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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

AVIRIS performance during the 1987 flight season: An AVIRIS project assessment and summary of the NASA-sponsored performance evaluation

Results are presented of the assessment of AVIRIS performance during the 1987 flight season by the AVIRIS project and the earth scientists who were chartered by NASA to conduct an independent data quality and sensor performance evaluation. The AVIRIS evaluation program began in late June 1987 with the sensor meeting most of its design requirements except for signal-to-noise ratio in the fourth spectrometer, which was about half of the required level. Several events related to parts failures and design flaws further reduced sensor performance over the flight season. Substantial agreement was found between the assessments by the project and the independent investigators of the effects of these various factors. A summary of the engineering work that is being done to raise AVIRIS performance to its required level is given. In spite of degrading data quality over the flight season, several exciting scientific results were obtained from the data. These include the mapping of the spatial variation of atmospheric precipitable water, detection of environmentally-induced shifts in the spectral red edge of stressed vegetation, detection of spectral features related to pigment, leaf water and ligno-cellulose absorptions in plants, and the identification of many diagnostic mineral absorption features in a variety of geological settings.

Vane, Gregg↗
DOE OSTI2019

Multi-Formalism Modeling for Disaster Resilience, Forecasting, and Response

Disaster response preparedness, risk mitigation, and effective post-event response are critical for national security, public health, and economic integrity. For areas impacted by extreme events, timely and accurate impact assessments of lifeline infrastructures are critical. Traditional disaster management and situational awareness platforms are not capable of handling the massive influx of available information from traditional and non-traditional sources. Next-generation analytic assessment approaches, where use of dynamically sourced, heterogeneous data with near real-time availability are integrated into a continually-updated analytics framework. The objective of this research was to develop a foundational multi-formalism modeling platform to integrate novel data sources for use in improving situational awareness after a disaster event. Specifically, to 1) provide an architecture for machine-learning based data fusion various multi-sensor datasets; 2) classify, geolocate, and temporally bin novel data sources for use in spatially-enabled machine-learning based data fusion; and 3) derive confidence-based observation data with machine-learning based prediction to fill spatial and temporal observation gaps. This project developed a reusable cloud-based pipeline architecture for ingesting, storing, and analyzing relevant data, executing a range of deep-learning models, and visualize the information geographically. The pipeline development was informed by previous PNNL investments (StreamKit) and built upon leading-edge technologies consisting of: 1) a raw datastore; 2) a data enrichment pipeline with custom and third-party analytics; 3) enriched data storage; and 4) a custom UI to display the enriched data. Machine learning/deep learning models were selected and tested to classify social media images for relevancy and presence of flood waters. Our custom trained relevance models were run on a validation dataset and the overall accuracy of the relevance classifiers ranged from 65% to 90%. We found that convolutional neural network (CNN) models were both faster and more accurate than more traditional machine learning models. We applied the relevance classifier to remove non-relevant images and then undertook a limited training of CNN models to detect flood on ~1,800 labeled images. The testing accuracy of the flood detection models were ~88%. To improve the geographic location of both social media and oblique aerial images we tested a multi-step workflow built on a pre-trained deep-learning model. To identify similarity features from test and reference scenes, we applied the Xception and Faiss models to a set of test images with inaccurate spatial locations, as well and precisely-located reference scenes from the general area. Matching reference scenes to the test scenes with the closest similarity index had limited success in improving the precision of test scene location and additional methods have been identified for testing. Data fusion between authoritative geographic data (satellite imaging) and non-authoritative crowdsourced data is an underlying theme throughout this research and methods are tested bring these data to a common geographic form through feature matching and transformations. The automated extraction of supporting information for disaster response from oblique aerial images or ground-level social media images is accomplished through semantic image segmentation and transformation. The non-authoritative data are used to validate the authoritative data collections and processing and optionally, t+0 flood models. In addition, the common form geographic data are combined with other static landscape features to develop spatially-explicit training vectors used in deep generative statistical inference models to develop complex non-linear relationships in static and dynamic data and ultimately derive a spatially continuous and probabilistic assessment of flood damage with the event domain.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1997

Flight Demonstration of a Shock Location Sensor Using Constant Voltage Hot-Film Anemometry

