SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Acoustic images of a silicon carbide ceramic disk were obtained using a precision scanning contact pulse echo technique. Phase and cross-correlation velocity, and attenuation maps were used to form color images of microstructural variations. These acoustic images reveal microstructural variations not observable with X-ray radiography.
Acoustic images of silicon carbide ceramic disks were obtained using a precision scanning contact pulse-echo technique. Phase and cross-correlation velocity and attenuation maps were used to form color images of microstructural variations. These acoustic images reveal microstructural variations not observable with X-radiography.
Preliminary results of early-type galaxies that will be part of a galaxy catalog to be derived from the complete Rosat data base are presented. The stored data were reduced and analyzed by an automatic pipeline. This pipeline is based on a command language scrip. The important features of the pipeline include new data time screening in order to maximize the signal to noise ratio of faint point-like sources, source detection via a wavelet algorithm, and the identification of sources with objects from existing catalogs. The pipeline outputs include reduced images, contour maps, surface brightness profiles, spectra, color and hardness ratios.
A pressure-sensitive paint (PSP) technique was applied in a wind tunnel experiment in the NASA Langley Research Center 8-Foot Transonic Pressure Tunnel to study the effect of wing fillets on the global vortex induced surface static pressure field about a sharp leading-edge 76 deg./40 deg. double delta wing, or strake-wing, model at subsonic and transonic speeds. Global calibrations of the PSP were obtained at M(sub infinity) = 0.50, 0.70, 0.85, 0.95, and 1.20, a Reynolds number per unit length of 2.0 million, and angles of attack from 10 degrees to 20 degrees using an insitu method featuring the simultaneous acquisition of electronically scanned pressures (ESP) at discrete locations on the model. The mean error in the PSP measurements relative to the ESP data was approximately 2 percent or less at M(sub infinity) = 0.50 to 0.85 but increased to several percent at M(sub infinity) =0.95 and 1.20. The PSP pressure distributions and pseudo-colored, planform-view pressure maps clearly revealed the vortex-induced pressure signatures at all Mach numbers and angles of attack. Small fillets having parabolic or diamond planforms situated at the strake-wing intersection were respectively designed to manipulate the vortical flows by removing the leading-edge discontinuity or introducing additional discontinuities. The fillets caused global changes in the vortex-dominated surface pressure field that were effectively captured in the PSP measurements. The vortex surface pressure signatures were compared to available off-surface vortex cross-flow structures obtained using a laser vapor screen (LVS) flow visualization technique. The fillet effects on the PSP pressure distributions and the observed leading-edge vortex flow characteristics were consistent with the trends in the measured lift, drag, and pitching moment coefficients.
The NASA Ames hyperwall is a display system designed to facilitate the visualization of sets of multivariate and multidimensional data like those generated in complex engineering and scientific computations. The hyperwall includes a 77 matrix of computer-driven flat-panel video display units, each presenting an image of 1,280 1,024 pixels. The term hyperwall reflects the fact that this system is a more capable successor to prior computer-driven multiple-flat-panel display systems known by names that include the generic term powerwall and the trade names PowerWall and Powerwall. Each of the 49 flat-panel displays is driven by a rack-mounted, dual-central-processing- unit, workstation-class personal computer equipped with a hig-hperformance graphical-display circuit card and with a hard-disk drive having a storage capacity of 100 GB. Each such computer is a slave node in a master/ slave computing/data-communication system (see Figure 1). The computer that acts as the master node is similar to the slave-node computers, except that it runs the master portion of the system software and is equipped with a keyboard and mouse for control by a human operator. The system utilizes commercially available master/slave software along with custom software that enables the human controller to interact simultaneously with any number of selected slave nodes. In a powerwall, a single rendering task is spread across multiple processors and then the multiple outputs are tiled into one seamless super-display. It must be noted that the hyperwall concept subsumes the powerwall concept in that a single scene could be rendered as a mosaic image on the hyperwall. However, the hyperwall offers a wider set of capabilities to serve a different purpose: The hyperwall concept is one of (1) simultaneously displaying multiple different but related images, and (2) providing means for composing and controlling such sets of images. In place of elaborate software or hardware crossbar switches, the hyperwall concept substitutes reliance on the human visual system for integration, synthesis, and discrimination of patterns in complex and high-dimensional data spaces represented by the multiple displayed images. The variety of multidimensional data sets that can be displayed on the hyperwall is practically unlimited. For example, Figure 2 shows a hyperwall display of surface pressures and streamlines from a computational simulation of airflow about an aerospacecraft at various Mach numbers and angles of attack. In this display, Mach numbers increase from left to right and angles of attack increase from bottom to top. That is, all images in the same column represent simulations at the same Mach number, while all images in the same row represent simulations at the same angle of attack. The same viewing transformations and the same mapping from surface pressure to colors were used in generating all the images.
