplet diameters were well predicted by a numerical model that included soot formation, a PB kinetic mechanism comprising 576 species and 27369 reactions, unsteady gas and liquid transport, variable properties and radiative transport. Flame diameters showed more variability compared to the simulations, depending on how the flame was defined (peak gas temperature and OH concentration). Droplets burned slower as Do was increased and the PB sooting propensity increased with Do. Flame extinction was observed for Do > 3.3 mm indicating a strong effect of radiation as Do was increased compared to the smaller droplet diameters examined where extinction was not experimentally observed. For the largest droplets examined the possibility that the observed extinction is indicative of a transition to cool flame burning is still under investigation.

Guo, Songtao↗
DOE OSTI2020

Accuracy of volumetric flow rate inflow/outflow measurement by integrating PIV velocity fields

In this paper, the usefulness of planar Particle Image Velocimetry (PIV) measurements to determine the volumetric flow rate from a rectangular or round jet exit is assessed. Both two-component PIV (2C–PIV) and through-plane three-component (3C) stereo PIV (SPIV) data sets were acquired at the exit of a turbulent, rectangular nozzle and a round nozzle with Reynolds numbers between 10 000 and 100 000. The PIV data sets were processed using a variety of algorithms. The time-averaged results were then spatially integrated across the jet exits and compared to a calibrated flow meter. Recommendations for each method are developed and discussed with potential drawbacks. The accuracy of the measurement was found to be a weak function of the Reynolds number of the flow. Furthermore, two-component PIV was found to underestimate the volumetric flow rate by 1%–4% depending on the integration scheme and SPIV underestimated volumetric flow rate by 2%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Automated nuclear cloud feature extraction from film

Chemical, biological, radiological, nuclear, and explosives incidents require rapid detection and characterization for appropriate response. For a nuclear detonation, visible-light cameras may be used to locate the cloud and characterize fallout deposition when coupled with numerical models. Films from the United States’ nuclear testing era compose the only sizeable collection of imagery depicting high-yield detonations. These films offer unique insights into characteristics of flows involving scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models for nuclear fallout transport, either as part of emergency response or forensic activities. In this work, we implement modern computer vision and machine learning techniques to identify and track the cloud automatically and subsequently determine the time dependence of some of its features. We trained a ResNet-18 image classifier on hundreds of images to categorize nuclear cloud morphology. Each category or cloud regime is determined by early cloud evolution and is associated to constitutive properties of the flow, such as distribution of vorticity. Next, we identified keypoint features using the KAZE algorithm and tracked these keypoints in the images, allowing us to determine the dimensions and velocities of the cloud across film frames. These measurements converted to real-world units provide valuable experimental data that can be used in the development and validation of nuclear cloud models. We compared the results of this method against manual cloud rise measurements from two different films. In one, our automated method accelerated the feature extraction process without sacrificing measurement accuracy.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
NASA NTRS1992

Passive microwave precipitation mapping and retrieval simulation

A numerical simulation of the satellite-based multispectral passive microwave mapping and precipitation retrieval process is described. The simulation contains three major components: (1) the forward radiative transfer calculation; (2) the sensor observation simulation; and (3) the precipitation retrieval algorithm. Secondary components include a Karhunen-Loeve transformation module and antenna pattern deconvolution module. The simulation facilitates the investigation of candidate precipitation retrieval algorithms using sub-Nyquist brightness temperature imagery, and the comparison of the relative merits of proposed radiometric systems such as the EOS multispectral imaging microwave radiometer (MIMR), the tropical rainfall measurement mission (TRMM) microwave imager (TRMM TMI), and the geosynchronous satellite sensors. A procedure for retrieving rain rates using a statistical iterative approach is outlined.

Skofronick, G. M.↗
NASA NTRS1994

High performance compression of science data

Two papers make up the body of this report. One presents a single-pass adaptive vector quantization algorithm that learns a codebook of variable size and shape entries; the authors present experiments on a set of test images showing that with no training or prior knowledge of the data, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard. The second paper addresses motion compensation, one of the most effective techniques used in the interframe data compression. A parallel block-matching algorithm for estimating interframe displacement of blocks with minimum error is presented. The algorithm is designed for a simple parallel architecture to process video in real time.

Storer, James A.↗
NASA NTRS2012

Synegies Between Visible/Near-Infrared Imaging Spectrometry and the Thermal Infrared in an Urban Environment: An Evaluation of the Hyperspectral Infrared Imager (HYSPIRI) Mission

