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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

Matthies, Larry↗
NASA NTRSDate not supplied

Developing a Cloud-Based ArcGIS Image Service for TROPOMI Level 2 Data: Preprocessing, Transformation, and Publication

TROPOMI, the Tropospheric Monitoring Instrument aboard the Sentinel-5 Precursor satellite, provides high spatiotemporal resolution atmospheric measurements. It is essential for monitoring air quality, greenhouse gases, and other trace gases. Integrating TROPOMI Level 2 data into an ArcGIS Image Service marks a significant advancement in the accessibility and utility of satellite-derived environmental information for GIS applications. This paper details the methodology for building an ArcGIS Image Service tailored to handle TROPOMI Level 2 data, with a focus on preprocessing, transformation, and cloud-based publication. The workflow utilizes Python and ArcPy for data reformatting, reprojection, and updating, ensuring efficient processing and cloud-based notifications. By establishing a robust pipeline, the ArcGIS Image Service provides real-time access to TROPOMI Level 2 data, enabling users to visualize, analyze, and interpret atmospheric phenomena effectively.

Level 2 Data, ArcGIS, Image Service, ArcPy, OGC↗
DOE OSTI2022

Quasi‐2D Perovskite Crystalline Layers for Printable Direct Conversion X‐Ray Imaging

Abstract Polycrystalline perovskite film‐based X‐ray detector is an appealing technology for assembling large scale imager by printing methods. However, thick crystalline layer without trap and solvent residual is challenging to fabricate. Here, the authors report a solution method to produce high quality quasi‐2D perovskite crystalline layers and detectors that are suitable for X‐ray imaging. By introducing n ‐butylamine iodide into methylammonium lead iodide precursor and coating at elevated temperatures, compact and crystalline layers with exceptional uniformity are obtained on both rigid and flexible substrates. Photodiodes built with the quasi‐2D layers exhibit a low dark current and stable operation under constant electrical field over 96 h in dark, and over 15 h under X‐ray irradiation. The detector responds sensitively under X‐ray, delivering a high sensitivity of 1214 µC Gy air −1 cm −2 and a sensitivity gain is observed when operated under higher fields. Finally, high resolution images are demonstrated using a single pixel device that can resolve 80–200 µm features. This work paves the path for printable direct conversion X‐ray imager development.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Unsteady Pressure-Sensitive-Paint Shot Noise Reduction

In the study of unsteady Pressure-Sensitive Paint (uPSP) image data sets, pixel intensity values collected by Phantom cameras from multiple perspectives are used to calculate the surface pressure of an experimental model. This paper focuses on mitigation of shot noise which is introduced into the image data set by the cameras. Shot noise impacts the quality of data collected, increasing the system error in its pressure value calculations. This paper characterises statistical methods to reduce shot noise within experimental data by taking an average or weighted average across an area of pixels of their respective counts. Each combined-pixel has a higher total effective intensity value and therefore exhibits reduced noise throughout its time history. This is demonstrated by calculating the standard deviations of the combined pixel values through time, which decrease as the combined pixel area increases. Finally, these methods are compared across experimental wind tunnel conditions to examine their effectiveness at different Mach numbers. Ultimately, the results are used to recommend a blur filter type and size which will be applied to the raw image data prior to processing, as well as a minimum camera resolution for future experiments. Downstream of the filter application, the software to convert the 2D image data sets into surface pressure readings on a 3D grid use a ratio of decimation that assigns multiple pixels to each 3D grid node. This decimation ratio will also be aligned with the size of the blur filter, resulting in a more manageable data set size and compromised spatial resolution. Combined with the effect of the blur filter, the resulting pixel intensity readings will exhibit significantly reduced shot noise, reducing the magnitude of uncertainty and error in the final calculated pressure. For future tests, the camera spatial resolution must be sufficient to capture small flow and model features even after the recommended blur filter is applied. The image data set is taken from a uPSP experiment of the Space Launch System Block 1 cargo vehicle model in September 2019.