Rosetta is an international mission led by the European Space Agency (ESA) with key support and instrumentation from the National Aeronautics and Space Administration (NASA). Rosetta is currently on a ten-year mission to catch comet 67P/Churyumov-Gerasimenko (C-G); throughout its voyage, the spacecraft has performed flybys of two main belt asteroids (MBA): Steins and Lutetia. Data on the physical, chemical, and geological properties of these asteroids are currently being processed and analyzed. Accurate interpretation of such data is fundamental in the success of Rosetta's mission and overall objectives. Post-flyby data analyses strive to correlate the size, shape, volume, and rotational rate of Lutetia, in addition to interpreting its multi-color imagining, albedo, and spectral mapping. Although advancements in science have contributed to the examination of celestial bodies, methods to analyze asteroids remain largely empirical, not semi-empirical, nor ab initio. This study aims to interpret and document the scientific methods currently utilized in the characterization of asteroid (21) Lutetia in order to render these processes and methods accessible to the public. Examples include a standardized technique for assessing the age of an asteroid surface, complete with clickable reference maps, methodology of grouping surface characteristics together, and a standardized power law equation for the age. Other examples include determining the density of an object. Context for what both density and age mean is a bi-product of this study. Results of the study will aid in the development of pedagogical material on asteroids for public use, and in creation of an academic database for selected targets that might be used as a reference.
We present new observations of the jet features in the barred spiral galaxy NGC 1097, including optical spectroscopy of the brightest jet features, two-color optical imagery, new VLA mapping at 327 MHz, and archival 1.4 GHz VLA data reprocessed for improved sensitivity.
Scheduled for launch in January 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. This paper describes the methods used for pre-launch calibration of OCI and considerations to ensure the combination of Ground Support Equipment (GSE) and instrument effects meet uncertainty and performance requirements. General considerations when designing a calibration campaign are also discussed.
Scheduled for launch in January 2024, the Phytoplankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records [1]. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. This paper describes the results of the prelaunch test campaign of the OCI Flight Unit. The measured OCI flight unit performance exceeded requirement thresholds in all critical areas. Overall, the performance of the OCI is excellent, and will allow the PACE science team to meet its science objectives.
Scheduled for launch in January 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records [1]. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. A critical requirement for OCI is the high-contrast or spatial cross-talk specification (also referred to as in-field stray-light response). The requirement states that for global top-of-atmosphere radiances based on measured MODIS radiances, the global average residual contamination shall be less than 0.15% for any multispectral band. Accurate resolution of high contrast in TOA radiance images is important to estimate stray light contamination due to clouds, for studying small scale features like ocean fronts and for working in coastal and estuarine areas where the scales are 1km. This occurs in all wavelengths in the spatial direction. Knowledge of high contrast resolution makes up part of the artifact budget. Accurate measurement of the high-contrast performance of OCI requires laboratory Ground Support Equipment (GSE) that projects a scene of sufficient quality that the unwanted stray light of the GSE itself is not confused with the stray light response of the telescope. This paper concerns the development, analyses and test of the GSE to ensure the quality of the projected image is sufficient to verify the OCI requirements. Optical models were developed for both the instrument as well as the GSE and laboratory environment. Simulation of various non-ideal parameters were critical to accurately predict performance. Measurements using COTS cameras and lenses were also made of the projected GSE image to reasonably verify the optical model predictions. Measured and modelled results from OCI are discussed.
Scheduled for launch in January 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records [1]. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. A critical requirement for OCI is the high-contrast or spatial cross-talk specification (also referred to as in-field stray-light response). The requirement states that for global top-of-atmosphere radiances based on measured MODIS radiances, the global average residual contamination shall be less than 0.15% for any multispectral band. Accurate resolution of high contrast in TOA radiance images is important to estimate stray light contamination due to clouds, for studying small scale features like ocean fronts and for working in coastal and estuarine areas where the scales are 1km. This occurs in all wavelengths in the spatial direction. Knowledge of high contrast resolution makes up part of the artifact budget. Accurate measurement of the high-contrast performance of OCI requires laboratory Ground Support Equipment (GSE) that projects a scene of sufficient quality that the unwanted stray light of the GSE itself is not confused with the stray light response of the telescope. This paper concerns the development, analyses and test of the GSE to ensure the quality of the projected image is sufficient to verify the OCI requirements. Optical models were developed for both the instrument as well as the GSE and laboratory environment. Simulation of various non-ideal parameters were critical to accurately predict performance. Measurements using COTS cameras and lenses were also made of the projected GSE image to reasonably verify the optical model predictions. Measured and modelled results from OCI are discussed.
Launched in February 2024, the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI provides two day global coverage of top-of-atmosphere radiances. Unlike its predecessors, OCI covers a spectral range from 340 nm to 2260 nm. Below 900 nm, OCI provides hyperspectral radiances sampled every 2.5 nm or 1.25nm, with a bandwidth of 5 nm for each channel. Its spatial resolution is about 1.2km. The high radiometric accuracy of OCI was made possible by a thorough and extensive prelaunch characterization campaign, conducted at NASA’s Goddard Space Flight Center. This presentation describes the prelaunch radiometric characterization (approach and results) of OCI, such as e.g. the linearity correction, signal to noise ratio, polarization, IFOV, relative spectral response, radiometric gain, temperature sensitivity, optical crosstalk, and response versus scan angle.
