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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 NTRS2019

LANDSAT 9: Mission Status and Prelaunch Instrument Performance Characterization and Calibration

Landsat 9 is currently under development as a joint effort between NASA and the United States Geological Survey (USGS). Landsat 9 is largely a rebuild of Landsat 8 and has the same two sensors, an Operational Land Imager (OLI) and a Thermal InfraRed Sensor(TIRS). The OLI-2 on Landsat 9, being built by Ball Aerospace, has completed its pre-launch characterization and calibration and is scheduled to be delivered in the summer of 2019. The TIRS-2, with improved stray light performance and increased redundancy for improved reliability, is being built by Goddard Space Flight Center. TIRS-2is undergoing testing through Spring 2019 and is also scheduled for summer2019 delivery. Several improvements to the characterization of both instruments have been incorporated into the testing plan, including improved spectral and radiometric characterization. The instruments will then be integrated onto the spacecraft being built by Northrop Grumman Innovation Systems (NGIS). The mission is targeted to launch as early as December 2020 on an Atlas V.

Landsat↗
NASA NTRS2021

Cincinnati & Covington Urban Development II: Assessing Flooding and Landslide Susceptibility Along the Ohio-Kentucky Border

Landslides and flooding are reoccurring environmental hazards that lead to health risks and economic burdens in the urban areas of Cincinnati, Ohio and Covington, Kentucky. These communities share underlying natural and artificial conditions that make them vulnerable to these hazards, including excessive precipitation, weak lithology, high impervious surface levels, and steep slopes. Despite the human and economic risks associated with these environmental hazards, the areas of highest vulnerability within the region remain unknown. NASA DEVELOP partnered with Groundwork USA and Groundwork Ohio River Valley (ORV) to assess the region’s susceptibility to landslides and flooding. The team utilized NASA Earth observations, including the Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrieval for GPM (IMERG), alongside ancillary datasets to map landslide susceptibility and exposure throughout the study area. The team also used ancillary data to map surface runoff and runoff retention using the Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model. The resulting landslide susceptibility and exposure maps highlight the neighborhoods around Avondale and Fairmount as areas of particularly high landslide exposure. Meanwhile, the InVEST outputs demonstrate that Downtown Cincinnati and the Queensgate neighborhood retain the least amount of rainfall. This research provides partners with a more complete hazard analysis of the greater Cincinnati area while also producing refined methodologies to enhance future flood and landslide vulnerability mapping throughout Groundwork USA’s nationwide network of communities.

Paxton LaJoie↗
NASA NTRS2021

The Io GIS Database 1.0: A Proto-Io Planetary Spatial Data Infrastructure

We collected a set of published, higher-order data products of Jupiterʼs volcanic moon Io and assembled them in an ArcGISTM database we are calling the Io GIS Database, version 1.0. The purpose of this database is to collect image, topographic, geologic, and thermal emission data of Io in one geospatially registered location to form the data component of an Io planetary spatial data infrastructure (PSDI). The goals of an Io PSDI are (1) to make higher-order data products more accessible and usable to the broader planetary science community, particularly to new scientists that were not associated with the projects that obtained the data; (2) to enable new scientific studies with the data; and (3) to create a tool to support observation planning for future Io-focused planetary missions. In this paper we describe the motivation behind our project, discuss the data sets acquired for this first version of the database, and demonstrate how they can be used. We conclude with a discussion of how our database relates to other PSDIs, our plans for future updates, and a request for additional Io data sets.

David A Williams↗
NASA NTRSDate not supplied

Towards Qualification and Certification of Laser Powder Bed Fusion Ti-6Al-4V with In-Situ Process Monitoring and Automated Defect Detection

Qualification and certification of laser powder bed fusion (LPBF) parts are two challenges that must be answered to ensure suitability for critical applications. In-situ monitoring using high frame rate thermal and conventional optical imaging sensors is applied to the LPBF build process. Currently, the large volume of data from such sensors becomes untenable for manual inspection in production environments. This presentation serves to address this in-situ monitoring deficiency in two ways. First, a framework for managing data streams from LPBF process monitoring sensors is described. Second, two candidate image analysis techniques are presented: one is a set of heuristics that are easily interpretable, and the other is an uninterpretable convolutional neural network. These strategies are compared in terms of performance, computational expense, and speed. These methodologies represent platforms for connecting processing conditions to process modeling efforts aligned with the qualification and certification mission for LPBF Ti-6Al-4V components.

