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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 469 records · Page 26

All sources NASA NTRS DOE OSTI

DOE OSTI2020

High-speed volumetric imaging of formaldehyde in a lifted turbulent jet flame using an acousto-optic deflector

The development of high-speed volumetric laser-induced fluorescence measurements of formaldehyde (CH 2 O-LIF) using a pulse-burst laser operated at a repetition rate of 100 kHz is presented here. A novel laser scanning system employing an acousto-optic deflector (AOD) enables quasi-4D CH 2 O-LIF imaging at a scan frequency of 10 kHz. The diagnostic capability of time-resolved volumetric imaging is demonstrated in a partially premixed DME/air lifted turbulent jet flame near the flame base. Simultaneous imaging of laser beam profiles is performed to account for the laser pulse energy fluctuation and laser sheet inhomogeneity. With the accurate registration of laser sheet positions, the volumetric reconstruction of CH 2 O-LIF signals is performed within a detection volume of 17.3 × 11.9 × 2.3 mm 3 with an average out-of-plane spatial resolution of 250μm. A surface detection algorithm with adaptive thresholding is used to determine the global maximum intensity gradient by calculating gradient percentiles. The flame topology characteristics are investigated by evaluating the 3D curvatures of CH 2 O surfaces. Curvatures calculated using 2D data systematically underestimate the full 3D curvature due to the lack of out-of-plane information. The inner surfaces near the turbulent fuel jet exhibit higher probabilities of large mean curvature than the outer surfaces. The saddle and cylindrical structures are dominant on both the inner and outer surfaces and the elliptic structures occur with lower probability. The results suggest that the damping of turbulent fluctuations by the temperature increase through the CH 2 O region reduces the curvature, but the local structure topology remains self-similar.

42 ENGINEERING↗

DOE OSTI2025

A co-registered in-situ and ex-situ dataset from wire arc additive manufacturing process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data-centric approach emphasizes leveraging sensor data available throughout the production process to optimize performance. Integration of extensive data analysis provides opportunities for improving precision, reducing waste, and enhancing the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes a comprehensive description of the deposition process, process parameters, welding characteristics and acoustic data collected in-situ, and X-Ray Computed Tomography data of the build.

42 ENGINEERING↗

DOE OSTI2024

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING↗

NASA NTRS1988

Concepts for processing and analyzing of multiple SAR and Landsat images

The use and application of multisensor data sets are an absolute necessity for remote sensing to fulfill its promise. Initial efforts at registering dissimilar images have been made, but results are not widely available. This paper describes some initial work to better understand the difficulties of multisensor registration. Accuracies achieved are in excess of a pixel diameter.

Thomas, J.↗

NASA NTRS1982

Proceedings of the NASA Workshop on Registration and Rectification

Issues associated with the registration and rectification of remotely sensed data. Near and long range applications research tasks and some medium range technology augmentation research areas are recommended. Image sharpness, feature extraction, inter-image mapping, error analysis, and verification methods are addressed.

Bryant, N. A.↗

NASA NTRS1981

Technologies for the multispectral mapping of earth resources

The application of solid-state detector array imaging to the remote sensing of the earth as a follow-on to currently planned Landsat missions provides the opportunity to achieve significantly increased performance. First-order advantages to be anticipated are higher sensitivity resulting in greater radiometric accuracies and improved geometric fidelity. The Multispectral Mapper design concept is responsive to a broad range of user needs by incorporating in-flight selection of spectral bands, instantaneous fields of view, and swath width. This versatility is achieved by the use of an imaging spectrometer which permits both spatial and spectral sampling in the image plane using area array detectors. Other improvements over the current Landsat multispectral scanner and Thematic Mapper include higher spatial resolution and inherently precise registration of the spectral bands. The key technologies required in order to realize these improvements include short-wavelength infrared detectors, wide field of view, broad spectral coverage optics, focal plane cooling, and high-speed onboard signal processing. Significant development activities will be required if an advanced remote sensing capability is to be implemented.