Lucy Tang↗
NASA NTRS2021

Unsteady Pressure-Sensitive Paint (UPSP) Shot Noise Reduction

In the study of unsteady Pressure-Sensitive Paint (uPSP) image data sets, pixel intensity values collected by Phantom cameras from multiple perspectives are used to calculate the surface pressure of an experimental model. This paper focuses on mitigation of shot noise which is introduced into the image data set by the cameras. Shot noise impacts the quality of data collected, increasing the system error in its pressure value calculations. This paper characterises statistical methods to reduce shot noise within experimental data by taking an average or weighted average across an area of pixels of their respective counts. Each combined-pixel has a higher total effective intensity value and therefore exhibits reduced noise throughout its time history. This is demonstrated by calculating the standard deviations of the combined pixel values through time, which decrease as the combined pixel area increases. Finally, these methods are compared across experimental wind tunnel conditions to examine their effectiveness at different Mach numbers. Ultimately, the results are used to recommend a blur filter type and size which will be applied to the raw image data prior to processing, as well as a minimum camera resolution for future experiments. Downstream of the filter application, the software to convert the 2D image data sets into surface pressure readings on a 3D grid use a ratio of decimation that assigns multiple pixels to each 3D grid node. This decimation ratio will also be aligned with the size of the blur filter, resulting in a more manageable data set size and compromised spatial resolution. Combined with the effect of the blur filter, the resulting pixel intensity readings will exhibit significantly reduced shot noise, reducing the magnitude of uncertainty and error in the final calculated pressure. For future tests, the camera spatial resolution must be sufficient to capture small flow and model features even after the recommended blur filter is applied. The image data set is taken from a uPSP experiment of the Space Launch System Block 1 cargo vehicle model in September 2019.

Lucy Tang↗
NASA NTRS1997

DCTune Perceptual Optimization of Compressed Dental X-Rays

In current dental practice, x-rays of completed dental work are often sent to the insurer for verification. It is faster and cheaper to transmit instead digital scans of the x-rays. Further economies result if the images are sent in compressed form. DCtune is a technology for optimizing DCT quantization matrices to yield maximum perceptual quality for a given bit-rate, or minimum bit-rate for a given perceptual quality. In addition, the technology provides a means of setting the perceptual quality of compressed imagery in a systematic way. The purpose of this research was, with respect to dental x-rays: (1) to verify the advantage of DCTune over standard JPEG; (2) to verify the quality control feature of DCTune; and (3) to discover regularities in the optimized matrices of a set of images. Additional information is contained in the original extended abstract.

Watson, Andrew B.↗
DOE OSTI2025

PhaseT3M: 3D imaging at 1.6 Å resolution via electron cryo-tomography with nonlinear phase retrieval

Electron cryo-tomography (cryo-ET) enables 3D imaging of complex, radiation-sensitive structures with molecular detail. However, image contrast from the interference of scattered electrons is nonlinear with atomic density and multiple scattering further complicates interpretation. These effects degrade resolution, particularly in conventional reconstruction algorithms, which assume linearity. Particle averaging can reduce such issues but is unsuitable for heterogeneous or dynamic samples ubiquitous in biology, chemistry, and materials sciences. Here, we develop a phase retrieval-based cryo-ET method, PhaseT3M. We experimentally demonstrate its application to an approximately 7 nm Co3O4 nanoparticle on an approximately 30 nm carbon substrate, achieving a maximum resolution of 1.6 Å, surpassing conventional limits using standard cryo-TEM equipment. PhaseT3M uses a multislice model for multiple scattering and Bayesian optimization for alignment and computational aberration correction, with a positivity constraint to recover ‘missing wedge’ information. Applied directly to biological particles, it enhances reconstruction quality and reduces artifacts, establishing a standard for routine 3D imaging with phase contrast.

Biophysics↗
NASA NTRS2000

3D MEMS in Standard Processes: Fabrication, Quality Assurance, and Novel Measurement Microstructures

Three-dimensional MEMS microsystems that are commercially fabricated require minimal post-processing and are easily integrated with CMOS signal processing electronics. Measurements to evaluate the fabrication process (such as cross-sectional imaging and device performance characterization) provide much needed feedback in terms of reliability and quality assurance. MEMS technology is bringing a new class of microscale measurements to fruition. The relatively small size of MEMS microsystems offers the potential for higher fidelity recordings compared to macrosize counterparts, as illustrated in the measurement of muscle cell forces.

Lin, Gisela↗
NASA NTRS2018

Reflectance-Based Imaging Spectrometer Error Budget Field Practicum at the Railroad Valley Test Site, Nevada

Calibration and validation determine the quality and integrity of the data provided by sensors and have enormous downstream impacts on the accuracy and reliabilityof the products generated by these sensors. With the imminent launch of the next generation of space borne imaging spectroscopy sensors, the IEEE Geoscience and Remote Sensing Society's (GRSS's) Geoscience Spaceborne Imaging Spectroscopy Technical Committee (GSIS TC) initiated a calibration and validation initiative.This article reports on a recent reflectance-based imaging spectrometer error budget field practicum focused on radiometric calibration of spaceborne imaging spectroscopy sensors. The field exercise, conducted at Railroad Valley in Nevada, provided valuable training for personnel in a variety of Earth observation (EO) areas, from engineers developing future sensors to calibration scientists actively working in the field. Future work in this area will focus on analyzing the data acquired as part of the training to answer numerous scientific questions, e.g., understanding the spatial and spectral homogeneity of the site being measured, identifying the optimal sampling to characterize the site, and optimizating the sampling techniques, including looking into the automation of some measurement protocol aspects. The training exercise was recorded to ensure that the knowledge can be disseminated across the GRSS and wider imaging spectroscopy community.