Qualification↗
NASA NTRS2011

Image Quality Indicator for Infrared Inspections

The quality of images generated during an infrared thermal inspection depends on many system variables, settings, and parameters to include the focal length setting of the IR camera lens. If any relevant parameter is incorrect or sub-optimal, the resulting IR images will usually exhibit inherent unsharpness and lack of resolution. Traditional reference standards and image quality indicators (IQIs) are made of representative hardware samples and contain representative flaws of concern. These standards are used to verify that representative flaws can be detected with the current IR system settings. However, these traditional standards do not enable the operator to quantify the quality limitations of the resulting images, i.e. determine the inherent maximum image sensitivity and image resolution. As a result, the operator does not have the ability to optimize the IR inspection system prior to data acquisition. The innovative IQI described here eliminates this limitation and enables the operator to objectively quantify and optimize the relevant variables of the IR inspection system, resulting in enhanced image quality with consistency and repeatability in the inspection application. The IR IQI consists of various copper foil features of known sizes that are printed on a dielectric non-conductive board. The significant difference in thermal conductivity between the two materials ensures that each appears with a distinct grayscale or brightness in the resulting IR image. Therefore, the IR image of the IQI exhibits high contrast between the copper features and the underlying dielectric board, which is required to detect the edges of the various copper features. The copper features consist of individual elements of various shapes and sizes, or of element-pairs of known shapes and sizes and with known spacing between the elements creating the pair. For example, filled copper circles with various diameters can be used as individual elements to quantify the image sensitivity limit. Copper line-pairs of various sizes where the line width is equivalent to the spacing between the lines can be used as element-pairs to quantify the image resolution limit.

Burke, Eric↗
NASA NTRS1991

Geologic mapping in Death Valley, California/Nevada using NASA/JPL airborne systems (AVIRIS, TIMS, and AIRSAR)

A multi-sensor aircraft campaign called the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 resulted in acquisition of high quality multispectral images in the visible, near infrared, shortwave infrared, thermal infrared, and microwave regions of the electromagnetic spectrum. The airborne data sets include the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Thermal Infrared Multispectral Scanner (TIMS), and the Airborne Synthetic Aperture Radar (SAR). Ancillary data include Landsat Thematic Mapper, laboratory and field spectral measurements, and traditional geologic mapping. The GRSFE data for a site in the northern Death Valley, (California and Nevada) region were calibrated to physical units and geometrically registered to a map base. Various aspects of this experiment are briefly discussed.

Kruse, Fred A.↗
DOE OSTI2023

Multispectral and thermal surface imagery and surface elevation mosaics (camspec-air)

This dataset contains high resolution image products (orthomosaics) acquired from midsized uncrewed aerial systems, which have been processed for value added quality. The instrument itself, a multispectral imager, the Altum by Micasense, captures 6 spectral bands (red, green blue, NIR, red edge, and LWIR/thermal1) as radiance, which is converted to reflectance. The code used to develop these images first uses tools from the Micasense python library2 to apply dark level corrections, row gradient corrections, and radiometric corrections. Next it uses the processing API from Agisoft Metashape software to align and mosaic the processed imagery, following the processes developed by the USGS' structure from motion workflow documentation3. Captures at different altitudes (recorded in MSL) produce an orthomosaic, a tif image containing information related to the 6 spectral bands, and a digital elevation model (DEM), a tif image containing information related to the elevation of the surveyed terraine. Metadata included in every image can be used to extract lat, lon, and reflectance values. 1https://www.arm.gov/publications/tech_reports/handbooks/doe-sc-arm-tr-281.pdf 2https://micasense.github.io/imageprocessing/MicaSense%20Image%20Processing%20Setup.html 3https://pubs.usgs.gov/of/2021/1039/ofr20211039.pdf

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications

The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1981

Wedge-and-strip anodes for centroid-finding position-sensitive photon and particle detectors

The paper examines geometries employing position-dependent charge partitioning to obtain a two-dimensional position signal from each detected photon or particle. Requiring three or four anode electrodes and signal paths, images have little distortion and resolution is not limited by thermal noise. An analysis of the geometrical image nonlinearity between event centroid location and the charge partition ratios is presented. In addition, fabrication and testing of two wedge-and-strip anode systems are discussed. Images obtained with EUV radiation and microchannel plates verify the predicted performance, with further resolution improvements achieved by adopting low noise signal circuitry. Also discussed are the designs of practical X-ray, EUV, and charged particle image systems.