Flight tests have demonstrated the effectiveness of an array of hot-film sensors using constant voltage anemometry to determine shock position on a wing or aircraft surface at transonic speeds. Flights were conducted at the NASA Dryden Flight Research Center using the F-15B aircraft and Flight Test Fixture (FTF). A modified NACA 0021 airfoil was attached to the side of the FTF, and its upper surface was instrumented to correlate shock position with pressure and hot-film sensors. In the vicinity of the shock-induced pressure rise, test results consistently showed the presence of a minimum voltage in the hot-film anemometer outputs. Comparing these results with previous investigations indicate that hot-film anemometry can identify the location of the shock-induced boundary layer separation. The flow separation occurred slightly forward of the shock- induced pressure rise for a laminar boundary layer and slightly aft of the start of the pressure rise when the boundary layer was tripped near the airfoil leading edge. Both minimum mean output and phase reversal analyses were used to identify the shock location.

Moes, Timothy R.↗
NASA NTRS2013

Corrections to the MODIS Aqua Calibration Derived From MODIS Aqua Ocean Color Products

Ocean color products such as, e.g., chlorophyll-a concentration, can be derived from the top-of-atmosphere radiances measured by imaging sensors on earth-orbiting satellites. There are currently three National Aeronautics and Space Administration sensors in orbit capable of providing ocean color products. One of these sensors is the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, whose ocean color products are currently the most widely used of the three. A recent improvement to the MODIS calibration methodology has used land targets to improve the calibration accuracy. This study evaluates the new calibration methodology and describes further calibration improvements that are built upon the new methodology by including ocean measurements in the form of global temporally averaged water-leaving reflectance measurements. The calibration improvements presented here mainly modify the calibration at the scan edges, taking advantage of the good performance of the land target trending in the center of the scan.

MODIS↗
NASA NTRSDate not supplied

Chasing Spacecraft

Measurements made during actual flight on a spacecraft represent the holy grail in supporting cutting edge research and providing critical vehicle health information during exposure to the harsh environments of launch and reentry. Remote optical imaging data obtained by the Scientifically Calibrated In-Flight Imagery (SCIFLI) team at NASA Langley Research Center (LaRC) is currently being used by NASA’s Artemis and Commercial Crew Programs to ensure the safety of astronauts. This emerging capability had its genesis during the Space Shuttle Program. A look toward the future will showcase the use of high-altitude long-endurance uncrewed aircraft coupled with novel sensors to support civilian and national flight-testing interests more effectively.

Tom Horvath↗
NASA NTRS2026

A Multi-Tier Autonomous Aerial Architecture for Wildfire Detection, Characterization, and Communication in Infrastructure-Denied Environments

Wildfire response depends on how fast an ignition can be confirmed and located, especially in remote regions where ground-based communication and monitoring may be limited. Geostationary sensors provide frequent observations but at kilometer-scale resolution, which is too coarse to resolve small fires in remote terrain. Ground camera networks require sightlines and infrastructure that back-country areas lack. To address these limitations, this work proposes a Multi-Tier Autonomous Wildfire Intelligence System that combines wide-area monitoring with targeted, high-resolution sensing. A solar-powered high-altitude long endurance (HALE) platform operating at approximately 60,000 ft provides persistent wide-area thermal and optical surveillance, running onboard edge inference to screen candidate ignitions and reduce false positives and downlink bandwidth. When a candidate ignition is detected, low-altitude uncrewed aircraft systems (UAS) can be deployed to conduct localized observations, including high-resolution imaging and atmospheric measurements such as wind and plume observation. By combining persistent detection with local sensing, the proposed architecture is designed to provide first responders with timely, high-resolution information about fire location and behavior to aid in emergency decision making.

