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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Addressing the crush of sampling

An overall space information system involves sensing, processing, analyzing, and distributing space-acquired information. These systems may be partitioned into the spacecraft segment, the wideband space-to-ground communication segment, and the ground-based data analysis and distribution segment. The paper discusses NASA's advanced technology programs aimed at providing improved sensors and on-board data systems. Advances in charge-transfer devices, lasers, and microwave technologies will be responsible for major improvements in NASA's sensing and detection capabilities for future missions. These improvements will result in a future data crush that will amplify the data management problem.

Olstad, W. B.↗
NASA NTRS1981

The location and scope of geographic remote sensing training in the United States

Maps displaying the distribution of graduate departments of geography in the United States and enrollments in remote sensing courses in all geography departments during the past two calendar years were compiled. It was anticipated that the two distributions would show a marked similarity since remote sensing is a relatively new geographic tool requiring specialized training to use as well as equipment not normally found in most geography departments. Thus only the larger graduate departments can afford to devote time and resources to this specialty. A broad correspondence does exist between the graduate departments of geography and the courses in remote ensing. However, the correlation is far from complete and the exceptions are frequent and large enough to cast doubt upon the accuracy of the original hypothesis. Whereas many large departments do offer courses in remote sensing, many smaller colleges and universities do also. A number of possible explanations can be offered for the discrepancies: (1) course titles, (2) the liberal arts orientation of geography departments in many universities, (3) job-oriented skills which many smaller departments have emphasized, and (4) in the tight job market many new graduates of even the larger departments have had to accept position in smaller departments and colleges.

Hawley, A. J.↗
NASA NTRS2010

Fiber-Optic Continuous Liquid Sensor for Cryogenic Propellant Gauging

An innovative fiber-optic sensor has been developed for low-thrust-level settled mass gauging with measurement uncertainty <0.5 percent over cryogenic propellant tank fill levels from 2 to 98 percent. The proposed sensor uses a single optical fiber to measure liquid level and liquid distribution of cryogenic propellants. Every point of the sensing fiber is a point sensor that not only distinguishes liquid and vapor, but also measures temperature. This sensor is able to determine the physical location of each point sensor with 1-mm spatial resolution. Acting as a continuous array of numerous liquid/vapor point sensors, the truly distributed optical sensing fiber can be installed in a propellant tank in the same manner as silicon diode point sensor stripes using only a single feedthrough to connect to an optical signal interrogation unit outside the tank. Either water or liquid nitrogen levels can be measured within 1-mm spatial resolution up to a distance of 70 meters from the optical interrogation unit. This liquid-level sensing technique was also compared to the pressure gauge measurement technique in water and liquid nitrogen contained in a vertical copper pipe with a reasonable degree of accuracy. It has been demonstrated that the sensor can measure liquid levels in multiple containers containing water or liquid nitrogen with one signal interrogation unit. The liquid levels measured by the multiple fiber sensors were consistent with those virtually measured by a ruler. The sensing performance of various optical fibers has been measured, and has demonstrated that they can survive after immersion at cryogenic temperatures. The fiber strength in liquid nitrogen has also been measured. Multiple water level tests were also conducted under various actual and theoretical vibration conditions, and demonstrated that the signal-to-noise ratio under these vibration conditions, insofar as it affects measurement accuracy, is manageable and robust enough for a wide variety of spacecraft applications. A simple solution has been developed to absorb optical energy at the termination of the optical sensor, thereby avoiding any feedback to the optical interrogation unit

Xu. Wei↗
NASA NTRS2011

Satellite-Derived Distributions, Inventories and Fluxes of Dissolved and Particulate Organic Matter Along the Northeastern U.S. Continental Margin