Martin, C.↗
NASA NTRS1993

The difference between laboratory and in-situ pixel-averaged emissivity: The effects on temperature-emissivity separation

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a Japanese future imaging sensor which has five channels in thermal infrared (TIR) region. To extract spectral emissivity information from ASTER and/or TIMS data, various temperature-emissivity (T-E) separation methods have been developed to date. Most of them require assumptions on surface emissivity, in which emissivity measured in a laboratory is often used instead of in-situ pixel-averaged emissivity. But if these two emissivities are different, accuracies of separated emissivity and surface temperature are reduced. In this study, the difference between laboratory and in-situ pixel-averaged emissivity and its effect on T-E separation are discussed. TIMS data of an area containing both rocks and vegetation were also processed to retrieve emissivity spectra using two T-E separation methods.

Matsunaga, Tsuneo↗
NASA NTRS1972

Rock-type discrimination from ratioed infrared scanner images of Pisgah Crater, California.

The radiances in two thermal infrared channels of an airborne scanner system were ratioed to produce images that recorded compositionally diagnostic emittance variations for several silicate rock types near Pisgah Crater, California. The images demonstrate that the ratio method is capable of enhancing emittance variations in the presence of temperature extremes that differ by no more than 25 C, with no temperature corrections.

Vincent, R. K.↗
NASA NTRS1972

Optical design of an imaging spectral radiometer for earth resources applications.

Description of the optics, thermal compensation measures, and calibration procedures for a scanning imaging spectroradiometer to be used in earth resources sensing applications. The spectral range covered extends from 4000 to 8500 A. Two possible modes of operation include (1) a high-spatial-resolution terrestrial survey mode with moderate spectral resolution, and (2) a high-spectral-resolution ocean survey mode with decreased spatial resolution. Two high-aperture f/1.4 objective lenses (providing fields of view of 10 and 25 deg) are interchangeable to give added flexibility in planning experiments with this instrument. A diffraction grating disperses the spectrum which is then scanned by the image sensor.

Harris, T. I.↗
NASA NTRS2016

Development and Implementation of a Generic Analysis Template for Structural-Thermal-Optical-Performance Modeling

Performance-related effects of system level temperature changes can be a key consideration in the design of many types of optical instruments. This is especially true for space-based imagers, which may require complex thermal control systems to maintain alignment of the optical components. Structural-Thermal-Optical-Performance (STOP) analysis is a multi-disciplinary process that can be used to assess the performance of these optical systems when subjected to the expected design environment. This type of analysis can be very time consuming, which makes it difficult to use as a trade study tool early in the project life cycle. In many cases, only one or two iterations can be performed over the course of a project. This limits the design space to best practices since it may be too difficult, or take too long, to test new concepts analytically. In order to overcome this challenge, automation, and a standard procedure for performing these studies is essential. A methodology was developed within the framework of the Comet software tool that captures the basic inputs, outputs, and processes used in most STOP analyses. This resulted in a generic, reusable analysis template that can be used for design trades for a variety of optical systems. The template captures much of the upfront setup such as meshing, boundary conditions, data transfer, naming conventions, and post-processing, and therefore saves time for each subsequent project. A description of the methodology and the analysis template is presented, and results are described for a simple telescope optical system.