Wildfire management, UAS, drones↗
DOE OSTI2025

Model Residuals as Shields: A Two-Level Formulation to Defend Smart Grids From Poisoning Attacks

The advancement of smart grids presents both vast opportunities and heightened cybersecurity risks. Data-driven defense mechanisms, though designed as a shield against these threats, can fall prey to poisoning attacks. We delve into regression settings, underscoring the imperative to fortify defenses against a spectrum of poison ratios, notably those above 0.5—an issue scarcely addressed in prior studies. Recognizing the susceptibilities of smart grids and their manipulable sensors, we exploit the very intent of poisoning attacks, compromising model accuracy, as our defense mechanism. Our proposed two-level optimization framework discerns between poisoned and authentic data based on model residuals, outperforming or matching existing methods in 72% to 77% of precision and 75% to 80% of recalls across various poisoning attacks, poison ratios, and datasets. Once the authentic data are identified, the trained model is adaptable for a variety of applications. Comprehensive evaluations on different smart grid datasets, pitted against myriad poisoning schemes, validate our methodology’s edge over existing methods. Here, we also shed light on the implications of model misspecification originating from temporal auto-correlation, a common feature in Internet of Things and smart grid data.

Adversarial machine learning (ML)↗
DOE OSTI2021

Formation of three-dimensional bicontinuous structures via molten salt dealloying studied in real-time by in situ synchrotron X-ray nano-tomography

Abstract Three-dimensional bicontinuous porous materials formed by dealloying contribute significantly to various applications including catalysis, sensor development and energy storage. This work studies a method of molten salt dealloying via real-time in situ synchrotron three-dimensional X-ray nano-tomography. Quantification of morphological parameters determined that long-range diffusion is the rate-determining step for the dealloying process. The subsequent coarsening rate was primarily surface diffusion controlled, with Rayleigh instability leading to ligament pinch-off and creating isolated bubbles in ligaments, while bulk diffusion leads to a slight densification. Chemical environments characterized by X-ray absorption near edge structure spectroscopic imaging show that molten salt dealloying prevents surface oxidation of the metal. In this work, gaining a fundamental mechanistic understanding of the molten salt dealloying process in forming porous structures provides a nontoxic, tunable dealloying technique and has important implications for molten salt corrosion processes, which is one of the major challenges in molten salt reactors and concentrated solar power plants.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Calibrating the Helium Pressurization System for the Space Shuttle Liquid-Hydrogen Tank

Analysis of the results from the STS-114 tanking tests and subsequent launch called into question existing thermal and mass models of helium pressurization of the liquid hydrogen tank. This hydrogen tank, which makes up the bottom two-thirds of the External Tank, is pressurized prior to launch to avoid cavitation in the Shuttle Main Engine pumps. At about 2 minutes prior to launch, the main vent valve is closed, and pressurized helium flows into the tank ullage space to achieve set point pressure. As the helium gas cools, its pressure drops, calling for additional helium. Subsequent helium flows are provided in short, timed pulses. The number of pulses is taken as a rough leak indicator. An analysis of thermal models by Marshall Space Flight Center showed considerable uncertainty in the pressure-versus-time behavior of the helium ullage space and the ability to predict the number of pulses normally expected. Kennedy Space Center proposed to calibrate the dime-sized orifice, which together with valves, controls the helium flow quantity (Figure 1). Pressure and temperature sensors were installed to provide upstream and downstream measurements necessary to compute flow rate based on the orifice discharge coefficient. An assessment of flow testing with helium indicated an extremely costly use of this critical resource. In order to reduce costs, we proposed removing the orifices from each Mobile Launcher Platform (MLP) and asking Colorado Engineering Experiment Station Inc. (CEESI) to calibrate the flow. CEESI has a high-pressure air flow system with traceable flow meters capable of handling the large flow rates. However, literature research indicated that square-edged orifices of small diameters often exhibit significant hysteresis and nonrepeatability in the vicinity of choked or sonic flow. Fortunately, the MLP orifices behaved relatively well in testing (Figure 2). Using curve fitting of the air-flow data, in conjunction with ASME orifice modeling equations, a method of relating the helium mass flow to measured air flow data was obtained. This analysis showed that the highest uncertainty in flow occurred in the vicinity of the choking pressure ratio, as would be expected. In addition, analysis of typical flow pulses showed that most of the helium flow occurred either well below or well above this uncertain area. The final result is the ability to provide postlaunch estimates of helium mass flows that are within 1.5 percent of the actual value.