Estuaries and the coastal ocean experience a high degree of variability in the composition and concentration of particulate and dissolved organic matter (DOM) as a consequence of riverine and estuarine fluxes of terrigenous DOM, sediments, detritus and nutrients into coastal waters and associated phytoplankton blooms. Our approach integrates biogeochemical measurements, optical properties and remote sensing to examine the distributions and inventories of organic carbon in the U.S. Middle Atlantic Bight and Gulf of Maine. Algorithms developed to retrieve colored DOM (CDOM), Dissolved (DOC) and Particulate Organic Carbon (POC) from NASA's MODIS-Aqua and SeaWiFS satellite sensors are applied to quantify the distributions and inventories of DOC and POC. Horizontal fluxes of DOC and POC from the continental margin to the open ocean are estimated from SeaWiFS and MODIS-Aqua distributions of DOC and POC and horizontal divergence fluxes obtained from the Northeastern North Atlantic ROMS model. SeaWiFS and MODIS imagery reveal the importance of estuarine outflow to the export of CDOM and DOC to the coastal ocean and a net community production of DOC on the shelf.

Mannino, A.↗
NASA NTRS2021

3D Cloud Tomography and Droplet Size Retrieval from Multi-Angle Polarimetric Imaging of Scattered Sunlight from Above

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging,it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomographyof cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3Dpolarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developedconvectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Currenttechniques are indeed based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometrydefaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud droplets, changesits polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and gloryangular regions can be used to infer the droplet size distribution. This work defines and derives a framework for afull 3D tomography of cloud droplets for both their mass concentration in space and their distribution across arange of sizes. This gridded 3D retrieval of key microphysical properties is made tractable by our novel approachthat involves a restructuring and partial linearization of an open-source polarized 3D RT code to accommodate aspecial two-step iterative optimization technique. Physically-realistic synthetic clouds are used to demonstrate themethodology with rigorous uncertainty quantification, while a real-world cloud imaged by AirMSPI is processedto illustrate the new remote sensing capability

Schechner, Yoav Y.↗
NASA NTRS1978

A concept for a transparent data acquisition and distribution system for spaceflight applications

The paper describes the Modular Data System concept of the NASA End-to-End Data System program. Data from a single instrument along with the necessary ancillary data will be assembled into self-contained packets and subsequently transmitted over various communications links (space telemetry channel, ground communications circuits, etc.) to the experimenter's facility in real time; reliable error control coding will be included in each link transmission to protect the integrity of the data packets. A major objective is to make the entire data acquisition and distribution process transparent to the experimenter in the sense that the output terminal of the distribution system will be physically, logically and electrically identical to that of the experiment output channel.

Greene, E. P.↗
NASA NTRS2000

Cirrus Parameter Retrieval by Combined Analysis of Spectral Thermal Infrared and Lidar Sensing from Aircraft and Space

The distribution, radiative and microphysical parameters of cirrus clouds are an important factor for cloud effects on the global radiation balance and climate. Multispectral thermal infrared observation are the most significant method used to remote sense cirrus parameter from current and planned passive satellite observations. Passive sensing alone has the limitation that both the cloud radiative temperature, or height, and the spectral emissivity must be derived in the analysis. Factors such as multiple cloud laying, which is very common, are known to introduce ambiguities in results. The addition of lidar cloud height structure measurements significantly improves retrievals. Such active/passive observations have been applied from the NASA ER-2 high altitude remote sensing aircraft since 1983. Applications include the study of the effective effective particle size of cirrus and application toward remote sensing of the ice/water content of cirrus clouds in addition to radiative parameters. Limitations, accuracy and examples of retrievals are presented. In 1997 a space shuttle hitch hiker experiment was flown which included a new technology Infrared Spectral Imaging Radiometer and a laser altimeter for direct cloud height measurements. A 30 orbit data set to test global application of combined spectral infrared and laser height measurements were obtained. Initial results for cirrus analysis from the shuttle experiment will also be presented.

Spinhirne, James D.↗
NASA NTRS2012

Improved Displacement Transfer Functions for Structure Deformed Shape Predictions Using Discretely Distributed Surface Strains

In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.

