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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Features of Point Clouds Synthesized from Multi-View ALOS/PRISM Data and Comparisons with LiDAR Data in Forested Areas

LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.

LiDARD↗
NASA NTRS2018

Multi-Sensor Integration of Vegetation Index Products for Long-Term Monitoring of Vegetation Dynamics: A Case Study from MODIS to VIIRS

Spectral vegetation index (VI) time series data from moderate resolution sensors, such as Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), have widely been used to identify "hot spot" areas of vegetation changes and to characterize long-term trends of vegetation changes. The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor series of the Joint Polar Satellite System (JPSS) program is slated to continue the highly calibrated data stream initiated with MODIS. The first VIIRS sensor has operationally been acquiring Earth-reflected radiation since March 2012. The second VIIRS sensor (NOAA-20) was launched in November 2017, which is to continue the measurements made by the first VIIRS sensor. In this study, we examined an integrated use of MODIS and VIIRS VI time series data on capturing vegetation dynamics in the Asia-Pacific region using their overlapped period of observations (2013-2017). Three VIs, the "top-of-canopy (TOC)" normalized difference vegetation index (NDVI), TOC enhanced vegetation index (EVI), and TOC two-band enhanced vegetation index (EVI2), were investigated. For all the three VIs, VIIRS VIs were systematically higher than the MODIS counterparts due mainly to their spectral bandpass differences. However, both VIIRS and MODIS VIs showed the comparable spatial patterns in their temporal variations. Empirical spectral corrections allowed to merge the two data streams, which slightly improved the temporal resolution of the VI temporal profiles. These results suggest the suitability of VIIRS data to extend and merge into the MODIS VI record for long-term vegetation dynamics studies.

MODIS↗
NASA NTRS2015

Comparison of Surface and Column Variations of CO2 Over Urban Areas for Future Active Remote CO2 Sensors

High resolution in-situ CO2 measurements were recorded onboard the NASA P-3B during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) Field Campaign, to investigate the ability of space-based observations to accurately assess near surface conditions related to air quality. This campaign includes, Washington DC/Baltimore, MD (July 2011), San Joaquin Valley, CA (January - February 2013), Houston, TX (September 2013), and Denver, CO (July-August 2014). Each of these campaigns consisted of missed approaches and approximately two hundred vertical soundings of CO2 within the lower troposphere (surface to about 5 km). In this study, surface (0 - 1 km) and column-averaged (0 - 3.5 km) CO2 mixing ratio values from the vertical soundings in the four geographically different urban areas are used to investigate the temporal and spatial variability of CO2 within the different urban atmospheric emission environments. Tracers such as CO, CH2O, NOx, and NMHCs are used to identify the source of CO2 variations in the urban sites. Additionally, we apply nominal CO2 column weighting functions for potential future active remote CO2 sensors operating in the 1.57-microns and 2.05-microns measurement regions to convert the in situ CO2 vertical mixing ratio profiles to variations in CO2 column optical depths, which is what the active remote sensors actually measure. Using statistics calculated from the optical depths at each urban site measured during the DISCOVER-AQ field campaign and for each nominal weighting function, we investigate the natural variability of CO2 columns in the lower troposphere; relate the CO2 column variability to the urban surface emissions; and show the measurement requirements for the future ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) in the continental U.S. urban areas.

Choi, Yonghoon↗
NASA NTRS1984

Automatic holographic droplet analysis for liquid fuel sprays

The basic scheme for automated holographic analysis involves an optical system for reconstruction of the three dimensional real image of the droplet field, a spatial scanning system to transport a digitizing X-y image sensor through the real image, and processing algorithms for droplet recognition which establish the droplet sizes and positions. The hardware for system demonstrated includes the expanded and collimated beam from a 5 mW helium-neon laser for hologram reconstruction, an imaging lens for magnification of the real image field, and a video camera and digitizer providing 512-by-512 pixel resolution with 8-bit digitization. A mechanical stage is used to scan the hologram in three dimensional space, maintaining constant image magnification. A test droplet hologram is used for development and testing of the image processing algorithms.