Source record↗
NASA NTRS2015

VIIRS-J1 Polarization Narrative

The VIS/NIR bands polarization sensitivity of Joint Polar Satellite Sensor 1 (JPSS1) Visible/Infrared Imaging Radiometer Suite (VIIRS) instrument was measured using a broadband source. While polarization sensitivity for bands M5-M7, I1, and I2 was less than 2.5%, the maximum polarization sensitivity for bands M1, M2, M3, and M4 was measured to be 6.4%, 4.4%, 3.1%, and 4.3%, respectively with a polarization characterization uncertainty of less than 0.3%. A detailed polarization model indicated that the large polarization sensitivity observed in the M1 to M4 bands was mainly due to the large polarization sensitivity introduced at the leading and trailing edges of the newly manufactured VISNIR bandpass focal plane filters installed in front of the VISNIR detectors. This was confirmed by polarization measurements of bands M1 and M4 bands using monochromatic light. Discussed are the activities leading up to and including the instruments two polarization tests, some discussion of the polarization model and the model results, the role of the focal plane filters, the polarization testing of the Aft-Optics-Assembly, the testing of the polarizers at Goddard and NIST and the use of NIST's T-SIRCUS for polarization testing and associated analyses and results.

polarization↗
NASA NTRSDate not supplied

Leading University Students to the Edge of Space

For over 16 years, the Louisiana Space Grant Consortium (LaSPACE), the NASA Balloon Program Office (BPO), and the NASA Columbia Scientific Balloon Facility (CSBF) have collaborated in a series of high altitude balloon-based programs involving hands-on authentic learning experiences that expose university students and other participants to technical skills, teamwork dynamics, and effective communication methods. Such programs go beyond what is possible to achieve in a normal classroom and help prepare future engineers and scientists for a successful aerospace workforce career. In our collaborative effort, LaSPACE has focused on the program content and student mentoring while NASA BPO and CSBF provide balloon flight support and operations. The entry-level Louisiana Aerospace Catalyst Experiences for Students (LaACES) builds students’ skills in basic electronics, sensor interfacing, real-time programming, mechanical development, and project management. These skills are then applied to the design, development, fabrication, and flight of a small (∼500 gram) balloon payload. Finally, the payloads are flight-tested to an altitude of ∼30 km using a 2 kg latex sounding balloon. The LaACES program includes a set of lectures, activities, and Arduino Mega based electronic kits that are used for skill building and as a core control system for the student payload. The more advanced High Altitude Student Platform (HASP) is designed to carry ∼twelve 3 to 20 kg student payloads to an altitude of about 36 kilometers with flight durations of 10 to 20 hours using a ∼311,500 cubic meter, zero pressure balloon. HASP provides all student payloads with power, downlink telemetry, uplink commanding, and real-time HD video for instrument control and assessment during the flight. While originally developed for university students, these programs have been adapted to projects focused on high school teachers as well as affecting minorities underrepresented in aerospace related science and engineering fields. We are now in the process of adapting the LaACES materials to a pre-engineering curriculum for high school students as well as for widespread access over the internet. During this presentation, we will provide details of both the LaACES and HASP programs, how these programs have engaged participants from all demographic groups, and our current plans for continuing and expanding upon our success.

University↗
DOE OSTI2021

Prediction of Solar Irradiance and Photovoltaic Solar Energy Product Based on Cloud Coverage Estimation Using Machine Learning Methods

Cloud cover estimation from images taken by sky-facing cameras can be an important input for analyzing current weather conditions and estimating photovoltaic power generation. The constant change in position, shape, and density of clouds, however, makes the development of a robust computational method for cloud cover estimation challenging. Accurately determining the edge of clouds and hence the separation between clouds and clear sky is difficult and often impossible. Toward determining cloud cover for estimating photovoltaic output, we propose using machine learning methods for cloud segmentation. We compare several methods including a classical regression model, deep learning methods, and boosting methods that combine results from the other machine learning models. To train each of the machine learning models with various sky conditions, we supplemented the existing Singapore whole sky imaging segmentation database with hazy and overcast images collected by a camera-equipped Waggle sensor node. We found that the U-Net architecture, one of the deep neural networks we utilized, segmented cloud pixels most accurately. However, the accuracy of segmenting cloud pixels did not guarantee high accuracy of estimating solar irradiance. We confirmed that the cloud cover ratio is directly related to solar irradiance. Additionally, we confirmed that solar irradiance and solar power output are closely related; hence, by predicting solar irradiance, we can estimate solar power output. This study demonstrates that sky-facing cameras with machine learning methods can be used to estimate solar power output. This ground-based approach provides an inexpensive way to understand solar irradiance and estimate production from photovoltaic solar facilities.