Ko, William L.↗
NASA NTRS1996

A Sundial-Atlas Precursor to the TIMED Mission: A Quick-Response Global Investigation into Coupled Lower Thermospheric, Ionospheric, and Mesospheric Physics

The SUNDIAL-ATLAS effort was a global-scale investigation which responded to the science priorities of the ITM Panel, the Integrated SPD Strategy Implementation Plan as a whole, and the need for potential cost-saving design criteria for the TIMED mission. The investigation focused on coupling processes in the ionospheric-thermospheric system, taking advantage of the timelines of the ATLAS-1 mission (March 1992), and the global-scale ground-based measurement and modeling activities of the SUNDIAL program. The collaborative SUNDIAL-ATLAS activity was the first opportunity for global measurements of the chemistry, kinetics, and electrodynamics which couple the E-, Fl-, and F2-regions into a single interactive system. As such, the program represented an important first step in studying global issues; and accordingly, was an important proof of concept experiment relevant to the strategic mission plans for the ITM community and the upcoming intermediate class satellite program called TIMED. To meet its projected goals, TIMED must perform a number of critical measurements and execute a number of correlations that were to be tried and tested for the first time in the SUNDIAL-ATLAS investigation. This was designed to include global correlations of thermospheric and ionospheric composition during quiet and disturbed conditions and the co-registration of global-scale ground-based measurements with along-track satellite diagnostics. The SUNDIAL component of the current investigation addressed this need by acquiring, reducing, and analyzing a multi-sensor database that complemented and extended that which was generated in the ATLAS mission (Atmospheric Laboratory for Applications and Science). The SUNDIAL data defined the state and condition of the global-scale ionosphere in the altitude range from 100 km to the F2-peak. These data specified the peak heights and densities of the E-, Fl-, and F2-regions, along with the global distributions of intermediate, descending, and sequential layers which play a critical role in the dynamo region of the lower ionospheric-thermospheric domain. The data were collected by the SUNDIAL network of more than 50 ground-based stations utilizing ionosondes, radars, photometers, Fabry-Perot interferometers, and total electron content measurements. The data were acquired during a three-week period centered on the eight-day ATLAS-1 mission, which provided image and photometric sensing of the altitude distributions of the major and minor ions and neutrals in the ITM system. This report focuses on the scientific contributions of the SUNDIAL component of the overall investigation. Specific findings are described in seven papers (attached) published in the Journal of Geophysical Research.

Szuszczewicz, E. P.↗
NASA NTRS1996

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Tsang, Leung↗
NASA NTRS2015

Variable-Domain Displacement Transfer Functions for Converting Surface Strains into Deflections for Structural Deformed Shape Predictions

Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions

displacement transfer functions↗
NASA NTRS2007

Chemical-Sensing Cables Detect Potential Threats

Intelligent Optical Systems Inc. (IOS) completed Phase I and II Small Business Innovation Research (SBIR) contracts with NASA's Langley Research Center to develop moisture- and pH-sensitive sensors to detect corrosion or pre-corrosive conditions, warning of potentially dangerous conditions before significant structural damage occurs. This new type of sensor uses a specially manufactured optical fiber whose entire length is chemically sensitive, changing color in response to contact with its target, and demonstrated to detect potentially corrosive moisture incursions to within 2 cm. After completing the work with NASA, the company received a Defense Advanced Research Projects Agency (DARPA) Phase III SBIR to develop the sensors further for detecting chemical warfare agents, for which they proved just as successful. The company then worked with the U.S. Department of Defense (DoD) to fine tune the sensors for detecting potential threats, such as toxic industrial compounds and nerve agents. In addition to the work with government agencies, Intelligent Optical Systems has sold the chemically sensitive fiber optic cables to major automotive and aerospace companies, who are finding a variety of uses for the devices. Marketed under the brand name Distributed Intrinsic Chemical Agent Sensing and Transmission (DICAST), these unique continuous-cable fiber optic chemical sensors can serve in a variety of applications: Corrosive-condition monitoring, aiding experimentation with nontraditional power sources, as an economical means of detecting chemical release in large facilities, as an inexpensive "alarm" systems to alert the user to a change in the chemical environment anywhere along the cable, or in distance-resolved optical time domain reflectometry systems to provide detailed profiles of chemical concentration versus length.