The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission is NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer, Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. The geolocation processing is performed for OCI using spacecraft navigation data and an instrument geometry model. To evaluate the geolocation accuracy for OCI and develop refinements to the processing methods, control point matching using Landsat data has been implemented as a step in the operational processing of OCI data at the Science Data Segment. This processing provides between 200 and 300 high-quality matchups per day with good global and geometric distribution, allowing rapid evaluation of the OCI geolocation accuracy. The results provided an early indication of the overall quality of the geolocation processing and of specific aspects needing improvement. A standard set of granules was identified to support rapid implementation and testing of geolocation refinements, and this approach has been highly successful in improving the geolocation processing accuracy to meet the science requirements. The evaluation will continue throughout the mission to ensure the ongoing accuracy of geolocation. This paper describes the control point matching methodology, the approach to development of the geolocation processing refinements, and the recent results.
The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission is NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer, Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. The geolocation processing is performed for OCI using spacecraft navigation data and an instrument geometry model. To evaluate the geolocation accuracy for OCI and develop refinements to the processing methods, control point matching using Landsat data has been implemented as a step in the operational processing of OCI data at the Science Data Segment. This processing provides between 200 and 300 high-quality matchups per day with good global and geometric distribution, allowing rapid evaluation of the OCI geolocation accuracy. The results provided an early indication of the overall quality of the geolocation processing and of specific aspects needing improvement. A standard set of granules was identified to support rapid implementation and testing of geolocation refinements, and this approach has been highly successful in improving the geolocation processing accuracy to meet the science requirements. The evaluation will continue throughout the mission to ensure the ongoing accuracy of geolocation. This paper describes the control point matching methodology, the approach to development of the geolocation processing refinements, and the recent results.
There are no author-identified significant results in this report. Evaluation has begun on ERTS-1 imagery of Crook County for use in landform interpretation and geologic mapping and interpretation. Outside of Crook County the geology team has been impressed by the display of fault patterns in southeastern Oregon and has begun preliminary analyses of these. Using the color combiner a complete timber type map of (1) all the forest land within Crook County, and (2) all the Ochoco National Forest has been completed. The timber types consist of five density classes which are correlated with different species compositions as the first step in the multistage forest inventory. Using the ERTS magnetic tape data the computer center has produced a 12 by 25 mile strip printout of bands 5, 6, and 7. The computer printouts are to be analyzed for different timber types and possible insect damage. Other results are: (1) limited number of clearcuts in eastern Oregon and in Cascades evident; (2) positive transparencies of band 5 appear to be too dark for maximum information of forested areas; and (3) much more information in the computer printouts of bands 6 and 7, than 5, when analyzing forest conditions.
The author has identified the following significant results. The Lydich quadrangle area was successfully classified into seven cover types: (1) trees, (2) poorly drained soil and water, (3) pasture land, (4) well drained brown soil, (5) moderately well drained dark brown soil, (6) moderately drained soil, and (7) medium to poorly drained soil. Measurements of the percent of mapping unit represented by a named soil series range from 44 to 55 percent. If the class identified as vegetation is combined with the named unit, the range increases from 54 to 64 percent. The Xenia mapping unit was the only unit represented by less than 50 percent of the named unit. Results from the intensive tent moth study in Owensburg and Williams were interpreted from 70 mm color infrared and visually transferred to maps. A correction factor was necessary, because the date the sample photography was taken was a month later than the intensive site data (CF x acres defoliated in each level = expanded defoliated acres).
The optics technology necessary for future solar system exploration is discussed. To satisfy the various mission objectives, optical components need to be of low weight, provide adequate spatial resolution and mapping coverage, provide necessary spectral resolution, provide means to perform adaptable mapping spectrometry, operate under low light levels, provide color images of high fidelity and operate under high temperatures. Future near-infrared mapping spectrometers are examined, and the use of focal-plane detectors to improve their sensitivity is discussed.
In terrestrial and marine ecosystems, remote sensing has been used to estimate gross primary productivity (GPP) for decades, but few applications exist for shallow freshwater ecosystems.Here we show field-based GPP correlates with satellite and airborne lake color across a range of optically and limnologically diverse lakes in interior Alaska. A strong relationship between in situ GPP derived from stable oxygen isotopes (δ18O) and space-based lake color from satellites (e.g. Landsat-8, Sentinel-2 and CubeSats) and airborne imagery (AVIRIS-NG) demonstrates the potential power of this technique for improving spatial and temporal monitoring of lake GPP when coupled with additional field validation measurements across different systems. In shallow waters clear enough for sunlight to reach lake bottoms, both submerged vegetation (macrophytes and algae) and phytoplankton likely contribute to GPP. The stable isotopes and remotely sensed shallow lake color used here integrate both components. These results demonstrate the utility of lake color as a feasible means for mapping lake GPP from remote sensing. This novel methodology estimates GPP from remote sensing in shallow lakes by combining field measurements of oxygen isotopes with airborne, satellite and CubeSat imagery. This use of lake color for providing insight into ecological processes of shallow lakes is recommended, especially for remote arctic and boreal landscapes.