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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

A comparison of LOWTRAN-7 corrected Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data with ground spectral measurements

Atmospheric correction of imaging spectroscopy data is required for quantitative analysis. Different models were proposed for atmospheric correction of these data. LOWTRAN-7 is a low-resolution model and computer code for predicting atmospheric transmittance and background radiance from 0 to 50,00 cm(sup -1) which was developed by the Air Force Geophysics Laboratory. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data used are radiometrically calibrated and include the 28 Sep. 1989 Providence Fan flight line segment 07, California. It includes a dark gravel surface defined as a calibration site by the Geologic Remote Sensing Field Experiment (GRSFE). Several ground measurements of portable spectrometer DAEDALUS AA440 Spectrafax were taken during the GRSFE, July 1989 field campaign. Comparisons of the LOWTRAN-7 corrected AVIRIS data with the ground spectrometer measurement were made.

Xu, Peng-Yang↗
NASA NTRS1997

Neutral-Line Magnetic Shear and Enhanced Coronal Heating in Solar Active Regions

By examining the magnetic structure at sites in the bright coronal interiors of active regions that are not flaring but exhibit persistent strong coronal heating, we establish some new characteristics of the magnetic origins of this heating. We have examined the magnetic structure of these sites in five active regions, each of which was well observed by both the Yohkoh SXT and the Marshall Space Flight Center Vector Magnetograph and showed strong shear in its magnetic field along part of at least one neutral line (polarity inversion). Thus, we can assess whether this form of nonpotential field structure in active regions is a characteristic of the enhanced coronal heating and vice versa. From 27 orbits' worth of Yohkoh SXT images of the five active regions, we have obtained a sample of 94 persistently bright coronal features (bright in all images from a given orbit), 40 long (greater than or approximately equals 20,000 km) neutral-line segments having strong magnetic shear throughout (shear angle greater than 45 deg), and 39 long neutral-line segments having weak magnetic shear throughout (shear angle less than 45 deg). From this sample, we find that: (1) all of our persistently bright coronal features are rooted in magnetic fields that are stronger than 150 G; (2) nearly all (95%) of these enhanced coronal features are rooted near neutral lines (closer than 10,000 km); (3) a great majority (80%) of the bright features are rooted near strong-shear portions of neutral lines; (4) a great majority (85%) of long strong-shear segments of neutral lines have persistently bright coronal features rooted near them; (5) a large minority (40%) of long weak-shear segments of neutral lines have persistently bright coronal features rooted near them; and (6) the brightness of a persistently bright Coronal feature often changes greatly over a few hours. From these results, we conclude that most persistent enhanced heating of coronal loops in active regions: (1) requires the presence of a polarity inversion in the magnetic field near at least one of the loop footpoints; (2) is greatly aided by the presence of strong shear in the core magnetic field along that neutral line; and (3) is controlled by some variable process that acts in this magnetic environment. We infer that this variable process is low-lying reconnection accompanying flux cancellation.

Falconer, D. A.↗
NASA NTRS1998

A New Synoptic Scale Feature of the Auroral Oval: The Nightside Gap

Th Polar Ultraviolet Imager (UVI) has recently identified a new morphological feature of the nightside aurora in which a well defined segment of the pre-midnight auroral oval, typically spanning 1.0- 1.5 hours in local time (710-1100 km), exhibits a significant reduction in luminosity relative to the active regions surrounding it. This feature appears in roughly 7% of the substorm period observed during our initial study spanning December 1996 through February, 1997. The energy flux (erg/sq cm/s) is shown to be lower by as much as a factor of four in this nightside gaps in comparison to the adjacent auroral activity. Substorm intensifications are often observed on either side of the nightside gap, which remains relatively inactive during these substorm periods. We demonstrate that the nightside gap is sometimes terminated by the onset of a substorm directly within the same local time boundaries. The nightside gap has strong implications for the dynamics of magnetosphere-ionosphere coupling and current closure in the midnight sector auroral oval. Specifically, we conjecture that the nightside gap occurs when transverse ionospheric currents do not feed into upward field-aligned currents in the midnight sector, perhaps due to the Harang discontinuity.