Source record↗
DOE OSTI2025

Accurate Monitoring of an Electrically Energized Casing Source using Fiber Optic Sensing

This report summarizes an investigation of utilizing a Piezoelectric coating on fiber optics to monitor electric fields. The application of interest was monitoring the electric field emitted from a borehole casing being used an an Electromagnetic source in geophysical monitoring. Testing consists of using a water filled vessel with plate electrodes on opposing sides to generate electric fields while lowering a custom designed sensor into the water. The results are compared to what is conventionally available via simulations.

03 NATURAL GAS↗
NASA NTRS1986

Retrieval of aerosol size distribution moments from multiwavelength particulate extinction data

An iterative method for deriving the particle size distribution from multiwavelength satellite remote sensing data is presented and its use illustrated with an application to SAGE II data. The compression size distribution method (CSD) features interpolation and look-up features for relating the coefficients of a least-squares fit as a function of wavelength to parameters of the compression function that have been obtained by Mie calculations. Results are reported of comparisons between particulate radii predicted for the El Chichon volcano aerosol based on SAGE II data and 14 radii measured with NASA flights through the aerosol with aircraft carrying wire impactors.

Livingston, J. M.↗
NASA NTRS1989

Remote sensing of geobotanical trends in East Africa

The spatial and phenological distribution of vegetation was examined in a remote sensing geobotanical study of the East Africa Rift region. Six normalized difference vegetation index (NDVI) AVHRR (advanced very high resolution radiometer) scenes (February, June, and September of both 1984 and 1987) were used as a measure of vegetation presence. NOAA ETOPO-5 elevation and geographic coordinate data were coregistered with the multitemporal NDVI images. Univariate and multivariate statistics indicate that the NDVI values are significantly associated with elevation, latitude, and longitude. This supports the concept of quantifiable, regional gradients that affect large-scale geobotanical studies. A quadratic regression line was fitted to the NDVI, elevation, latitude, and longitudinal data. In this way a regional trend, as affected by elevation, was determined. The deviation of the actual data from this regional trend was displayed as an image, and shows the local climatic and geological influences.

Warner, Timothy A.↗
DOE OSTI2024

Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements

Abstract. Given the importance of constraining cloud droplet number concentrations (Nd) in low-level clouds, we explore two methods for retrieving Nd from surface-based remote sensing that emphasize the information content in lidar measurements. Because Nd is the zeroth moment of the droplet size distribution (DSD), and all remote sensing approaches respond to DSD moments that are at least 2 orders of magnitude greater than the zeroth moment, deriving Nd from remote sensing measurements has significant uncertainty. At minimum, such algorithms require the extrapolation of information from two other measurements that respond to different moments of the DSD. Lidar, for instance, is sensitive to the second moment (cross-sectional area) of the DSD, while other measures from microwave sensors respond to higher-order moments. We develop methods using a simple lidar forward model that demonstrates that the depth to the maximum in lidar-attenuated backscatter (Rmax⁡) is strongly sensitive to Nd when some measure of the liquid water content vertical profile is given or assumed. Knowledge of Rmax⁡ to within 5 m can constrain Nd to within several tens of percent. However, operational lidar networks provide vertical resolutions of > 15 m, making a direct calculation of Nd from Rmax⁡ very uncertain. Therefore, we develop a Bayesian optimal estimation algorithm that brings additional information to the inversion such as lidar-derived extinction and radar reflectivity near the cloud top. This statistical approach provides reasonable characterizations of Nd and effective radius (re) to within approximately a factor of 2 and 30 %, respectively. By comparing surface-derived cloud properties with MODIS satellite and aircraft data collected during the MARCUS and CAPRICORN II campaigns, we demonstrate the utility of the methodology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m −2 ) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m −2 (mean ≈ 350 g m −2 ), while predicted values ranged from 0 to ∼4000 g m −2 (mean ≈ 275 g m −2 ), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m −2 and R 2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling.

Climate change↗