14 SOLAR ENERGY↗
NASA NTRS1998

Wheel Abrasion Experiment Conducted on Mars

Sojourner rover showing Lewis' wheel abrasion experiment. The Mars Pathfinder spacecraft soft-landed on Mars on July 4, 1997. Among the many experiments on its small Sojourner rover are three technology experiments from the NASA Lewis Research Center, including the Wheel Abrasion Experiment (WAE). The WAE was designed, built, delivered, and operated on Mars by a team of engineers and scientists from Lewis' Photovoltaics and Space Environments Branch. This experiment collected data to assess wheel surface wear on the Sojourner. It used a specially designed rover wheel, with thin films (200 to 1000 angstroms) of aluminum, nickel, and platinum deposited on black, anodized aluminum strips attached to the rover's right center wheel. As the wheel spun in the Martian soil, a photovoltaic sensor monitored changes in film reflectivity. These changes indicated abrasion of the metal films by Martian surface material. Rolling wear data were accumulated by the WAE. Also, at frequent intervals, all the rover wheels, except the WAE test wheel, were locked to hold the rover stationary while the test wheel alone was spun and dug into the Martian regolith. These tests created wear conditions more severe than simple rolling. The WAE will contribute substantially to our knowledge of Martian surface characteristics. Marked abrasion would indicate a surface composed of hard, possibly sharply edged grains, whereas lack of abrasion would suggest a somewhat softer surface. WAE results will be correlated with ground simulations to determine which terrestrial materials behave most like those on Mars. This knowledge will enable a deeper understanding of erosion processes on Mars and the role they play in Martian surface evolution. Preliminary results show that electrostatic charging of the rover wheels sometimes caused dust to accumulate on the WAE wheel, making interpretation of the reflectance data problematic. If electrostatic charging is the mechanism for dust attraction, this indicates that the Martian dust has a size somewhat smaller than 40 microns in diameter. The WAE experiment has detected electrostatic charging in the Martian environment for the first time; however, under conditions when the wheel is relatively clean of Martian dust, flight data now indicate that abrasion has also been detected. Crude limits so far place the hardness of the Martian dust at harder than aluminum but softer than nickel, and place the grain size at somewhat smaller than 40 microns.

Ferguson, Dale C.↗
NASA NTRS1985

Spectral characterization of the Landsat Thematic Mapper sensors

Relative spectral response data for the Landsat-4 and Landsat-4 backup multispectral scanner subsystems (MSS), the protoflight and flight models, are presented and compared to similar data for the Landsat 1, 2 and 3 scanners. Channel (six channels per band) outputs for soil and soybean targets were simulated and compared within each band and between scanners.The principal differences between the spectral responses of the Landsat-4 scanners and previous scanners are discussed. The simulated Landsat-4 scanner outputs were 3 to 10 percent lower in the red band and 3 to 11 percent higher in the first near-IR band than previous scanners for the soybeans targets. The Landsat-4 scanners were generally more uniform from channel to channel within bands than previous scanners. In the upper-band edge of the red band of the protoflight scanner, one channel was markedly different (12 nm) from the rest. For a soybeans target, this nonuniformity resulted in a within-band difference of 6.2 percent in simulated outputs between channels.

Markham, B. L.↗
NASA NTRS2004

Prediction of STS-107 Hypervelocity Flow Fields about the Shuttle Orbiter with Various Wing Leading Edge Damage