Cliua, D.↗
NASA NTRS2012

The Mojave Subsurface Bio-Geochemistry Explorer (MOSBE)

The MOSBE Team has developed a terrestrial field campaign to explore two subsurface biological habitats under the Mojave Desert. This field campaign will not only help us understand terrestrial desert biology, but also will develop methodologies and strategies for potential future Mars missions that would seek to explore the Martian subsurface. We have proposed to the ASTEP program to integrate a suite of field demonstrated instruments with a 20 m subsurface drill as a coherent unit, the Mojave Subsurface Bio-geochemistry Explorer. The ATK Space Modular Planetary Drill System (MPDS) requires no drilling fluid, which allows aseptic sampling, can penetrate lithic ground up to 20 meters of depth, and utilizes less than 100 Watts throughout the entire depth. The drill has been developed and demonstrated in field testing to a depth of 10 meters in Arizona, December 2002. In addition to caching a continuous core throughout the drilling depth, it also generates and caches cuttings and fines that are strata-graphically correlated with the core. As a core segment is brought to the surface, it will be analyzed for texture and structure by a color microscopic imager and for relevant chemistry and mineralogy with a UV fluorescence/Raman spectrometer. Organic and soluble ionic species will be identified through two instruments -- a microcapillary electrophoresis, and an ion trap mass spectrometer that have been developed under PIDDP, ASTID and MIDP funding.

robotic subsurface drilling↗
NASA NTRS2004

Novel Image Processing Interface to Relate DSB Spatial Distribution from Immunofluorescence Foci Experiments to the State-of-the-Art Models of DNA Breakage

A recently developed software (NASARadiationTrackImage) allows a quick and automatic segmentation of foci that indicate spatial localization of specific proteins that are visualized by immunofluorescence. Of interest are the spatial and temporal distribution of foci such as gammaH2AX, a signal of the phosphorylation of a variant of the histone H2A that has been shown to correspond to DSBs, or proteins involved in DSB processing, such as ATM, Rad51, and p53, following exposures of human cells to high charge and energy (HZE) ion irradiation. Experimental data are recorded as sets of two-dimensional images in color with cells and foci of gammaH2AX, ATM, Rad51 or others shown. Different cells, levels of radiation and timing after radiation were recorded. The software allows us to calculate the number of foci per cell, overall intensity of light in foci and their spatial organization. A simple statistical model allows for testing of foci overlap (eclipse). A more complex statistical model previously known as DNAbreak simulates track structure and random chromosome geometry. It has one adjustable parameter corresponding to an average intensity of DSB creation in cubic micrometers of DNA volume per particle track or unit dose. Its limitation is the low-resolution limit both in physical space and DSB's along DNA. It works adequately on the scale of a cell and provides further insights on how the geometry of tracks and DNA affects genomic damage of the cell and subsequent repair. Future developments of the model for the description of the time evolution of DNA damage response proteins, and more robust track structure models will be discussed.

Ponomarev, A. L.↗
NASA NTRS2016

3D Backscatter Imaging System

Systems and methods for imaging an object using backscattered radiation are described. The imaging system comprises both a radiation source for irradiating an object that is rotationally movable about the object, and a detector for detecting backscattered radiation from the object that can be disposed on substantially the same side of the object as the source and which can be rotationally movable about the object. The detector can be separated into multiple detector segments with each segment having a single line of sight projection through the object and so detects radiation along that line of sight. Thus, each detector segment can isolate the desired component of the backscattered radiation. By moving independently of each other about the object, the source and detector can collect multiple images of the object at different angles of rotation and generate a three dimensional reconstruction of the object. Other embodiments are described.