Stanton, A. C.↗
NASA NTRS2002

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

Grecu, Mircea↗
NASA NTRS2014

S-NPP ATMS Instrument Prelaunch and On-Orbit Performance Evaluation

The first of a new generation of microwave sounders was launched aboard the Suomi-National Polar-Orbiting Partnership satellite in October 2011. The Advanced Technology Microwave Sounder (ATMS) combines the capabilities and channel sets of three predecessor sounders into a single package to provide information on the atmospheric vertical temperature and moisture profiles that are the most critical observations needed for numerical weather forecast models. Enhancements include size/mass/power approximately one third of the previous total, three new sounding channels, the first space-based, Nyquist-sampled cross-track microwave temperature soundings for improved fusion with infrared soundings, plus improved temperature control and reliability. This paper describes the ATMS characteristics versus its predecessor, the advanced microwave sounding unit (AMSU), and presents the first comprehensive evaluation of key prelaunch and on-orbit performance parameters. Two-year on-orbit performance shows that the ATMS has maintained very stable radiometric sensitivity, in agreement with prelaunch data, meeting requirements for all channels (with margins of ~40% for channels 1-15), and improvements over AMSU-A when processed for equivalent spatial resolution. The radiometric accuracy, determined by analysis from ground test measurements, and using on-orbit instrument temperatures, also shows large margins relative to requirements (specified as <1.0K for channels 1, 2, and 16-22 and <0.75 K for channels 3-15). A thorough evaluation of the performance of ATMS is especially important for this first proto-flight model unit of what will eventually be a series of ATMS sensors providing operational sounding capability for the U.S. and its international partners well into the next decade.

temperature↗
NASA NTRS2020

Terrain Relative Navigation for Guided Descent on Titan

Titan’s dense atmosphere, low gravity, and high winds at high altitudes create descent times of >90 minutes with standard entry/descent/landing (EDL) architectures and result in large unguided landing ellipses, with 99% values of 110x110 km and 149x72 km in recent Titan lander proposals. Enabling precision landing on Titan could increase science return for the types of missions proposed to date and make additional types of landing sites accessible, opening up new possibilities for science investigations. Precision landing on Titan has unique challenges, because the hazy atmosphere makes it difficult to see the surface and because it requires guided descent with divert ranges that are one to two orders of magnitude larger than needed for other target bodies, i.e. up to on the order of 100 km. It is conceivable that such a divert capability could be provided economically by a parafoil or other steerable aerodynamic decelerator deployed several 10s of km above the surface. The long descent times lead to large inertial navigation errors, hence a need for terrain relative navigation (TRN). This would require a TRN capability that can operate at such altitudes, despite challenges of seeing the surface sufficiently clearly and of depending on map products that are two orders of magnitude lower in spatial resolution than those for Mars and airless bodies. We then develop algorithms for map matching and feature tracking with descent images and test these with synthetic images created from Cassini/Huygens data sets and our radiative transfer model. We also introduce new possibilities for TRN based on the potential to discriminate some specific types of terrain onboard in descent imagery, such as lake vs adjacent ground and dune vs interdune. We use sensor measurement noise models in simulations of state estimation with an extended Kalman filter that includes coordinates of a set of tracked features in the state vector. Case studies were done for two notional landing sites, one in a site with only dry ground and one in a Titan lake district. In both cases, the filter error model shows 3 position error at touchdown on the order of 2 km. More work is needed to validate these results with higher fidelity camera models and larger data sets, but this is very promising.

Matthies, Larry↗
NASA NTRSDate not supplied

CyanoSCape: Freshwater Phytoplankton and Floating Aquatic Vegetation Biodiversity