Ong, Cindy↗
NASA NTRSDate not supplied

On the use of DSCOVR EPIC to monitor the visible calibration stability of polar orbiting imagers to improve the next edition of the CERES climate data record.

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES instruments are onboard the Terra, Aqua, NPP, and NOAA-20 spacecraft. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert CERES footprint radiance observations into fluxes using empirically derived angular directional models obtained during early CERES record. CERES utilizes geostationary sensors to infer the regional diurnal fluxes in between Terra and Aqua CERES observations. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The Aqua-MODIS, SNPP-VIIRS, and NOAA-20 VIIRS afternoon imagers will also need to be radiometrically scaled to the same common calibration reference. Although all three imagers employ onboard solar diffusers, the calibration is not consistent over time due to instrument anomalies and ageing of the onboard calibrators. The CERES imager and GEO calibration group (IGCG) has been tasked to remove the imager channel calibration drifts for the next CERES reprocessing effort. The team will rely primarily on deep convective clouds, desert, and polar ice invariant targets to monitor the imager channel stability. The team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to Aqua-MODIS. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC instrument onboard DSCOVR employs a CCD array to image the Earth approximately every 2-hours. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. This is likely due to the DSCOVR satellite being located about a 1.5M km from the Earth, where very little Earth reflected solar radiation degrades the optics. The excellent radiometric stability of EPIC allows the CERES IGCG to utilize the EPIC observations as a stable reference for monitoring the calibration stability of the three afternoon imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗
NASA NTRS1997

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect local and regional climate and air quality. Clouds play a significant role in this relationship. Using GOES images, we found that in a 63-day period (5 July-5 September 1996) there were zero days which were clear for the entire daylight period. Days which are cloud-free in the morning become partly cloudy with small cumulus clouds in the afternoon in response to solar heating. This result casts doubt on the applicability of California-style air quality models which run in perpetual clear skies. Days which are clear in the morning have higher ozone than those which are cloudy in the morning. Using the RAMS model, we found that urbanization increases the skin surface temperature by about 1.0-1.5 C on average under cloudy conditions, with an extreme of +3.5 C. Clouds cool the surface due to their shading effect by 1.5-2.0 C on average, with an extreme of 5.0 C. RAMS simulates well the building stage of the cumulus cloud field, but does poorly in the decaying phase. Next year's work: doing a detailed cloud climatology and developing improved RAMS cloud simulations.

Kidder, Stanley Q.↗
NASA NTRS1995

Metrics and Benchmarks for Visualization

What is a "good" visualization? How can the quality of a visualization be measured? How can one tell whether one visualization is "better" than another? I claim that the true quality of a visualization can only be measured in the context of a particular purpose. The same image generated from the same data may be excellent for one purpose and abysmal for another. A good measure of visualization quality will correspond to the performance of users in accomplishing the intended purpose, so the "gold standard" is user testing. As a user of visualization software (or at least a consultant to such users) I don't expect visualization software to have been tested in this way for every possible use. In fact, scientific visualization (as distinct from more "production oriented" uses of visualization) will continually encounter new data, new questions and new purposes; user testing can never keep up. User need software they can trust, and advice on appropriate visualizations of particular purposes. Considering the following four processes, and their impact on visualization trustworthiness, reveals important work needed to create worthwhile metrics and benchmarks for visualization. These four processes are (1) complete system testing (user-in-loop), (2) software testing, (3) software design and (4) information dissemination. Additional information is contained in the original extended abstract.