Scola, Salvatore↗
NASA NTRS2022

Quantifying Mangrove Canopy Regrowth and Recovery After Hurricane Irma With Large-Scale Repeat Airborne Lidar in the Florida Everglades

Hurricane Irma caused significant damages to mangrove forested wetlands in south Florida, including defoliation, tree snapping, and uprooting. Previous studies have used optical satellite imagery to estimate large-scale forest disturbance and resilience patterns. However, satellite images alone cannot provide measurements of vertical mangrove structure. In this study, we used dense point cloud data collected by NASA Goddard’s LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager before (March 2017) and after (December 2017 and March 2020) Hurricane Irma to quantify the recovery, or lack thereof, of the three-dimensional (3D) mangrove forest structure. Recent resilience and vulnerability models developed from Landsat time series following the storm were used to group the lidar data into distinct disturbance-recovery classes. We then analyzed lidar-based forest canopy within each of the recovery classes to test a suite of forest structural characteristics. Our results indicate that 77.0 % of the survey area experienced canopy height loss three months after Hurricane Irma, whereby the majority of canopy height loss occurred in areas with the tallest mangrove forests (i.e., 15–25 m tall). Our analysis shows that the mangrove canopy height in South Florida increased by an average 0.26 m from December 2017 to March 2020, with most of the forest (84.7 % of the survey area) experiencing canopy height regrowth. However, only 38.1 % of the survey area has recovered to pre-storm canopy height. The distribution of canopy height was significantly altered by Hurricane Irma in the low and intermediate resilience classes, but were not significantly different 2.5 years later. Indeed, in areas of low resilience, little to no vertical change has occurred suggesting the absence of canopy regrowth and natural regeneration. Conversely, mangroves in high resilience class, which are dominated by shorter canopies (<5 m), were not heavily damaged by the storm and have maintained the same structural attributes as those before Hurricane Irma. Our findings highlight that hurricane disturbances significantly alter mangrove forest canopy structure, but recovery of vertical structure varies by resilience classes, species composition, and canopy height.

Lidar↗
DOE OSTI2026

Visualization of Thermal and Strain Dynamics in X-ray Optics by Time-Resolved Rocking Curve Imaging

The absorption of intense X-ray pulses from free-electron lasers by X-ray crystal optics triggers rapid thermal and mechanical responses, including lattice compression, expan- sion, and strain-wave propagation, which dynamically modify diffraction conditions and wavefront properties. These effects pose significant challenges for next-generation high- repetition-rate X-ray sources, particularly for crystal monochromators used in XFEL beam- lines and self-seeding. Here, we demonstrate time-resolved rocking curve imaging (TrRCI) of X-ray Bragg optics with high spatial resolution (6.4 μm) and sub-1-μrad angular resolu- tion, enabling direct visualization of lattice dynamics from nanoseconds to microseconds. By combining a high-flux beamline at SPring-8, a scintillator-coupled sCMOS detector, and a synchronized femtosecond laser system, we capture lattice dynamics induced by tran- sient laser heating with a strain sensitivity on the order of 10−6 . Our results reveal transient lattice deformation and the propagation of laser-induced strain waves over millimeter-scale distances. This approach provides experimental benchmarks for understanding heat-load effects in high-repetition-rate X-ray optics.

Source record↗
NASA NTRS2010

Back-illuminated imager and method for making electrical and optical connections to same

Methods for bringing or exposing metal pads or traces to the backside of a backside-illuminated imager allow the pads or traces to reside on the illumination side for electrical connection. These methods provide a solution to a key packaging problem for backside thinned imagers. The methods also provide alignment marks for integrating color filters and microlenses to the imager pixels residing on the frontside of the wafer, enabling high performance multispectral and high sensitivity imagers, including those with extremely small pixel pitch. In addition, the methods incorporate a passivation layer for protection of devices against external contamination, and allow interface trap density reduction via thermal annealing. Backside-illuminated imagers with illumination side electrical connections are also disclosed.

Pain, Bedabrata↗
NASA NTRS1987

Color enhancement of highly correlated images. II - Channel ratio and 'chromaticity' transformation techniques

Two techniques for enhancing the color of multispectral images are described; both involve ratioing of data from different image channels. In the first technique, the ratioed data are assigned the primary color for display as color ratio pictures, and in the second method, image data are transformed to RGB chromaticity coordinates by ratioing the data acquired in three channels to the sum of their intensities. The two techniques are applied to a NASA Thermal-IR Multispectral Scanner (TIMS) image of Death Valley and to a Landsat MSS image of the Mojave Desert. The basic principles of ratioing are discussed, and the effects of atmospheric path radiances on the interpretation of ratioed images are investigated. It is observed that the color pictures produced using these two enhancement techniques are similar to the pictures enhanced by decorrelation and hue-saturation-intensity methods.

Gillespie, Alan R.↗