Turner, D. Clark↗
DOE OSTI2025

Improved Gas Plume Identification Using Nearest Neighbor Methods for Background Estimation

Longwave infrared (LWIR) hyperspectral imaging (HSI) can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Identification is used after detection to increase confidence in weakly detected plumes, reduce false positives from detection, and distinguish between similar and confounding material signatures. Background estimation is an important step used to reveal the unique spectral characteristics of the detected gas, allowing the identification model to determine what the gas is specifically. The importance of proper background estimation increases when dealing with weak signals, large libraries of gases of interest, and uncommon or heterogeneous backgrounds. In this article, we propose two methods for background estimation: a novel k-nearest segments (KNS) algorithm and the standard k-nearest neighbors (KNN) algorithm. We test our methods and three existing background estimation methods for comparison against global background estimation to determine which performs best at estimating the true background radiance under a plume and for increasing identification confidence using a neural network classification model. We compare the different methods using 640 simulated weak plumes in an urban environment. For identification, our KNS algorithm improves median neural network identification confidence by 53.2%. For background radiance estimation, the KNN algorithm provides a median of 49 times less RMSE than global background estimation. Furthermore, KNN is the easiest method to tune for different plumes, making it an excellent “out of the box” background estimator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗
NASA NTRS1993

A robust line extraction and matching algorithm

This paper presents an algorithm for extracting straight lines from intensity mages and describes a line matching algorithm for solving the line correspondence problem. The line extraction process begins by detecting edges in the intensity image. Next, line support regions are formed where image points (pixels) have similar gradient orientation. A line fitting algorithm is then used to fit a line to the points in the line support region based on a least means square fitting algorithm. Finally, line segments are linked together to form the final lines by using an adaptive line linking method; this results in much stronger lines and a smaller set of lines to be considered. Once the lines are detected in a sequence of images, a line matching algorithm is used to match lines in one image to the lines in the other image. The images are either from a motion or stereo sequence. The matched lines may then be used with the sensor position and orientation data to estimate range to objects corresponding to the lines. We present results based on applying the line extraction and line matching algorithms to a synthetic image and an outdoor scene captured by a camera on a helicopter.

Hussien, B.↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Nighttime observations of thunderstorm electrical activity from a high altitude airplane

Photographs from a NASA U-2 airplane flying over nocturnal thunderstorms show frequent lightning activity in the upper part of the cloud. In some cases, unobscured segments of lightning channels 1 km or longer are visible in clear air around and above the cloud. Multiple images of lightning channels indicate multiple discharges in the same channel. Photographs taken through a diffraction grating show that the lightning has a spectrum similar to that observed in the lower troposphere. Lightning spectra obtained with a slitless line-scan spectrometer show strong singly ionized nitrogen emissions at 463.0 and 500.5 nm. Field changes measured with an electric field-change meter correlate with pulses measured with a photocell optical system. Optical signals corresponding to dart leader, return stroke, and continuing current events are readily distinguished in the scattered light emerging from the cloud surface. The variation of light intensity with time in lightning events is consistent with predicted modification of optical lightning signals by clouds. It appears that satellite based optical sensor measurements cannot provide reliable information on current rise times in return strokes. On the other hand, discrimination between cloud-to-ground and intracloud flashes and the counting of ground strokes is possible using the optical pulse pairs which have been identified with leader, return-stroke events in the cloud-to-ground flashes studied.

Brook, M.↗
NASA NTRS1990

Advanced technology optical telescopes IV; Proceedings of the Meeting, Tucson, AZ, Feb. 12-16, 1990. Parts 1 & 2

The present conference on the current status of large, advanced-technology optical telescope development and construction projects discusses topics on such factors as their novel optical system designs, the use of phased arrays, seeing and site performance factors, mirror fabrication and testing, pointing and tracking techniques, mirror thermal control, structural design strategies, mirror supports and coatings, and the control of segmented mirrors. Attention is given to the proposed implementation of the VLT Interferometer, the first diffraction-limited astronomical images with adaptive optics, a fiber-optic telescope using a large cross-section image-transmitting bundle, the design of wide-field arrays, Hartmann test data reductions, liquid mirrors, inertial drives for telescope pointing, temperature control of large honeycomb mirrors, evaporative coatings for very large telescope mirrors, and the W. M. Keck telescope's primary mirror active control system software.