Uselton, Samuel P.↗
NASA NTRS2004

Comparison of Satellite Observations of Aerosol Optical Depth to Surface Monitor Fine Particle Concentration

Under NASA's Earth Science Applications Program, the Infusing satellite Data into Environmental Applications (IDEA) project examined the relationship between satellite observations and surface monitors of air pollutants to facilitate a more capable and integrated observing network. This report provides a comparison of satellite aerosol optical depth to surface monitor fine particle concentration observations for the month of September 2003 at more than 300 individual locations in the continental US. During September 2003, IDEA provided prototype, near real-time data-fusion products to the Environmental Protection Agency (EPA) directed toward improving the accuracy of EPA s next-day Air Quality Index (AQI) forecasts. Researchers from NASA Langley Research Center and EPA used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument combined with EPA ground network data to create a NASA-data-enhanced Forecast Tool. Air quality forecasters used this tool to prepare their forecasts of particle pollution, or particulate matter less than 2.5 microns in diameter (PM2.5), for the next-day AQI. The archived data provide a rich resource for further studies and analysis. The IDEA project uses data sets and models developed for tropospheric chemistry research to assist federal, state, and local agencies in making decisions concerning air quality management to protect public health.

Kleb, Mary M.↗
NASA NTRS1993

HiRES - High Resolution Extreme Ultraviolet Spectroheliometer toroidal diffraction grating performance evaluation

The ray-tracing results presented characterize the theoretically achievable EUV performance of the HiRES instrument. The effects of optical system misalignment on spectrograph images, and the laboratory results for two f/15 toroidal diffraction gratings that employ a multianode microchannel array, are also presented. Interferometric studies of toroidal figure accuracy, as well as optical and electron microscopy investigations of surface quality, are discussed. While the current toroidal gratings are noted to furnish good imaging across a wide wavelength range, they exhibit excessive EUV scatter, as well as spectral ghosting.

Berger, Thomas E.↗
NASA NTRS2022

Maldives Climate: Monitoring Shoreline Changes and Island Loss in Response to Climate Change

Global sea level rise as a result of climate change continues to pose a critical threat to coastal ecosystems and populations. The archipelagic country of the Maldives is of critical concern due to being one of the lowest lying areas in the world. The development of reclaimed land in the Maldives by sand dredging has been a frequent response to both increasing sea levels and population increase. Such disturbance can lead to increased sedimentation off the coast and negatively impact coastal environments. Remote sensing tools such as satellite imagery have proved to be an effective tool in observing coastal changes in response to climate change and development. NASA DEVELOP created a methodology to analyze both water quality and shoreline erosion in the Maldives utilizing satellite imagery. Methods relied on open-source software such as QGIS and Google Earth Engine (GEE) and Satellite Imagery from PlanetScope, Landsat 8 Operational Land Instrument (OLI), Sentinel-2 Multi Spectral Instrument (MSI), and Aqua & Terra Moderate Resolution Imaging Radiospectrometer (MODIS) to analyze the changes in shorelines and assess water quality of select atolls within the Maldives. Findings show less shoreline change in developed parts of the island and more shoreline change in natural parts of the island. Additionally, water quality varies throughout the year and our data did not indicate seasonal trends. The methodology will be replicated to continue to monitor island erosion and water quality with the Maldives and will be applicable to other island and coastal systems.

remote sensing↗
NASA NTRSDate not supplied

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗
DOE OSTI2024

Machine learning informed control systems for extrusion printing processes

Systems and methods for controlling a material extrusion device to extrude a filament of an ink are provided. An extrusion printing control system collects from one or more sensors measurements representing an internal state of material extrusion processing during extrusion of the filament. In addition, the system collects an image of the filament as the filament is extruded. The system applies a classifier to the collected image to generate an image-derived state characterizing the filament. Based on the internal state and the image-derived state, the system estimates a derived state using a model. The system determines control parameters using the model to achieve a desired quality of the filament by minimizing a cost function based on the internal state, the image-derived state, the derived state, and constraints of the material extrusion device. Finally, the system provides the control parameters to a controller of the material extrusion device.

Howell, Brian↗
NASA NTRS2015

Exoplanet Coronagraph Shaped Pupil Masks and Laboratory Scale Star Shade Masks: Design, Fabrication and Characterization

Star light suppression technologies to find and characterize faint exoplanets include internal coronagraph instruments as well as external star shade occulters. Currently, the NASA WFIRST-AFTA mission study includes an internal coronagraph instrument to find and characterize exoplanets. Various types of masks could be employed to suppress the host star light to about 10 -9 level contrast over a broad spectrum to enable the coronagraph mission objectives. Such masks for high contrast internal coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultra-low reflectivity regions, uniformity, wave front quality, achromaticity, etc. We present the approaches employed at JPL to produce pupil plane and image plane coronagraph masks by combining electron beam, deep reactive ion etching, and black silicon technologies with illustrative examples of each, highlighting milestone accomplishments from the High Contrast Imaging Testbed (HCIT) at JPL and from the High Contrast Imaging Lab (HCIL) at Princeton University. We also present briefly the technologies applied to fabricate laboratory scale star shade masks.

black silicon↗