A majority of the human population lives in urban areas and as such, the quality of urban environments is becoming increasingly important to the human population. Furthermore, these areas are major sources of environmental contaminants and sinks of energy and materials. Remote sensing provides an improved understanding of urban areas and their impacts by mapping urban extent, urban composition (vegetation and impervious cover fractions), and urban radiation balance through measures of albedo, emissivity and land surface temperature (LST). Recently, the National Research Council (NRC) completed an assessment of remote sensing needs for the next decade (NRC, 2007), proposing several missions suitable for urban studies, including a visible, near-infrared and shortwave infrared (VSWIR) imaging spectrometer and a multispectral thermal infrared (TIR) instrument called the Hyperspectral Infrared Imagery (HyspIRI). In this talk, we introduce the HyspIRI mission, focusing on potential synergies between VSWIR and TIR data in an urban area. We evaluate potential synergies using an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and MODIS-ASTER (MASTER) image pair acquired over Santa Barbara, United States. AVIRIS data were analyzed at their native spatial resolutions (7.5m VSWIR and 15m TIR), and aggregated 60 m spatial resolution similar to HyspIRI. Surface reflectance was calculated using ACORN and a ground reflectance target to remove atmospheric and sensor artifacts. MASTER data were processed to generate estimates of spectral emissivity and LST using Modtran radiative transfer code and the ASTER Temperature Emissivity Separation algorithm. A spectral library of common urban materials, including urban vegetation, roofs and roads was assembled from combined AVIRIS and field-measured reflectance spectra. LST and emissivity were also retrieved from MASTER and reflectance/emissivity spectra for a subset of urban materials were retrieved from co-located MASTER and AVIRIS pixels. Fractions of Impervious, Soil, Green Vegetation (GV) and Non-photosynthetic Vegetation (NPV), were estimated using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to AVIRIS data at 7.5, 15 and 60 m spatial scales. Surface energy parameters, including albedo, vegetation cover fraction, broadband emissivity and LST were also determined for urban and natural land-cover classes in the region. Fractions were validated using 1m digital photography.

Roberts, Dar A.↗
NASA NTRS2016

Cross-correlation and image alignment for multi-band IR sensors

We present the development of a cross-­‐correlation algorithm for correlating objects in the long wave, mid wave and short wave Infrared sensor arrays. The goal is to align the images in the multi-­‐ sensor suite by correlating multiple key features in the images. Due to the wavelength differences, the object appears very differently in the sensor images even the sensors focus on the same object. In order to perform accurate correlation of the same object in the multi-­‐band images, we perform image processing on the images so that the features of the object become similar to each other. Fourier domain band pass filters are used to enhance the images. Mexican Hat and Gaussian Derivative Wavelets are used to further enhance the features of the object. A Python based QT graphical user interface has been implemented to carry out the process. We show reliable results of the cross-­‐correlation of the objects in multiple band videos.

Torres, Gilbert↗
NASA NTRSDate not supplied

Hourly Carbon Fluxes Estimation Using the GOES Advanced Baseline Imager (ABI) Data Over the Conterminous USA

Tremendous efforts by Fluxnet scientists over the past few decades have made thousands of site-years of carbon flux observations available for advancing our understanding of carbon cycling in terrestrial ecosystems. One of key Fluxnet measurements is net ecosystem exchange (NEE) as it is directly related to carbon budget of terrestrial ecosystems. However, carbon flux estimation studies using satellite remote sensing have focused mainly on daily Gross Primary Production (GPP). The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. Because daily NEE is close to zero value, the carbon flux models using the polar orbiting satellite data have not been well used for NEE estimation. The new generation of geostationary satellite sensors (e.g., GOES Advanced Baesline Imager (ABI) and Himawari Advanced Himawari Imager (AHI)) provide frequent observations, often less than every 10 minutes. Here, we use GOES ABI data to estimate hourly NEE over the conterminous USA. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and, in particular, solar radiation that is directly derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Fluxnet data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

Geostationary satellite↗
DOE OSTI2021

LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure (LoTToR) v1.0

The low-tilt tomographic reconstruction (LoTToR) method is a post-processing method to correct the missing-wedge artifact, which contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination. Moreover, the software can be used for hospital computer tomography (CT) to reduce the radiation damage to patients without reducing the CT image quality.

Ren, Gang↗
DOE OSTI2022

CodEx: A Modular Framework for Joint Temporal De-Blurring and Tomographic Reconstruction

In many computed tomography (CT) imaging applications, it is important to rapidly collect data from an object that is moving or changing with time. Tomographic acquisition is generally assumed to be step-and-shoot, where the object is rotated to each desired angle, and a view is taken. However, step-and-shoot acquisition is slow and can waste photons, so in practice fly-scanning is done where the object is continuously rotated while collecting data. However, this can result in motion-blurred views and consequently reconstructions with severe motion artifacts. In this paper, we introduce CodEx, a modular framework for joint de-blurring and tomographic reconstruction that can effectively invert the motion blur introduced in sparse view fly-scanning. The method is a synergistic combination of a novel acquisition method with a novel non-convex Bayesian reconstruction algorithm. CodEx works by encoding the acquisition with a known binary code that the reconstruction algorithm then inverts. Using a well chosen binary code to encode the measurements can improve the accuracy of the inversion process. The CodEx reconstruction method uses the alternating direction method of multipliers (ADMM) to split the inverse problem into iterative deblurring and reconstruction sub-problems, making reconstruction practical to implement. Here we present reconstruction results on both simulated and binned experimental data to demonstrate the effectiveness of our method.

42 ENGINEERING↗
NASA NTRS2007

Ground-Based Correction of Remote-Sensing Spectral Imagery

Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.