Wellman, J. B.↗

NASA NTRS1992

Spectrum-Imaging Detector Array With Integrated Filter

Proposed rectangular array of photodetectors in imaging spectrometer includes integral filter deposited directly on imaging array which would not become misaligned or misregistered as result of mechanical shock, vibration, or differential thermal expansion. Need for precise alignment and registration of filter cannot be over-emphasized.

Labaw, Clayton C.↗

NASA NTRS2020

Satellite-To-Satellite Imaging in Support of LEO Optical Navigation, Using the ASTERIA Cubesat

The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was a 6-unit CubeSat technology demonstration mission that was built at NASA’s Jet Propulsion Laboratory (JPL) and deployed from the International Space Station (ISS) on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations alongside science until end of mission in December 2019. At the end of its lifetime it was being used as a demonstration platform for several experiments, including low earth orbit (LEO) optical navigation operations. With its visible light astrometric camera and stable attitude control system, the ASTERIA spacecraft showed itself to be a capable platform for the imaging of geosynchronous satellites from LEO. This paper will describe the imagery attained in flight and also the image processing algorithms that were developed to render that imagery into navigation quality data. These algorithms dealt with hot pixel filtering, noise modeling, attitude registration, star signal rejection and satellite signal identification. Brightness prediction algorithms used for target selection will also be discussed.

Fesq, Lorraine↗

NASA NTRS2009

Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images

A document describes cryogenic test architecture for the James Webb Space Telescope (JWST) integrated science instrument module (ISIM). The ISIM element primarily consists of a mechanical metering structure, three science instruments, and a fine guidance sensor. One of the critical optomechanical alignments is the co-registration of the optical telescope element (OTE) exit pupil with the entrance pupils of the ISIM instruments. The test architecture has been developed to verify that the ISIM element will be properly aligned with the nominal OTE exit pupil when the two elements come together. The architecture measures three of the most critical pupil degrees-of-freedom during optical testing of the ISIM element. The pupil measurement scheme makes use of specularly reflective pupil alignment references located inside the JWST instruments, ground support equipment that contains a pupil imaging module, an OTE simulator, and pupil viewing channels in two of the JWST flight instruments. Pupil alignment references (PARs) are introduced into the instrument, and their reflections are checked using the instrument's mirrors. After the pupil imaging module (PIM) captures a reflected PAR image, the image will be analyzed to determine the relative alignment offset. The instrument pupil alignment preferences are specularly reflective mirrors with non-reflective fiducials, which makes the test architecture feasible. The instrument channels have fairly large fields of view, allowing PAR tip/tilt tolerances on the order of 0.5deg.

Bos, Brent↗

NASA NTRS1979

Integration of Landsat, Seasat, and other geo-data sources

The paper discusses integration of Landsat, Seasat, and other geographic information sources. Mosaicking of radar data and registration of radar to Landsat digital imagery are described, and six types of geophysical data, including gravity and magnetic measurements, are integrated and analyzed using image processing techniques.

Zobrist, A. L.↗

NASA NTRS1984

Geometric Accuracy Assessment of LANDSAT-4 Multispectral Scanner (MSS)

Standard LANDSAT-4 MSS digital image data were analyzed for geometric accuracy using two P-format (UTM projection) images of the Washington, D.C. area, scene day 109 (ID number 4010915140) and scene day 125 (ID number 4012515144). Both scenes were tested for geodetic registration accuracy (scene-to-map), temporal registration accuracy (scene-to-scene), and band-to-band registration accuracy (within a scene). The combined RMS error for geodetic registration accuracy was 0.43 pixel (25.51 meters), well within specifications. The comparison between the 2 scenes was made on a band-by-band basis. The 90 percent error figure for temporal registration was 0.68 (57x57) pixel (38.8 meters). Although this figure is larger than the specification, it can be considered excellent with respect to user application. The best case registration errors between bands 1 and 2, and 3 and 4 were 14.2m and 13.7m, respectively, both within specifications. The worst case registration error was 38.0 m between bands 2 and 3.