In Southern Africa, the impacts of anthropogenic activities on biodiversity and ecosystem services are exacerbated by the climate crisis. Rapid land use change and the lack of emphasis on environmentally sustainable agricultural practices has hindered hydrological processes and compromised riverine and aquatic ecosystems. This poses obvious risks to natural/indigenous aquatic biodiversity and long-term ecosystem sustainability. Phytoplankton serve as the foundation of the freshwater food web with zooplankton as consumers, which feed fish, invertebrates, and so on up the food chain that comprises the biodiversity of the freshwater system that serves as habitat for biodiversity as well. The diversity of phytoplankton (microscopic organisms) includes photosynthesizing bacteria (cyanobacteria), plant-like diatoms, dinoflagellates, and green algae. Nutrient run-off from agricultural fertilizers and urban overflows, warm temperatures, abundant light availability and compromised hydrological systems provide an ideal environment for cyanobacteria to flourish. Increased prevalence of cyanobacteria, due to both natural and anthropogenic causes, can incur significant effects on the biodiversity of the overall phytoplankton assemblage. These bloom forming algae can significantly outcompete other phytoplankton classes in warmer and eutrophic waters where they are quick to dominate the freshwater system. Eutrophication and toxic cyanobacteria blooms (cyanoHABs) in the inland waters of the Greater Cape Floristic Region (GCFR) incur significant effects on the biodiversity of the overall phytoplankton assemblage and provide a favorable environment forthe overgrowth of floating aquatic vegetation (FAV), which is often invasive and associated with reduced aquatic biodiversity. The algal biodiversity of the GCFR’s freshwater systems is not well characterized. Hyperspectral optical observations are expected to facilitate the improvement of current phytoplankton functional type retrievals significantly, as the sensitivity is sufficient that the distinctive, fine spectral features of different phytoplankton groups can be detected. This will enable testing emerging algorithms and inform the development of new algorithms for use with upcoming hyperspectral satellite missions in this decade. Innovations in optical sensor sensitivity and next generation machine learning capabilities considerably enhance the potential for accurate and rapid detection of phytoplankton, namely the presence, extent, and diversity of cyanobacteria present in cyanoHABs and additionally, invasive FAV. Upcoming hyperspectral satellite missions such as NASA’s Surface Biology and Geology (SBG), Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and the European Space Agency’s Copernicus Hyperspectral Imaging Mission (CHIME) will provide imagery with unprecedented spectral and spatial resolution which will further enable the discovery of linkages between the seasonality and dynamics of HABs and FAV. The overarching goal of this project is to utilize hyperspectral data, with recently developed and next-generation algorithms, to determine the biodiversity of freshwater systems phytoplankton assemblage with emphasis on genus level distinction, as well as monitor the prevalence and diversity of FAV.

CyanoSCape↗
NASA NTRSDate not supplied

International Satellite Cloud Climatology Project (ISCCP) Ice Snow Product in Native (NAT) Format (ISCCP_ICESNOW_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=112 Km; Longitude_Resolution=112 Km; Temporal_Resolution=5-day].

SNOW COVER↗
NASA NTRSDate not supplied

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Temporal_Resolution=about 15 orbits/day].

AM-1↗
DOE OSTI2023

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗
NASA NTRS1989

Science requirements for passive microwave sensors on earth science geostationary platforms

It is suggested that the science requirements for passive geostationary microwave observations be met by near- and far-term sensors for each of two overlapping bands, with each band covering no more than a decade in frequency. The low-frequency band includes channels near 6, 10, 18, 22, 31 to 37, and possibly 50 to 60 GHz. The high-frequency band includes channels near 220 to 230, 183, 166, 118, 90 to 110, and possibly 50 to 60 and 31 to 37 GHz. The precise channel specifications will have to comply with international frequency allocations. The near-term goal is a high-frequency sensor based on a filled-aperture solid reflector antenna, which should rely on currently existing technology. The most critical issues for the near-term sensor are momentum compensation and the design of the feed assembly; these issues are coupled through the desired scan rate. The successful demonstration of the near-term (high-frequency) sensor will be essential for the continued development of far-term sensors satisfying the ideal science requirements. The far-term goal includes both a high-frequency sensor which meets the ideal science requirements, and a low-frequency sensor whose design will depend on advances in large antenna technology. The low-frequency (far-term) sensor might be based on one of several concepts: a deployable mesh reflector antenna of diameter at least 20 m, which shows promise for use at frequencies up to 30-GHz, a synthetic aperture interferometer of maximum baseline from 100 to 300 m, or a deployable phased-array bootlace lens, of diameter from 100 to 300 m. The first of these, a deployable mesh reflector antenna, will satisfy only the adequate spatial resolution requirements. The last two concepts meet the ideal spatial resolution science requirements, although they present significant structural and meteorological challenges.

Gasiewski, A. J.↗
NASA NTRS1991

Optical design of the Moderate Resolution Imaging Spectrometer - Tilt (MODIS-T) for the Earth Observing System (Eos)

The Moderate Resolution Imaging Spectrometer (MODIS) is an Earth viewing sensor that is planned as a facility instrument for the Earth Observing System (Eos) scheduled to begin functioning in the late 1990's. The MODIS is composed of two mutually supporting sensors one of which is MODIS-T, where 'T' signifies a tiltable along-track field of view. MODIS-T is a 32 channel imaging spectrometer with a required 10 nm to 15 nm spectral resolution (FWHM) in the 400 nm to 880 nm spectral range with less than 2.3 percent instrument induced linear polarization. The instrument provides at nadir a 33 km by 1500 km swath with a 1.1 km spatial resolution and an along-track pointing capability of +/- 50 deg about nadir. The heart of the optical design consists of a f/3 grating-type reflecting Schmidt camera.