Alder-Golden, Steven M.↗
DOE OSTI2020

Path-Based Dictionary Augmentation: A Framework for Improving $k$ -Sparse Image Processing

In this study, we have previously shown that augmenting orthogonal matching pursuit (OMP) with an additional step in the identification stage of each pursuit iteration yields improved $k$ -sparse reconstruction and denoising performance relative to baseline OMP. At each iteration a “path” or geodesic, is generated between the two dictionary atoms that are most correlated with the residual and from this path a new atom that has a greater correlation to the residual than either of the two bracketing atoms is selected. Here, we provide new computational results illustrating improvements in sparse coding and denoising on canonical datasets using both learned and structured dictionaries. The two methods of constructing a path are investigated for each dictionary type: the Euclidean geodesic formed by a linear combination of the two atoms and the 2-Wasserstein geodesic corresponding to the optimal transport map between the atoms. We prove here the existence of a higher-correlation atom in the Euclidean case under assumptions on the two bracketing atoms and introduce algorithmic modifications to improve the likelihood that the bracketing atoms meet those conditions. Although, we demonstrate our augmentation on OMP alone, in general it may be applied to any reconstruction algorithm that relies on the selection and sorting of high-similarity atoms during an analysis or identification phase.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

The Future: Nasa’s Surface Biology and Geology Mission and the Dark (Aquatic) Side

With the release of NASA’s Earth System Observatory (ESO) measurement targets that includes studying the Earth’s Surface Biology and Geology (SBG), a global visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager have been planned to launch in the late 2020s. This mission will enable unprecedented interdisciplinary science and applications relevant to studying the biology and geology of the Earth's surface. Measurement targets are directly aligned for studying coastal and inland waters ecosystems and water quality, including coralreef ecosystems, snow and ice, mineralogy, volcanology, biology, ecology, biodiversity, and components of radiative forcing from the surface such as greenhouse gas emissions. The observations not only have scientific value in studying feedbacks and interactions of surface processes (e.g., harmful algal blooms, domoic acid, oil spills, and other hazardous events), but also societal benefit – with the capacity to support real-world decision-making such as response to theseevents and inland water conservation, protection of drinking water quality for public and environmental health, and habitat conservation. The work presented here outlines the conducted mission and architecture study and the initiation of science performance trades (signal sensitivity; spectral, spatial, and temporal resolution; and atmospheric effects) informing the design of the SBG segment of the ESO providing the most value to myriad science and applications as possible. Science and applications synergies and algorithms with the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) and the Geostationary Littoral Imaging and Monitoring Radiometer (GLIMR) is opportunistic for advancing aquatics research and applications.

THE FUTURE↗
DOE OSTI2023

Unsupervised classification for region of interest in X-ray ptychography

X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data outside the region of interest (RoI) based on the multimodal features present in the diffraction patterns. The preprocessing time for the proposed method is inconsequential in contrast to the resource-intensive reconstruction process, leading to an impressive reduction in the data workload to a mere 20% of the initial dataset. This capability consequently reduces computational time dramatically while preserving reconstruction quality. Through further segmentation of the diffraction patterns, our proposed approach can also detect features that are smaller than beam size and correctly classify them as within the RoI.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

A Simple, Scalable, Script-based Science Processor

The production of Earth Science data from orbiting spacecraft is an activity that takes place 24 hours a day, 7 days a week. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), this results in as many as 16,000 program executions each day, far too many to be run by human operators. In fact, when the Moderate Resolution Imaging Spectroradiometer (MODIS) was launched aboard the Terra spacecraft in 1999, the automated commercial system for running science processing was able to manage no more than 4,000 executions per day. Consequently, the GES DAAC developed a lightweight system based on the popular Per1 scripting language, named the Simple, Scalable, Script-based Science Processor (S4P). S4P automates science processing, allowing operators to focus on the rare problems occurring from anomalies in data or algorithms. S4P has been reused in several systems ranging from routine processing of MODIS data to data mining and is publicly available from NASA.

Lynnes, Christopher↗
NASA NTRS2008

Using Electronic Noses to Detect Tumors During Neurosurgery

It has been proposed to develop special-purpose electronic noses and algorithms for processing the digitized outputs of the electronic noses for determining whether tissue exposed during neurosurgery is cancerous. At present, visual inspection by a surgeon is the only available intraoperative technique for detecting cancerous tissue. Implementation of the proposal would help to satisfy a desire, expressed by some neurosurgeons, for an intraoperative technique for determining whether all of a brain tumor has been removed. The electronic-nose technique could complement multimodal imaging techniques, which have also been proposed as means of detecting cancerous tissue. There are also other potential applications of the electronic-nose technique in general diagnosis of abnormal tissue. In preliminary experiments performed to assess the viability of the proposal, the problem of distinguishing between different types of cultured cells was substituted for the problem of distinguishing between normal and abnormal specimens of the same type of tissue. The figure presents data from one experiment, illustrating differences between patterns that could be used to distinguish between two types of cultured cancer cells. Further development can be expected to include studies directed toward answering questions concerning not only the possibility of distinguishing among various types of normal and abnormal tissue but also distinguishing between tissues of interest and other odorous substances that may be present in medical settings.

Homer, Margie L.↗