Imhoff, M. L.↗

NASA NTRS2001

Measurement of Separated Flow Structures Using a Multiple-Camera DPIV System

A novel multiple-camera system for the recording of digital particle image velocimetry (DPIV) images acquired in a two-dimensional separating/reattaching flow is described. The measurements were performed in the NASA Langley Subsonic Basic Research Tunnel as part of an overall series of experiments involving the simultaneous acquisition of dynamic surface pressures and off-body velocities. The DPIV system utilized two frequency-doubled Nd:YAG lasers to generate two coplanar, orthogonally polarized light sheets directed upstream along the horizontal centerline of the test model. A recording system containing two pairs of matched high resolution, 8-bit cameras was used to separate and capture images of illuminated tracer particles embedded in the flow field. Background image subtraction was used to reduce undesirable flare light emanating from the surface of the model, and custom pixel alignment algorithms were employed to provide accurate registration among the various cameras. Spatial cross correlation analysis with median filter validation was used to determine the instantaneous velocity structure in the separating/reattaching flow region illuminated by the laser light sheets. In operation the DPIV system exhibited a good ability to resolve large-scale separated flow structures with acceptable accuracy over the extended field of view of the cameras. The recording system design provided enhanced performance versus traditional DPIV systems by allowing a variety of standard and non-standard cameras to be easily incorporated into the system.

Humphreys, William M., Jr.↗

NASA NTRS2000

A simulator for evaluating methods for the detection of lesion-deficit associations

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

NASA Program Biomedical Research and Countermeasur↗

NASA NTRS1982

Working group organizational meeting

Scene radiation and atmospheric effects, mathematical pattern recognition and image analysis, information evaluation and utilization, and electromagnetic measurements and signal handling are considered. Research issues in sensors and signals, including radar (SAR) reflectometry, SAR processing speed, registration, including overlay of SAR and optical imagery, entire system radiance calibration, and lack of requirements for both sensors and systems, etc. were discussed.

Source record↗

NASA NTRS1988

System Turns SAR Images Into Maps

Postprocessing system for synthetic-aperture radar (SAR) transforms raw images from natural rotated and distorted SAR reference frame into geocoded images. Images automatically corrected to remove slant-range nonlinearities and Doppler skew. Produces multiple-frame mosaics for large-scale mapping. Does not require tedious manual registration of representative "tie" points in raw SAR imagery with known locations on Earth.

Curlander, J. C.↗

NASA NTRS1983

Analysis of Subpixel Registration Accuracy

Geometric and probabilistic models for subpixel accuracy are developed. The geometric models bound the error in offset estimation using the pixels in an observed digital straight line. One probabilistic model bounds the estimate of error offset for continuous images. The other model bounds the error for discrete images given that one is in the correct pixel.

Lavine, D.↗

DOE OSTI2019

Binocular high dynamic range imaging system based on digital micromirror device

In the applications of scientific imaging and space exploration, the dynamic range of imaging systems is usually required to reach more than 120 dB. In order to observe a highly dynamic scene in real time, we designed an imaging system based on a digital micromirror device (DMD) that is used as a spatial light modulator. First, we designed a binocular highly dynamic light-adjusting system based on a DMD according to the DMD’s optical structure. Second, in order to realize the registration between the micromirrors of a DMD and pixels of the two cameras, a pixel-matching algorithm was developed. Finally, we introduce a novel light-adjusting algorithm that can recover the highly dynamic data of the dynamic scene. Experiments showed that the deviation between the DMD and the two cameras is reduced to 0.48 pixels after correction, and that bright and dark targets in a high-dynamic-range scene can both be displayed simultaneously in one image with high quality after light adjustment. The dynamic range of the system is theoretically 209 dB, which meets the requirements of high-dynamic-range observation.

42 ENGINEERING↗

NASA NTRS1983

Experimental philosophy leading to a small scale digital data base of the conterminous United States for designing experiments with remotely sensed data

Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.

Labovitz, M. L.↗