Computations were performed for damaged configurations of the Shuttle Orbiter in support of the STS-107 Columbia accident investigation. Two configurations with missing wing leading-edge reinforced carbon-carbon (RCC) panels were evaluated at conditions just prior to the peak heating trajectory point. The initial configuration modeled the Orbiter with an approximate missing RCC panel 6 to determine whether this damage could result in anomalous temperatures measured during the STS-107 reentry. This missing RCC panel 6 computation was found to produce heating augmentation factors of 5 times the nominal heating rates on the side fuselage with lesser heat increases on the front of the OMS pod. This is consistent with the thermocouple and resistance temperature detector sensors from the STS-107 re-entry which observed off nominal high early in the re-entry trajectory. A second damaged configuration modeled the Orbiter with missing RCC panel 9 and included ingestion of the flow into the outboard RCC channel. This computation lowered the level (only 2 times nominal) and moved the location of the heating augmentation on the leeside fuselage relative to the missing RCC panel 6 configuration. The lesser heating augmentation for missing RCC panel 9 was confined near the wing fuselage juncture. Near nominal heating was predicted on the remainder of the side fuselage with some lower than nominal heating on the front surface of the OMS pod. These results for missing RCC panel 9 are consistent with data from the STS-107 re-entry where the heating augmentation was observed to move off the side fuselage and OMS pod sensors at later times in the trajectory. As this solution requires supersonic mass ingestion into the RCC channel, it is probably not an appropriate model prior to penetration of the flow through the spar into the wing structure. It may, however, be representative of the conditions at later times and could account for the movement of the heating signature on the side fuselage.

Pulsonetti, Maria V.↗
NASA NTRS1984

Spectral Characterization of the LANDSAT-4 MSS Sensors

Relative spectral response data for the LANDSAT-4 and LANDSAT-4 backup multispectral scanner subsystems (MSS), the protoflight and flight models are presented and compared to similar data for the LANDSAT 1, 2 and 3 scanners. Channel (six channels per band) outputs for soil and soybean targets were simulated and compared within each band and between scanners. The principal differences between the spectral responses of the LANDSAT-4 scanners and previous scanners are discussed. The simulated LANDSAT-4 scanner outputs were 3 to 10 percent lower in the red band and 3 to 11 percent higher in the first near-IR band than previous scanners for the soybeans targets. The LANDSAT-4 scanners were generally more uniform from channel to channel within bands than previous scanners. In the upper-band edge of the red band of the protoflight scanner, one channel was markedly different (12 nm) from the rest. For a soybeans target, this nonuniformity resulted in a within-band difference of 6.2 percent in simulated outputs between channels.

Markham, B. L.↗
NASA NTRS2009

Using Vanadium in Spinel as a Sensor of Oxygen Fugacity in Meteorites: Applications to Mars, Vesta, and Other Asteroids

Igneous and metamorphic rocks commonly contain a mineral assemblage that allows oxygen fugacity to be calculated or constrained such as FeTi oxides, olivine-opx-spinel, or some other oxybarometer [1]. Some rocks, however, contain a limited mineral assemblage and do not provide constraints on fO2 using mineral equilibria. Good examples of the latter are orthopyroxenites or dunites, such as diogenites, ALH 84001, chassignites, or brachinites. In fact it is no surprise that the fO2 of many of these samples is not well known, other than being "reduced" and below the metal saturation value. In order to bridge this gap in our understanding, we have initiated a study of V in chromites in natural meteorite samples. Because the V pre-edge peak intensity and energy in chromites varies with fO2 (Fig. 1) [2], and this has been calibrated over a large fO 2 range, we can apply this relation to rocks for which we otherwise have no fO2 constraints.

Righter, K.↗
DOE OSTI2013

Nanophotonic Filters and Integrated Networks in Flexible 2D Polymer Photonic Crystals

Polymers have appealing optical, biochemical, and mechanical qualities, including broadband transparency, ease of functionalization, and biocompatibility. However, their low refractive indices have precluded wavelength-scale optical confinement and nanophotonic applications in polymers. Here, we introduce a suspended polymer photonic crystal (SPPC) architecture that enables the implementation of nanophotonic structures typically limited to high-index materials. Using the SPPC platform, we demonstrate nanophotonic band-edge filters, waveguides, and nanocavities featuring quality (Q) factors exceeding 2, 300 and mode volumes (V-mode) below 1.7(l/n) 3 . The unprecedentedly high Q/V-mode ratio results in a spectrally selective enhancement of radiative transitions of embedded emitters via the cavity Purcell effect with an enhancement factor exceeding 100. Moreover, the SPPC architecture allows straightforward integration of nanophotonic networks, shown here by a waveguide-coupled cavity drop filter with sub-nanometer spectral resolution. The nanoscale optical confinement in polymer promises new applications ranging from optical communications to organic opto-electronics, and nanophotonic polymer sensors.

PHOTONIC CRYSTALS↗