Maymon, Peter W.↗
NASA NTRS1994

Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model

Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

Lin, D. S.↗
NASA NTRSDate not supplied

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=about 15 orbits/day].

NEAR IR IMAGERY↗
DOE OSTI2023

Direct observation of the local microenvironment in inhomogeneous CO 2 reduction gas diffusion electrodes via versatile pOH imaging

In this study, we report how the micrometer-scale morphology of a carbon dioxide reduction (CO 2 R) gas diffusion electrode (GDE) affects the mass transport properties and with it, the local CO 2 R performance. We developed a technique to probe the microenvironment in a CO 2 R GDE via local pOH imaging with time- and three-dimensional spatial, micrometer-scale resolution. The local activity of hydroxide anions (OH - ), represented by the pOH value, around a GDE in contact with an aqueous electrolyte is a crucial parameter that governs the catalytic activity and CO 2 R selectivity. Here, we use fluorescence confocal laser scanning microscopy (CLSM) to create maps of the local pOH around a copper GDE by combining two ratiometric fluorescent dyes, one of which is demonstrated as a pOH sensor for the first time in this work. We observe that the local pOH decreases when current is applied due to the creation of OH - as a byproduct of CO 2 R. Interestingly, the pOH is lower inside microtrenches compared to the electrode surface and decreases further as trenches become more narrow due to enhanced trapping of OH - . We support our experimental results with multiphysics simulations that correlate exceptionally well with measurements. These simulations additionally suggest that the decreased pOH inside microcavities in the surface of a CO 2 R GDE leads to locally enhanced selectivity towards multicarbon (C 2+ ) products. This study suggests that narrow microstructures on the length scale of 5 μm in a GDE surface serve as local CO 2 R hotspots, and thus highlights the importance of a GDE's micromorphology on the CO 2 R performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Wake Vortex Tracking Using a 35 GHz Pulsed Doppler Radar

A 35 GHz, pulsed-Doppler radar system has been designed and assembled for wake vortex detection and tracking in low visibility conditions. Aircraft wake vortices continue to be an important factor in determining safe following distances or spacings for aircraft in the terminal area. Currently, under instrument meteorological conditions (IMC), aircraft adhere to conservative, fixed following-distance guidelines based primarily on aircraft weight classifications. When ambient conditions are such that vortices will either drift or dissipate, leaving the flight corridor clear, the prescribed spacings are unnecessarily long and result in decreased airport throughput. There is a potential for significant airport efficiency improvement, if a system can be employed to aid regulators and pilots in setting safe and efficient following distances based on airport conditions. The National Aeronautics and Space Administration (NASA), the Federal Aviation Agency, and Volpe National Transportation Systems Center have promoted and worked to develop systems that would increase airport capacity and provide for safe reductions in aircraft separation. The NASA Aircraft Vortex Spacing System (AVOSS), a wake vortex spacing system that can provide dynamic adjustment of spacings based on real-time airport weather conditions, has demonstrated that Lidar systems can be successfully used to detect and track vortices in clear air conditions. To fill the need for detection capability in low-visibility conditions, a 35 GHz, pulsed-Doppler radar system is being investigated for use as a complimentary, low-visibility sensor for wake vortices. The radar sensor provides spatial and temporal information similar to that provided by Lidar, but under weather conditions that a Lidar cannot penetrate. Currently, we are analyzing the radar design based upon the data and experience gained during the wake vortex Lidar deployment with AVOSS at Dallas/Fort Worth International Airport. As part of this study, two numerical models were utilized in system simulations. The results of this study improve our understanding of the method of detection, resolution requirements for range and azimuth, pulse compression, and performance prediction. Simulations applying pulse compression techniques show that detection is good in heavy fog to greater than 2000 m. Both compressed and uncompressed short pulses show the vortex structure. To explore operational challenges, siting and scanning strategies were also analyzed. Simulation results indicate that excellent wake vortex detection, tracking and classification is possible in drizzle (+15 dBZ) and heavy fog (- 13 dBZ) using short pulse techniques (<99ns) at ranges on the order of 900 m, with a modest power of 500 W output. At 1600 m, detection can be expected at reflectivities as low as -13 dBZ (heavy fog). The radar system, as designed and built, has the potential to support field studies of a wake vortex spacing system in low-visibility conditions ranging from heavy fog to rain, when sited within 2000m of the flight path.

Neece, Robert T.↗