Barr, Lawrence D.↗
NASA NTRS1987

High-resolution CCD imagers using area-array CCD's for sensing spectral components of an optical line image

CCD imagers with a novel replicated-line-imager architecture are abutted to form an extended line sensor. The sensor is preceded by optics having a slit aperture and having an optical beam splitter or astigmatic lens for projecting multiple line images through an optical color-discriminating stripe filter to the CCD imagers. A very high resolution camera suitable for use in a satellite, for example, is thus provided. The replicated-line architecture of the imager comprises an area-array CCD, successive rows of which are illuminated by replications of the same line segment, as transmitted by respective color filter stripes. The charge packets formed by accumulation of photoresponsive charge in the area-array CCD are read out row by row. Each successive row of charge packets is then converted from parallel to serial format in a CCD line register and its amplitude sensed to generate a line of output signal.

Elabd, Hammam↗
NASA NTRS2021

Concept of Operations for OSIRIS-REx Optical Navigation Image Planning

Optical navigation (OpNav) is a critical subsystem of the OSIRIS-REx asteroid sample return mission, which operated in the vicinity of near-Earth asteroid (101955) Bennu from August 2018 through April 2021. A substantial amount of mission resources across multiple subsystems and institutions is required to ensure that the OpNav data are successfully acquired. The KinetX OpNav team, part of the Flight Dynamics System (FDS), is responsible for performing required analysis to develop the OpNav operations plans; requesting, reviewing and verifying the plans; and ultimately using the image data for critical navigation operations. The FDS team, responsible for the mission navigation, is operated by KinetX Aerospace with management and operations support from NASA’s Goddard Space Flight Center. The Science Processing and Operations Center (SPOC), located at the University of Arizona’s Lunar and Planetary Laboratory, is responsible for generating the planning products for all science and most OpNav data. These plans are integrated into the spacecraft sequences, tested, and commanded by the Mission Support Area (MSA) at Lockheed Martin Space. To ensure mission-critical navigation image data are successfully acquired, the plan is developed through a waterfall of planning cycles over the course of 3 months prior to onboard plan execution. During the initial strategic planning for a mission phase, detailed analysis is performed by the OpNav team to conceptualize the concept of operations (ConOps) for image data collection. This phase OpNav Narrative is included along with other strategic planning documents for the key ground segment stakeholders to review and provide feedback. The detailed OpNav plans get defined in the tactical planning cycle, which spans 8 to 3 weeks before the week-long integrated sequence is executed on-board the spacecraft. During the tactical cycle, the initial OpNav Request is submitted along with the science requests, kicking off development of the science and OpNav plans. Once the initial plan is drafted, interfaces are exercised so that the plan can be reviewed and iterated, if necessary. A rigorous schedule is followed by the planning teams during the implementation cycle, spanning the last 18 days before uplink, to ensure all the necessary integration, testing, and reviewing can occur on time. The development of the OpNav planning ConOps, including responsibilities, interfaces, timelines, and procedures, took extensive collaboration across mission elements and institutions. The process was robust throughout the 137 weeks of continuous Optical Navigation Operations at Bennu, which concluded on April 9th, 2021.

Coralie D. Adam↗
NASA NTRSDate not supplied

Introduction to Image-Based Wavefront Sensing

The James Webb Space Telescope (JWST) is easily one of the most advanced devices ever created by humans, bridging a gap between the macroscopic and quantum worlds in terms of how accurately we can align mirrors. It is the product of exhaustive testing, countless innovations, and the international collaboration between 1000’s of people working tirelessly for more than 20 years. In this talk we discuss the physics of image-based wavefront sensing: one of the core technologies that was utilized to complete the final alignment of the segmented mirror.

Wavefront Sensing↗
NASA NTRS2010

Wavefront Controls for a Large Submillimeter-Wave Observatory

The 25-m aperture Cornell Caltech Atacama Telescope (CCAT) will have a primary mirror that is divided into 162 individual segments, each of which is equipped with 3 positioning actuators. This paper presents a mathematical description of the telescope, its actuators and sensors, and uses it to derive control laws for figure maintenance. A Kalman Filter-based Optical State Estimator is used to continuously estimate the aberrations of the telescope; these are used in a state-feedback controller to maintain image quality. This approach provides the means to correct for the optical effects of errors that occur in unactuated degrees of freedom, such as lateral translations of the segments. The control laws are exercised in Monte Carlo and covariance analysis, to bound the closed-loop performance of the telescope and to conduct control design trades.

edge sensors↗